Disentangling the seasonality effects of malaria transmission in the Brazilian Amazon basin.

The evidence of seasonal patterns in malaria epidemiology in the Brazilian Amazon basin indicates the need for a thorough investigation of seasonality in this last and heterogeneous region. Additionally, since these patterns are linked to climate variables, malaria models should also incorporate them. This study applies wavelet analysis to incidence data from 2003 to 2020 in the Epidemiological Surveillance System for Malaria (SIVEP-Malaria) database. A mathematical model with climate-dependent parametrization is proposed to study counts of malaria cases over time based on notification data, temperature and rainfall. The wavelet analysis reveals marked seasonality in states Amazonas and Amapá throughout the study period, and from 2003 to 2012 in Pará. However, these patterns are not as marked in other states such as Acre and Pará in more recent years. The wavelet coherency analysis indicates a strong association between incidence and temperature, especially for the municipalities of Macapá and Manaus, and a similar association for rainfall. The mathematical model fits well with the observed temporal trends in both municipalities. Studies on climate-dependent mathematical models provide a good assessment of the baseline epidemiology of malaria. Additionally, the understanding of seasonality effects and the application of models have great potential as tools for studying interventions for malaria control.

Multiple endemic equilibria in an environmentally-transmitted disease with three disease stages.

We construct, analyze and interpret a mathematical model for an environmental transmitted disease characterized for the existence of three disease stages: acute, severe and asymptomatic. Besides, we consider that severe and asymptomatic cases may present relapse between them. Transmission dynamics driven by the contact rates only occurs when a parameter R∗>1, as normally occur in directly-transmitted or vector-transmitted diseases, but it will not adequately correspond to a basic reproductive number as it depends on environmental parameters. In this case, the forward transcritical bifurcation that exists for R∗<1, becomes a backward bifurcation, producing multiple steady-states, a hysteresis effect and dependence on initial conditions. A threshold parameter for an epidemic outbreak, independent of R∗ is only the ratio of the external contamination inflow shedding rate to the environmental clearance rate. R∗ describes the strength of the transmission to infectious classes other than the I-(acute) type infections. The epidemic outbreak conditions and the structure of R∗ appearing in this model are both responsible for the existence of endemic states.

Optimized microwave-assisted azadirachtin extraction using response surface methodology.

The neem tree (Azadirachta indica A. Juss) is grown mainly for shade, fuel, and numerous non-timber forest products using its leaves, fruit, and bark. It produces an essential oil that is used as a source for obtaining bioinsecticides, with a broad spectrum of action in agricultural production. Its bioinsecticidal activity is due to the presence of triterpenes, such as azadirachtin, a product in continued growth of the global biopesticide market. Optimal conditions for neem oil extraction using response surface methodology (RSM) and microwave-assisted extraction (MAE) methods have been defined. However, the extraction conditions for these methods tend to consume high volumes of organic solvent and long extraction times. The aim of the present study is to determine the optimal conditions for the extraction of azadirachtin from neem seeds in a hydroalcoholic medium using MAE and RSM with a Box-Behnken design (BBD). A BBD was applied to evaluate the effects of the factors, magnetron voltage (X1), extraction time (X2), and pH of the extraction medium (X3), on the yield of the azadirachtin extraction process. The effect of each variable on the extraction yield was studied independently, considering the pure coefficients (linear and quadratic) on the three levels that were studied in the experiments. Moreover, the study experiments were conducted in triplicate, data were presented as mean and standard deviation, homogeneity of variances was estimated using Levene's test, and a two-way ANOVA with Tukey's post hoc analysis was performed to identify the experimental conditions that allowed us to find the highest extraction yield and to analyze whether the response surface model adequately described our data. The most significant effects of the model correspond to quadratic and interaction effects (p < 0.0001); the quadratic terms voltage (X1), extraction time (X2), and pH (X3); and the interaction effects between voltage-pH (X1*X3) and time-pH (X2*X3), which had a significant influence on the model. Moreover, a canonical analysis was performed. The optimal conditions were as follows: 69.22 V, 6.89 min, and a pH value of 4.35, coinciding with the zones shown in the contour plots. Furthermore, the response obtained at the optimal conditions was 37.5 µg of azadirachtin per gram of pretreated seed.

