Machine Learning-Driven Classification of Urease Inhibitors Leveraging Physicochemical Properties as Effective Filter Criteria.

Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic Helicobacter pylori. Inhibiting urease activity offers a promising approach to combating infections and associated ailments, such as chronic kidney diseases and gastric cancer. However, identifying potent urease inhibitors remains challenging due to resistance issues that hinder traditional approaches. Recently, machine learning (ML)-based models have demonstrated the ability to predict the bioactivity of molecules rapidly and effectively. In this study, we present ML models designed to predict urease inhibitors by leveraging essential physicochemical properties. The methodological approach involved constructing a dataset of urease inhibitors through an extensive literature search. Subsequently, these inhibitors were characterized based on physicochemical properties calculations. An exploratory data analysis was then conducted to identify and analyze critical features. Ultimately, 252 classification models were trained, utilizing a combination of seven ML algorithms, three attribute selection methods, and six different strategies for categorizing inhibitory activity. The investigation unveiled discernible trends distinguishing urease inhibitors from non-inhibitors. This differentiation enabled the identification of essential features that are crucial for precise classification. Through a comprehensive comparison of ML algorithms, tree-based methods like random forest, decision tree, and XGBoost exhibited superior performance. Additionally, incorporating the "chemical family type" attribute significantly enhanced model accuracy. Strategies involving a gray-zone categorization demonstrated marked improvements in predictive precision. This research underscores the transformative potential of ML in predicting urease inhibitors. The meticulous methodology outlined herein offers actionable insights for developing robust predictive models within biochemical systems.

The Controlled Release of Abscisic Acid (ABA) Utilizing Alginate-Chitosan Gel Blends: A Synergistic Approach for an Enhanced Small-Molecule Delivery Controller.

The integration of abscisic acid (ABA) into a chitosan-alginate gel blend unveils crucial insights into the formation and stability of these two substances. ABA, a key phytohormone in plant growth and stress responses, is strategically targeted for controlled release within these complexes. This study investigates the design and characterization of this novel controlled-release system, showcasing the potential of alginate-chitosan gel blends in ABA delivery. Computational methods, including molecular dynamics simulations, are employed to analyze the structural effects of microencapsulation, offering valuable insights into complex behavior under varying conditions. This paper focuses on the controlled release of ABA from these complexes, highlighting its strategic importance in drug delivery systems and beyond. This controlled release enables targeted and regulated ABA delivery, with far-reaching implications for pharmaceuticals, agriculture, and plant stress response studies. While acknowledging context dependency, the paper suggests that the liberation or controlled release of ABA holds promise in applications, urging further research and experimentation to validate its utility across diverse fields. Overall, this work significantly contributes to understanding the characteristics and potential applications of chitosan-alginate complexes, marking a noteworthy advancement in the field of controlled-release systems.

Structural and transcriptional characterization of pyruvate decarboxylase (PDC) gene family during strawberry fruit ripening process.

Strawberry is one of the most popular fruits in the world, because their high fruit quality, especially with respect to the combination of aroma, flavor, color, and nutritional compounds. Pyruvate decarboxylase (PDC) is the first of two enzymes specifically required for ethanolic fermentation and catalyzes the decarboxylation of pyruvate to yield acetaldehyde and CO2. The ethanol, an important alcohol which acts as a precursor for the ester and other alcohols formation in strawberry, is produced by the PDC. The objective was found all different PDCs genes present in the strawberry genome and investigate PDC gene expression and ligand-protein interactions in strawberry fruit. Volatile organic compounds were evaluated during the development of the fruit. After this, eight FaPDC were identified with four genes that increase the relative expression during fruit ripening process. Molecular dynamics simulations were performed to analyze the behavior of Pyr and TPP ligands within the catalytic and regulatory sites of the PDC proteins. Results indicated that energy-restrained simulations exhibited minor fluctuations in ligand-protein interactions, while unrestrained simulations revealed crucial insights into ligand affinity. TPP consistently displayed strong interactions with the catalytic site, emphasizing its pivotal role in enzymatic activity. However, FaPDC6 and FaPDC9 exhibited decreased pyruvate affinity initially, suggesting unique binding characteristics requiring further investigation. Finally, the present study contributes significantly to understanding PDC gene expression and the intricate molecular dynamics underlying strawberry fruit ripening, shedding light on potential targets for further research in this critical biological pathway.

