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Environmental monitoring is crucial for assessing the overall state of the ecosystems in terms of contaminant impact and chemical landscape. The use of honey bee (Apis mellifera) colonies considerably eases the sampling activities, as honey bees are exposed to a wide range of substances that are transported and accumulated within the beehives. In this work, combining low-resolution and high-resolution mass spectrometry, the APIStrip passive sampler has been employed to evaluate the presence of pesticide residues and the overall characterization of beehive environments. A total of 180 APIStrips have been deployed in 10 Danish apiaries, located in different landscapes, during a five-month sampling period. The targeted methodology for pesticide analysis was based on gas and liquid chromatography coupled with triple quadrupole mass spectrometry, covering 430 pesticide residues. A total of 29 pesticide residues were identified (fluopyram and azoxystrobin being the most frequently detected), with remarkable differences in the pesticide load between apiaries. For its part, the use of non-targeted approaches through liquid chromatography coupled with an Orbitrap mass spectrometer allowed the detection of unknown compounds that were specific of certain environments. Natural products such as eupatilin and gnaphaliin, which are derived from plant sources, were present exclusively in one of the apiaries. Additionally, the detection of drimane sesquiterpenoids, including compounds potentially originating from the Aspergillus genus, suggests the capability of APIStrips to early detect fungal contamination within beehives. This dual approach of low- and high-resolution mass spectrometry maximizes the analytical potential of APIStrips as a tool capable of detecting a wide range of substances with implications for both agricultural practices and ecological health., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Amadeo R. Fernndez-Alba reports financial support was provided by European Commission. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: One of the main lessons of the COVID-19 pandemic is that we must prepare to face another pandemic like it. Consequently, this article aims to develop a general framework consisting of epidemiological modeling and a practical identifiability approach to assess combined vaccination and non-pharmaceutical intervention (NPI) strategies for the dynamics of any transmissible disease., Materials and Methods: Epidemiological modeling of the present work relies on delay differential equations describing time variation and transitions between suitable compartments. The practical identifiability approach relies on parameter optimization, a parametric bootstrap technique, and data processing. We implemented a careful parameter optimization algorithm by searching for suitable initialization according to each processed dataset. In addition, we implemented a parametric bootstrap technique to accurately predict the ICU curve trend in the medium term and assess vaccination., Results: We show the framework's calibration capabilities for several processed COVID-19 datasets of different regions of Chile. We found a unique range of parameters that works well for every dataset and provides overall numerical stability and convergence for parameter optimization. Consequently, the framework produces outstanding results concerning quantitative tracking of COVID-19 dynamics. In addition, it allows us to accurately predict the ICU curve trend in the medium term and assess vaccination. Finally, it is reproducible since we provide open-source codes that consider parameter initialization standardized for every dataset., Conclusion: This work attempts to implement a holistic and general modeling framework for quantitative tracking of the dynamics of any transmissible disease, focusing on accurately predicting the ICU curve trend in the medium term and assessing vaccination. The scientific community could adapt it to evaluate the impact of combined vaccination and NPIs strategies for COVID-19 or any transmissible disease in any country and help visualize the potential effects of implemented plans by policymakers. In future work, we want to improve the computational cost of the parametric bootstrap technique or use another more efficient technique. The aim would be to reconstruct epidemiological curves to predict the combined NPIs and vaccination policies' impact on the ICU curve trend in real-time, providing scientific evidence to help anticipate policymakers' decisions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cumsille, Rojas-Díaz and Conca.)