Flow modeling and structural characterization in fungal pellets.

Fungal pellets are hierarchical systems that can be found in an ample variety of applications. Modeling transport phenomena in this type of systems is a challenging but necessary task to provide knowledge-based processes that improve the outcome of their biotechnological applications. In this work, an upscaled model for total mass and momentum transport in fungal pellets is implemented and analyzed, using elements of the volume averaging and adjoint homogenization methods departing from the governing equations at the microscale in the intracellular and extracellular phases. The biomass is assumed to be composed of a non-Newtonian fluid and the organelles impervious to momentum transport are modeled as a rigid solid phase. The upscaled equations contain effective-medium coefficients, which are predicted from the solution of adjoint closure problems in a three-dimensional periodic domains representative of the microstructure. The construction of these domains was performed for Laccaria trichodermophora based on observations of actual biological structures. The upscaled model was validated with direct numerical simulations in homogeneous portions of the pellets core. It is shown that no significant differences are observed when the dolipores are open or closed to fluid flow. By comparing the predictions of the average velocity in the extracellular phase resulting from the upscaled model with those from the classical Darcy equation (i.e., assuming that the biomass is a solid phase) the contribution of the intracellular fluid phase was evidenced. This work sets the foundations for further studies dedicated to transport phenomena in this type of systems.

Modeling Zinc Absorption in the Adult Population of Colombia: Insights for Nutritional Evaluation and Intervention Strategies.

Zinc is a vital trace element, yet its deficiency is common in various populations. This study addresses the gap in understanding zinc intake and its relationship with key nutritional parameters in a Colombian population. We analyzed data from 12,987 individuals, focusing on the daily intake of zinc, phytate, protein, and calcium, and used the phytate/zinc molar ratio as an input parameter in the Miller et al. (2013) model. This model was employed to estimate the total absorbed zinc (TAZ) and the fractional absorption of zinc (FAZ). Our findings highlight a general trend towards insufficient intake compared to the standards of the Institute of Medicine (IOM) and Colombia, with a significant percentage of the population falling below the estimated average requirement (EAR) and recommended daily allowance (RDA) for zinc, underscoring the need for targeted nutritional strategies. Our study contributes to a broader understanding of zinc nutrition and public health implications in Colombia, providing a basis for future dietary guidelines and health interventions.

Analysis of a fractional-order model for dengue transmission dynamics with quarantine and vaccination measures.

A comprehensive mathematical model is proposed to study two strains of dengue virus with saturated incidence rates and quarantine measures. Imperfect dengue vaccination is also assumed in the model. Existence, uniqueness and stability of the proposed model are proved using the results from fixed point and degree theory. Additionally, well constructed Lyapunov function candidates are also applied to prove the global stability of infection-free equilibria. It is also demonstrated that the model is generalized Ulam-Hyers stable under some appropriate conditions. The model is fitted to the real data of dengue epidemic taken from the city of Espirito Santo in Brazil. For the approximate solution of the model, a non-standard finite difference(NSFD) approach is applied. Sensitivity analysis is also carried out to show the influence of different parameters involved in the model. The behaviour of the NSFD is also assessed under different denominator functions and it is observed that the choice of the denominator function could influence the solution trajectories. Different scenario analysis are also assessed when the reproduction number is below or above one. Furthermore, simulations are also presented to assess the epidemiological impact of dengue vaccination and quarantine measures for infected individuals.

A Dynamic Fitting Strategy for Physiological Models: A Case Study of a Cardiorespiratory Model for the Simulation of Incremental Aerobic Exercise.