A growing body of evidence indicates that dietary polyphenols could be used as an early intervention to treat glucose-insulin (G-I) dysregulation. However, studies report heterogeneous information, and the targets of the intervention remain largely elusive. In this work, we provide a general methodology to quantify the effects of any given polyphenol-rich food or formulae over glycemic regulation in a patient-wise manner using an Oral Glucose Tolerance Test (OGTT). We use a mathematical model to represent individual OGTT curves as the coordinated action of subsystems, each one described by a parameter with physiological interpretation. Using the parameter values calculated for a cohort of 1198 individuals, we propose a statistical model to calculate the risk of dysglycemia and the coordination among subsystems for each subject, thus providing a continuous and individual health assessment. This method allows identifying individuals at high risk of dysglycemia-which would have been missed with traditional binary diagnostic methods-enabling early nutritional intervention with a polyphenol-supplemented diet where it is most effective and desirable. Besides, the proposed methodology assesses the effectiveness of interventions over time when applied to the OGTT curves of a treated individual. We illustrate the use of this method in a case study to assess the dose-dependent effects of Delphinol® on reducing dysglycemia risk and improving the coordination between subsystems. Finally, this strategy enables, on the one hand, the use of low-cost, non-invasive methods in population-scale nutritional studies. On the other hand, it will help practitioners assess the effectiveness of an intervention based on individual vulnerabilities and adapt the treatment to manage dysglycemia and avoid its progression into disease., Competing Interests: AL is currently employed by MNL-Group, company producing Delphinol®. However, he did not participate in conceptualisation of the study, data collection, investigation, processing, or analysis of the results. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Olivera-Nappa, Contreras, Tevy, Medina-Ortiz, Leschot, Vigil and Conca.)

Wolbachia are endosymbiont bacteria known to infect arthropods causing different effects, such as cytoplasmic incompatibility and pathogen blocking in Aedes aegypti. Although several Wolbachia strains have been studied, there is little knowledge regarding the relationship between this bacterium and their hosts, particularly on their obligate endosymbiont nature and its pathogen blocking ability. Motivated by the potential applications on disease control, we developed a genome-scale model of two Wolbachia strains: w Mel and the strongest Dengue blocking strain known to date: w MelPop. The obtained metabolic reconstructions exhibit an energy metabolism relying mainly on amino acids and lipid transport to support cell growth that is consistent with altered lipid and cholesterol metabolism in Wolbachia -infected mosquitoes. The obtained metabolic reconstruction was then coupled with a reconstructed mosquito model to retrieve a symbiotic genome-scale model accounting for 1,636 genes and 6,408 reactions of the Aedes aegypti- Wolbachia interaction system. Simulation of an arboviral infection in the obtained novel symbiotic model represents a metabolic scenario characterized by pathogen blocking in higher titer Wolbachia strains, showing that pathogen blocking by Wolbachia infection is consistent with competition for lipid and amino acid resources between arbovirus and this endosymbiotic bacteria. IMPORTANCE Arboviral diseases such as Zika and Dengue have been on the rise mainly due to climate change, and the development of new treatments and strategies to limit their spreading is needed. The use of Wolbachia as an approach for disease control has motivated new research related to the characterization of the mechanisms that underlie its pathogen-blocking properties. In this work, we propose a new approach for studying the metabolic interactions between Aedes aegypti and Wolbachia using genome-scale models, finding that pathogen blocking is mainly influenced by competition for the resources required for Wolbachia and viral replication.

Existing mathematical models for the glucose-insulin (G-I) dynamics often involve variables that are not susceptible to direct measurement. Standard clinical tests for measuring G-I levels for diagnosing potential diseases are simple and relatively cheap, but seldom give enough information to allow the identification of model parameters within the range in which they have a biological meaning, thus generating a gap between mathematical modeling and any possible physiological explanation or clinical interpretation. In the present work, we present a synthetic mathematical model to represent the G-I dynamics in an Oral Glucose Tolerance Test (OGTT), which involves for the first time for OGTT-related models, Delay Differential Equations. Our model can represent the radically different behaviors observed in a studied cohort of 407 normoglycemic patients (the largest analyzed so far in parameter fitting experiments), all masked under the current threshold-based normality criteria. We also propose a novel approach to solve the parameter fitting inverse problem, involving the clustering of different G-I profiles, a simulation-based exploration of the feasible set, and the construction of an information function which reshapes it, based on the clinical records, experimental uncertainties, and physiological criteria. This method allowed an individual-wise recognition of the parameters of our model using small size OGTT data (5 measurements) directly, without modifying the routine procedures or requiring particular clinical setups. Therefore, our methodology can be easily applied to gain parametric insights to complement the existing tools for the diagnosis of G-I dysregulations. We tested the parameter stability and sensitivity for individual subjects, and an empirical relationship between such indexes and curve shapes was spotted. Since different G-I profiles, under the light of our model, are related to different physiological mechanisms, the present method offers a tool for personally-oriented diagnosis and treatment and to better define new health criteria., (Copyright © 2020 Contreras, Medina-Ortiz, Conca and Olivera-Nappa.)