Using mathematical models of physiological systems in medicine has allowed for the development of diagnostic, treatment, and medical educational tools. However, their complexity restricts, in most cases, their application for predictive, preventive, and personalized purposes. Although there are strategies that reduce the complexity of applying models based on fitting techniques, most of them are focused on a single instant of time, neglecting the effect of the system's temporal evolution. The objective of this research was to introduce a dynamic fitting strategy for physiological models with an extensive array of parameters and a constrained amount of experimental data. The proposed strategy focused on obtaining better predictions based on the temporal trends in the system's parameters and being capable of predicting future states. The study utilized a cardiorespiratory model as a case study. Experimental data from a longitudinal study of healthy adult subjects undergoing aerobic exercise were used for fitting and validation. The model predictions obtained in a steady state using the proposed strategy and the traditional single-fit approach were compared. The most successful outcomes were primarily linked to the proposed strategy, exhibiting better overall results regarding accuracy and behavior than the traditional population fitting approach at a single instant in time. The results evidenced the usefulness of the dynamic fitting strategy, highlighting its use for predictive, preventive, and personalized applications.

Unraveling Drug Delivery from Cyclodextrin Polymer-Coated Breast Implants: Integrating a Unidirectional Diffusion Mathematical Model with COMSOL Simulations.

Breast cancer ranks among the most commonly diagnosed cancers worldwide and bears the highest mortality rate. As an integral component of cancer treatment, mastectomy entails the complete removal of the affected breast. Typically, breast reconstruction, involving the use of silicone implants (augmentation mammaplasty), is employed to address the aftermath of mastectomy. To mitigate postoperative risks associated with mammaplasty, such as capsular contracture or bacterial infections, the functionalization of breast implants with coatings of cyclodextrin polymers as drug delivery systems represents an excellent alternative. In this context, our work focuses on the application of a mathematical model for simulating drug release from breast implants coated with cyclodextrin polymers. The proposed model considers a unidirectional diffusion process following Fick's second law, which was solved using the orthogonal collocation method, a numerical technique employed to approximate solutions for ordinary and partial differential equations. We conducted simulations to obtain release profiles for three therapeutic molecules: pirfenidone, used for preventing capsular contracture; rose Bengal, an anticancer agent; and the antimicrobial peptide KR-12. Furthermore, we calculated the diffusion profiles of these drugs through the cyclodextrin polymers, determining parameters related to diffusivity, solute solid-liquid partition coefficients, and the Sherwood number. Finally, integrating these parameters in COMSOL multiphysics simulations, the unidirectional diffusion mathematical model was validated.

Spatial analysis of Dengue through the reproduction numbers relating to socioeconomic features: Case studies on two Brazilian urban centers.

The study of the propagation of infectious diseases in urban centers finds a close connection with their population's social characteristics and behavior. This work performs a spatial analysis of dengue cases in urban centers based on the basic reproduction numbers, R0, and incidence by planning areas (PAs), as well as their correlations with the Human Development Index (HDI) and the number of trips. We analyzed dengue epidemics in 2002 at two Brazilian urban centers, Belo Horizonte (BH) and Rio de Janeiro (RJ), using PAs as spatial units. Our results reveal heterogeneous spatial scenarios for both cities, with very weak correlations between R0 and both the number of trips and the HDI; in BH, the values of R0 show a less spatial heterogeneous pattern than in RJ. For BH, there are moderate correlations between incidence and both the number of trips and the HDI; meanwhile, they weakly correlate for RJ. Finally, the absence of strong correlations between the considered measures indicates that the transmission process should be treated considering the city as a whole.

Describing and understanding the time course of the property listing task.

To study linguistically coded concepts, researchers often resort to the Property Listing Task (PLT). In a PLT, participants are asked to list properties that describe a concept (e.g., for DOG, subjects may list "is a pet", "has four legs", etc.). When PLT data is collected for many concepts, researchers obtain Conceptual Properties Norms (CPNs), which are used to study semantic content and as a source of control variables. Though the PLT and CPNs are widely used across psychology, only recently a model that describes the listing course of a PLT has been developed and validated. That original model describes the listing course using order of production of properties. Here we go a step beyond and validate the model using response times (RT), i.e., the time from cue onset to property listing. Our results show that RT data exhibits the same regularities observed in the previous model, but now we can also analyze the time course, i.e., dynamics of the PLT. As such, the RT validated model may be applied to study several similar memory retrieval tasks, such as the Free Listing Task, Verbal Fluidity Task, and to research related cognitive processes. To illustrate those kinds of analyses, we present a brief example of the difference in PLT's dynamics between listing properties for abstract versus concrete concepts, which shows that the model may be fruitfully applied to study concepts.

Simplifying two-vector mechanics calculations for challenging tooth movements.

The purpose of this article was to describe a simple graphical driven method for determining the necessary two-vector mechanics (TVM) as an alternative solution to the ideal or single force. In orthodontics, some tooth movements are difficult to achieve, mainly because of the impossibility of getting the point of application for the necessary force system. Given two points in biomechanically accessible areas, adding together two vectors applied to those points will result in an equivalent force system. The method was developed based on previous research, 3,880 hypothetical cases were analyzed to determine the trends between the resulting forces and their relative locations. A graphical driven TVM method (GTVM) for establishing the necessary TVM is presented in a manner that combine different procedures from the traditional method that simplify the analysis and may allow the user to perform more complex orthodontic cases making easier to compare systems of force equivalents.

Mathematical modeling for operative improvement of the decoloration of Acid Red 27 by a novel microbial consortium of Trametes versicolor and Pseudomonas putida: A multivariate sensitivity analysis.

In this work, it is presented a first approach of a mathematical and kinetic analysis for improving the decoloration and further degradation process of an azo dye named acid red 27 (AR27), by means of a novel microbial consortium formed by the fungus Trametes versicolor and the bacterium Pseudomonas putida. A multivariate analysis was carried out by simulating scenarios with different operating conditions and developing a specific mathematical model based on kinetic equations describing all stages of the biological process, from microbial growth and substrate consuming to decoloration and degradation of intermediate compounds. Additionally, a sensitivity analysis was performed by using a factorial design and the Response Surface Method (RSM), for determining individual and interactive effects of variables like, initial glucose concentration, initial dye concentration and the moment in time for bacterial inoculation, on response variables assessed in terms of the minimum time for: full decoloration of AR27 (R1 = 2.375 days); maximum production of aromatic metabolites (R2 = 1.575 days); and full depletion of aromatic metabolites (R3 = 12.9 days). Using RSM the following conditions improved the biological process, being: an initial glucose concentration of 20 g l-1, an initial AR27 concentration of 0.2 g l-1 and an inoculation moment in time of P. putida at day 1. The mathematical model is a feasible tool for describing AR27 decoloration and its further degradation by the microbial consortium of T. versicolor and P. putida, this model will also work as a mathematical basis for designing novel bio-reaction systems than can operate with the same principle of the described consortium.

A model for the dynamics of expanded CAG repeat alleles: ATXN2 and ATXN3 as prototypes.

Background: Spinocerebellar ataxia types 2 (SCA2) and 3 (SCA3/MJD) are diseases due to dominant unstable expansions of CAG repeats (CAGexp). Age of onset of symptoms (AO) correlates with the CAGexp length. Repeat instability leads to increases in the expanded repeats, to important AO anticipations and to the eventual extinction of lineages. Because of that, compensatory forces are expected to act on the maintenance of expanded alleles, but they are poorly understood. Objectives: we described the CAGexp dynamics, adapting a classical equation and aiming to estimate for how many generations will the descendants of a de novo expansion last. Methods: A mathematical model was adapted to encompass anticipation, fitness, and allelic segregation; and empirical data fed the model. The arbitrated ancestral mutations included in the model had the lowest CAGexp and the highest AO described in the literature. One thousand generations were simulated until the alleles were eliminated, fixed, or 650 generations had passed. Results: All SCA2 lineages were eliminated in a median of 10 generations. In SCA3/MJD lineages, 593 were eliminated in a median of 29 generations. The other ones were eliminated due to anticipation after the 650th generation or remained indefinitely with CAG repeats transitioning between expanded and unexpanded ranges. Discussion: the model predicted outcomes compatible with empirical data - the very old ancestral SCA3/MJD haplotype, and the de novo SCA2 expansions -, which previously seemed to be contradictory. This model accommodates these data into understandable dynamics and might be useful for other CAGexp disorders.