Wolbachia are alpha-proteobacteria known to infect arthropods, which are of interest for disease control since they have been associated with improved resistance to viral infection. Although several genomes for different strains have been sequenced, there is little knowledge regarding the relationship between this bacterium and their hosts, particularly on their dependency for survival. Motivated by the potential applications on disease control, we developed genome-scale models of four Wolbachia strains known to infect arthropods: wAlbB (Aedes albopictus), wVitA (Nasonia vitripennis), wMel and wMelPop (Drosophila melanogaster). The obtained metabolic reconstructions exhibit a metabolism relying mainly on amino acids for energy production and biomass synthesis. A gap analysis was performed to detect metabolic candidates which could explain the endosymbiotic nature of this bacterium, finding that amino acids, requirements for ubiquinone precursors and provisioning of metabolites such as riboflavin could play a crucial role in this relationship. This work provides a systems biology perspective for studying the relationship of Wolbachia with its host and the development of new approaches for control of the spread of arboviral diseases. This approach, where metabolic gaps are key objects of study instead of just additions to complete a model, could be applied to other endosymbiotic bacteria of interest., Competing Interests: The authors have declared that no competing interests exist.

In this work we develop a general mathematical model and devise a practical identifiability approach for gastrointestinal stromal tumor (GIST) metastasis to the liver, with the aim of quantitatively describing therapy failure due to drug resistance. To this end, we have modeled metastatic growth and therapy failure produced by resistance to two standard treatments based on tyrosine kinase inhibitors (Imatinib and Sunitinib) that have been observed clinically in patients with GIST metastasis to the liver. The parameter identification problem is difficult to solve, since there are no general results on this issue for models based on ordinary differential equations (ODE) like the ones studied here. We propose a general modeling framework based on ODE for GIST metastatic growth and therapy failure due to drug resistance and analyzed five different model variants, using medical image observations (CT scans) from patients that exhibit drug resistance. The associated parameter estimation problem was solved using the Nelder-Mead simplex algorithm, by adding a regularization term to the objective function to address model instability, and assessing the agreement of either an absolute or proportional error in the objective function. We compared the goodness of fit to data for the proposed model variants, as well as evaluated both error forms in order to improve parameter estimation results. From the model variants analyzed, we identified the one that provides the best fit to all the available patient data sets, as well as the best assumption in computing the objective function (absolute or proportional error). This is the first work that reports mathematical models capable of capturing and quantitatively describing therapy failure due to drug resistance based on clinical images in a patient-specific manner., Competing Interests: The authors have declared that no competing interests exist.

Background: There is controversy about the outcome of patients with acute myocarditis (AM), and data are lacking on how patients admitted with suspected AM are managed. We report characteristics, in-hospital management, and long-term outcome of patients with AM based on a retrospective multicenter registry from 19 Italian hospitals., Methods: A total of 684 patients with suspected AM and recent onset of symptoms (<30 days) were screened between May 2001 and February 2017. Patients >70 years of age and those >50 years of age without coronary angiography were excluded. The final study population comprised 443 patients (median age, 34 years; 19.4% female) with AM diagnosed by either endomyocardial biopsy or increased troponin plus edema and late gadolinium enhancement at cardiac magnetic resonance., Results: At presentation, 118 patients (26.6%) had left ventricular ejection fraction <50%, sustained ventricular arrhythmias, or a low cardiac output syndrome, whereas 325 (73.4%) had no such complications. Endomyocardial biopsy was performed in 56 of 443 (12.6%), and a baseline cardiac magnetic resonance was performed in 415 of 443 (93.7%). Cardiac mortality plus heart transplantation rates at 1 and 5 years were 3.0% and 4.1%. Cardiac mortality plus heart transplantation rates were 11.3% and 14.7% in patients with complicated presentation and 0% in uncomplicated cases (log-rank P<0.0001). Major AM-related cardiac events after the acute phase (postdischarge death and heart transplantation, sustained ventricular arrhythmias treated with electric shock or ablation, symptomatic heart failure needing device implantation) occurred in 2.8% at the 5-year follow-up, with a higher incidence in patients with complicated forms (10.8% versus 0% in uncomplicated AM; log-rank P<0.0001). β-Adrenoceptor blockers were the most frequently used medications both in complicated (61.9%) and in uncomplicated forms (53.8%; P=0.18). After a median time of 196 days, 200 patients had follow-up cardiac magnetic resonance, and 8 of 55 (14.5%) with complications at presentation had left ventricular ejection fraction <50% compared with 1 of 145 (0.7%) of those with uncomplicated presentation., Conclusions: In this contemporary study, overall serious adverse events after AM were lower than previously reported. However, patients with left ventricular ejection fraction <50%, ventricular arrhythmias, or low cardiac output syndrome at presentation were at higher risk compared with uncomplicated cases that had a benign prognosis and low risk of subsequent left ventricular systolic dysfunction.

One of the main challenges in cancer modelling is to improve the knowledge of tumor progression in areas related to tumor growth, tumor-induced angiogenesis and targeted therapies efficacy. For this purpose, incorporate the expertise from applied mathematicians, biologists and physicians is highly desirable. Despite the existence of a very wide range of models, involving many stages in cancer progression, few models have been proposed to take into account all relevant processes in tumor progression, in particular the effect of systemic treatments and angiogenesis. Composite biological experiments, both in vitro and in vivo, in addition with mathematical modelling can provide a better understanding of theses aspects. In this work we proposed that a rational experimental design associated with mathematical modelling could provide new insights into cancer progression. To accomplish this task, we reviewed mathematical models and cancer biology literature, describing in detail the basic principles of mathematical modelling. We also analyze how experimental data regarding tumor cells proliferation and angiogenesis in vitro may fit with mathematical modelling in order to reconstruct in vivo tumor evolution. Additionally, we explained the mathematical methodology in a comprehensible way in order to facilitate its future use by the scientific community.

Background: Iron is essential for the maintenance of basic cellular processes. In the regulation of its cellular levels, ferritin acts as the main intracellular iron storage protein. In this work we present a mathematical model for the dynamics of iron storage in ferritin during the process of intestinal iron absorption. A set of differential equations were established considering kinetic expressions for the main reactions and mass balances for ferritin, iron and a discrete population of ferritin species defined by their respective iron content., Results: Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels. Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP). Ferritin stabilizes the cLIP for a wide range of total intracellular iron concentrations, but the model predicts an exponential increment of the cLIP at an iron content > 2,500 Fe/ferritin protein cage, when the storage capacity of ferritin is exceeded., Conclusions: The results presented support the role of ferritin as an iron buffer in a cellular system. Moreover, the model predicts desirable characteristics for a buffer protein such as effective removal of excess iron, which keeps intracellular cLIP levels approximately constant even when large perturbations are introduced, and a freely available source of iron under iron starvation. In addition, the simulated dynamics of the iron removal process are extremely fast, with ferritin acting as a first defense against dangerous iron fluctuations and providing the time required by the cell to activate slower transcriptional regulation mechanisms and adapt to iron stress conditions. In summary, the model captures the complexity of the iron-ferritin equilibrium, and can be used for further theoretical exploration of the role of ferritin in the regulation of intracellular labile iron levels and, in particular, as a relevant regulator of transepithelial iron transport during the process of intestinal iron absorption.

We have fabricated miniature implantable fluorescence sensors for continuous fluorescence sensing applications in living subjects. These monolithically integrated GaAs-based sensors incorporate a 675 nm vertical-cavity surface-emitting laser (VCSEL), a GaAs PIN photodiode, and a fluorescence emission filter. We demonstrate high detection sensitivity for Cy5.5 far-red dye (50 nanoMolar) in living tissue, limited by the intrinsic background autofluorescence. These low cost, sensitive and scalable sensors are promising for long-term continuous monitoring of molecular dynamics for biomedical studies in freely moving animals.