Computational Analysis of the Influence of Menopause and Ageing on Bone Mineral Density, Exploring the Impact of Bone Turnover and Focal Bone Balance-A Study on Overload and Underload Scenarios.

This study aims to investigate the impact of hormonal imbalances during menopause, compounded by the natural ageing process, on bone health. Specifically, it examines the effects of increased bone turnover and focal bone balance on bone mass. A three-dimensional computational bone remodeling model was employed to simulate the response of the femur to habitual loads over a 19-year period, spanning premenopause, menopause, and postmenopause. The model was calibrated using experimental bone mineral density data from the literature to ensure accurate simulations. The study reveals that individual alterations in bone turnover or focal bone balance do not fully account for the observed experimental outcomes. Instead, simultaneous changes in both factors provide a more comprehensive explanation, leading to increased porosity while maintaining the material-to-apparent density ratio. Additionally, different load scenarios were tested, demonstrating that reaching the clinical osteoporosis threshold is independent of the timing of load changes. However, underload scenarios resulted in the threshold being reached approximately 6 years earlier than overload scenarios. These findings hold significant implications for strategies aimed at delaying the onset of osteoporosis and minimizing fracture risks through targeted mechanical stimulation during the early stages of menopause.

Ecotoxicological assessment of natural soil amended with sewage sludge: the impacts on soil edaphic organisms and microbial community.

Sewage sludge usage as agricultural soil amendment is a well-known practice employed worldwide. However, certain components may pose risks to the soil ecosystem. For a better verification of the potential adverse effects on the soil biota, biological assays have become an indispensable tool for an accurate understanding of the residue's behavior on soil, as well as its potential toxicity. Accordingly, to properly assess the effects of natural tropical soil (Oxisoil) amended with sewage sludge, we conducted toxicological tests with edaphic organisms (Enchytraeus crypticus and Folsomia candida) and microbial biomass (through respirometric assessment). Results indicate that E. crypticus and F. candida present similar reproduction sensitivity behavior to sewage sludge. For the microbiological analysis, the results suggest that microbial activity was stimulated by sludge application. For further evaluation of respiration of the microbial community and CO2 stabilization values behavior, Ford-Walford modeling was applied and presented limit values for sludge application in soil for 1.5 g kg-1 and 15.0 g kg-1 of, approximately, 55 mg and 88 mg, respectively. CO2 releases were faster and reached stability within 18 weeks for the soil with higher sludge content (15.0 g kg-1 of dry soil). In contrast, CO2 releases were slower for the soil with lower sludge content (1.5 g kg-1 of dry soil), and until the experiment's final period (21 weeks) respiration behavior did not reach stability. This study indicates that the stabilized sewage sludge, at the considered recommended application rate, presents a low toxicity risk for the studied bioindicators, being suitable for agricultural use.

Mathematical Model of the Spread of Hantavirus Infection.

A mathematical epidemiological model incorporating the mobility of rodents and human groups among zones of less or major contact between them is presented. The hantavirus infection dynamics is expressed using a model type SEIR (Susceptible-Exposed-Infectious-Removed), which incorporates the displacement of the rodent and the human, between the urban and rural sector, the latter being subdivided in populated and non-populated. The results show the impact that rodent or human displacement may have on the propagation of hantavirus infection. Human mobility is more significant than rodents in increasing the number of hantavirus infection cases. The results found may be used as a reference by the health authorities to develop more specific campaigns on the territorial dynamics of the rodent, attend to the mobility of humans in these territories, mainly agricultural and forestry workers, and strengthen control-prevention actions in the community, to prevent future outbreaks that are fatal.