Objectives: We sought to determine the feasibility of cardiac computed tomography (CT) to detect significant differences in the extent of left ventricular dyssynchrony in heart failure (HF) patients with wide QRS, HF patients with narrow QRS, and age-matched controls., Background: The degree of mechanical dyssynchrony has been suggested as a predictor of response to cardiac resynchronization therapy. There have been no published reports of dyssynchrony assessment with the use of CT., Methods: Thirty-eight subjects underwent electrocardiogram-gated contrast-enhanced 64-slice multidetector CT. The left ventricular endocardial and epicardial boundaries were delineated from short-axis images reconstructed at 10% phase increments of the cardiac cycle. Global and segmental CT dyssynchrony metrics that used changes in wall thickness, wall motion, and volume over time were assessed for reproducibility. We defined a global metric using changes in wall thickness as the dyssynchrony index (DI)., Results: The DI was the most reproducible metric (interobserver and intraobserver intraclass correlation coefficients >/=0.94, p < 0.0001) and was used to determine differences between the 3 groups: HF-wide QRS group (ejection fraction [EF] 22 +/- 8%, QRS 163 +/- 28 ms), HF-narrow QRS (EF 26 +/- 7%, QRS 96 +/- 11 ms), and age-matched control subjects (EF 64 +/- 5%, QRS 87 +/- 9 ms). Mean DI was significantly different between the 3 groups (HF-wide QRS: 152 +/- 44 ms, HF-narrow QRS: 121 +/- 58 ms, and control subjects: 65 +/- 12 ms; p < 0.0001) and greater in the HF-wide QRS (p < 0.0001) and HF-narrow QRS (p = 0.005) groups compared with control subjects. We found that DI had a good correlation with 2-dimensional (r = 0.65, p = 0.012) and 3-dimensional (r = 0.68, p = 0.008) echocardiographic dyssynchrony., Conclusions: Quantitative assessment of global CT-derived DI, based on changes in wall thickness over time, is highly reproducible and renders significant differences between subjects most likely to have dyssynchrony and age-matched control subjects.

Background: The sequence of left ventricular (LV) systolic emptying is not completely understood. Using real-time 3-dimensional echocardiography, we investigated this sequence and LV synchronicity in physiological and pathological conditions., Methods and Results: The study population consisted of 116 healthy volunteers, 20 top-level athletes, 35 patients with LV dysfunction, and 84 patients with LV dysfunction and left bundle-branch block (LBBB). We subdivided the LV into 16 volumetric segments for regional analysis and into apical, middle, and basal regions to calculate the mean of end-systolic times and the time to minimum systolic volume of each region. In healthy volunteers and in top-level athletes, the emptying systolic times increased smoothly from apex to base. These differences determined an apex-to-base time gradient in the LV emptying sequence. In patients with LV dysfunction and without LBBB, this gradient was maintained with a relatively higher LV dyssynchrony. However, in patients with LV dysfunction and LBBB, there was no clear sequence in LV emptying volumes, and this group had the highest LV dyssynchrony., Conclusions: Real-time 3-dimensional echocardiography tomographic slicing of the LV enables accurate analysis of LV emptying in physiological conditions and in conditions of LV dysfunction with and without electrical dyssynchrony. Progressive dilation of LV produces deterioration in LV synchronicity. However, it is the presence of LV dysfunction in combination with LBBB that determines the loss of the apex-to-base time gradient in LV emptying.

The changes in breathing pattern and lung mechanics in response to incremental exercise were compared in 14 subjects with chronic heart failure and 15 normal subjects. In chronic heart failure subjects, exercise hyperpnea was achieved by increasing breathing frequency more than tidal volume. The rate of increase in breathing frequency with carbon dioxide output was inversely correlated (r = -0.61, P < 0.05) with dynamic lung compliance measured at rest, but not with static lung compliance either at rest or at maximum exercise. Although decrease in expiratory flow reserve near functional residual capacity in chronic heart failure occurred earlier with exercise than in the normal subjects (P < 0.01), it was not correlated with changes in breathing pattern or occurrence of tachypnea. Tachypnea was achieved in chronic heart failure subjects with an increase in duty cycle because of a greater than normal decrease in expiratory time with exercise. We conclude that in chronic heart failure preexisting increase in lung stiffness plays a significant role in causing tachypnea during exercise. The results of the present study do not support the hypothesis that dynamic compression of the airways downstream from the flow-limiting segment occurring during exercise contributes to hyperpnea.