A soil water indicator for a dynamic model of crop and soil water interaction.

Water scarcity is a critical issue in agriculture, and the development of reliable methods for determining soil water content is crucial for effective water management. This study proposes a novel, theoretical, non-physiological indicator of soil water content obtained by applying the next-generation matrix method, which reflects the water-soil-crop dynamics and identifies the minimum viable value of soil water content for crop growth. The development of this indicator is based on a two-dimensional, nonlinear dynamic that considers two different irrigation scenarios: the first scenario involves constant irrigation, and the second scenario irrigates in regular periods by assuming each irrigation as an impulse in the system. The analysis considers the study of the local stability of the system by incorporating parameters involved in the water-soil-crop dynamics. We established a criterion for identifying the minimum viable value of soil water content for crop growth over time. Finally, the model was calibrated and validated using data from an independent field study on apple orchards and a tomato crop obtained from a previous field study. Our results suggest the advantages of using this theoretical approach in modeling the plants' conditions under water scarcity as the first step before an empirical model. The proposed indicator has some limitations, suggesting the need for future studies that consider other factors that affect soil water content.

A primer on modelling pancreatic islets: from models of coupled ß-cells to multicellular islet models.

Pancreatic islets are mini-organs composed of hundreds or thousands of ɑ, ß and δ-cells, which, respectively, secrete glucagon, insulin and somatostatin, key hormones for the regulation of blood glucose. In pancreatic islets, hormone secretion is tightly regulated by both internal and external mechanisms, including electrical communication and paracrine signaling between islet cells. Given its complexity, the experimental study of pancreatic islets has been complemented with computational modeling as a tool to gain a better understanding about how all the mechanisms involved at different levels of organization interact. In this review, we describe how multicellular models of pancreatic cells have evolved from the early models of electrically coupled ß-cells to models in which experimentally derived architectures and both electrical and paracrine signals have been considered.

Biomass and lipid production by the native green microalgae Chlorella sorokiniana in response to nutrients, light intensity, and carbon dioxide: experimental and modeling approach.

Introduction: Microalgae are photosynthetic cells that can produce third-generation biofuels and other commercial compounds. Microalgal growth is influenced by two main parameters: light intensity and carbon dioxide concentration, which represent the energy and carbon source, respectively. For photosynthesis, the optimum values of abiotic factors vary among species. Methods: In this study, the microalga Chlorella sorokiniana was isolated from a freshwater lake. It was identified using molecular analysis of the ribosomal internal transcribed spacer. A single-factor design of experiments in 250-mL Erlenmeyer flasks was used to evaluate which concentrations of nitrogen and phosphorus increase the production of biomass and lipids. The response surface methodology was used with a 32-factorial design (light intensity and CO2 were used to evaluate its effect on biomass, lipid production, and specific growth rates, in 200-mL tubular photobioreactors (PBRs)). Results and Discussion: Low levels of light lead to lipid accumulation, while higher levels of light lead to the synthesis of cell biomass. The highest biomass and lipid production were 0.705 ± 0.04 g/L and 55.1% ± 4.1%, respectively. A mathematical model was proposed in order to describe the main phenomena occurring in the culture, such as oxygen and CO2 mass transfer and the effect of light and nutrients on the growth of microalgae. The main novelties of this work were molecular identification of the strain, optimization of culture conditions for the indigenous microalgae species that were isolated, and formulation of a model that describes the behavior of the culture.

Final size and partial distance estimate for a two-group SEIRD model.

In this paper we consider a SEIRD epidemic model for a population composed by two groups of individuals with asymmetric interaction. Given an approximate solution for the two-group model, we estimate the error of this approximation to the unknown solution to the second group based on the known error that the approximation has with respect to the solution to the first group. We also study the final size of the epidemic for each group. We illustrate our results with the spread of the coronavirus disease 2019 (COVID-19) pandemic in the New York County (USA) for the initial stage of the contamination, and in the cities of Petrolina and Juazeiro (Brazil).