Unveiling Novel Urease Inhibitors for Helicobacter pylori: A Multi-Methodological Approach from Virtual Screening and ADME to Molecular Dynamics Simulations.

Helicobacter pylori (Hp) infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key Hp virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for Hp urease (HpU). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel HpU inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.

An intracellular hydrophobic nexus critical for hERG1 channel slow deactivation.

Slow deactivation is a critical property of voltage-gated K+ channels encoded by the human Ether-à-go-go-Related Gene 1 (hERG). hERG1 channel deactivation is modulated by interactions between intracellular N-terminal Per-Arnt-Sim (PAS) and C-terminal cyclic nucleotide-binding homology (CNBh) domains. The PAS domain is multipartite, comprising a globular domain (gPAS; residues 26-135) and an N-terminal PAS-cap that is further subdivided into an initial unstructured "tip" (residues 1-12) and an amphipathic α-helical region (residues 13-25). Although the PAS-cap tip has long been considered the effector of slow deactivation, how its position near the gating machinery is controlled has not been elucidated. Here, we show that a triad of hydrophobic interactions among the gPAS, PAS-cap α helix, and the CNBh domains is required to support slow deactivation in hERG1. The primary sequence of this "hydrophobic nexus" is highly conserved among mammalian ERG channels but shows key differences to fast-deactivating Ether-à-go-go 1 (EAG1) channels. Combining sequence analysis, structure-directed mutagenesis, electrophysiology, and molecular dynamics simulations, we demonstrate that polar serine substitutions uncover an intermediate deactivation mode that is also mimicked by deletion of the PAS-cap α helix. Molecular dynamics simulation analyses of the serine-substituted channels show an increase in distance among the residues of the hydrophobic nexus, a rotation of the intracellular gating ring, and a retraction of the PAS-cap tip from its receptor site near the voltage sensor domain and channel gate. These findings provide compelling evidence that the hydrophobic nexus coordinates the respective components of the intracellular gating ring and positions the PAS-cap tip to control hERG1 deactivation gating.

Fusion Position-Dependent Aromatic Transitions of Ligand Backbone Rings for Controlling the Redox Energetics of Photoredox Catalysts.

To reveal, quantify, and rationalize the effect of backbone π-extension on ligand redox activity, we studied the ground- and excited-state reduction potentials of eight ruthenium photoredox catalysts with the formula Ru(ppy)2L (L is the redox-active ligand of the bipyridine family) using density functional theory. Our research underlines the profound importance of the fusion position of backbone aromatic C6 rings on the redox activity of ligands in transition metal photoredox catalysts. Namely, certain fusion positions lead to the dearomatization of C6 rings in ligand-centered electron transfer events, resulting in a thermodynamic penalty equivalent to a half-volt negative shift in the reduction potential. Contrarily, the extent of backbone delocalization shows a minimal impact on redox energetics, which can be explained by the charge concentration at the nitrogen contact atoms in ligand-centered reductions. Grounded in Caulton's conceptual framework, we reaffirm the predictive potency of Lewis structures in ligand-centered redox energetics with qualitative and quantitative data. Our hypothesis regarding the effect of backbone ring dearomatization on redox energetics is further corroborated using magnetic and structure-based aromaticity indicators. Highlighting fusion-dependent dearomatization as a determining factor of ligand-centered electron transfer energetics, our findings hold implications for molecular-level design in advanced electroactive materials and catalysts.

Development and Evaluation of Cross-Linked Alginate-Chitosan-Abscisic Acid Blend Gel.

Abscisic acid (ABA) has been proposed to play a significant role in the ripening of nonclimacteric fruit, stomatal opening, and response to abiotic stresses in plants, which can adversely affect crop growth and productivity. The biological effects of ABA are dependent on its concentration and signal transduction pathways. However, due to its susceptibility to the environment, it is essential to find a suitable biotechnological approach to coat ABA for its application. One promising approach is to utilize alginate and chitosan, two natural polysaccharides known for their strong affinity for water and their ability to act as coating agents. In this study, an alginate-chitosan blend was employed to develop an ABA cover. To achieve this, an alginate-chitosan-abscisic acid (ALG-CS-ABA) blend was prepared by forming ionic bonds or complexes with calcium ions, or through dual cross-linking. This was done by dripping a homogeneous solution of alginate-chitosan and ABA into a calcium chloride solution, resulting in the formation of the blend. By combining the unique properties of alginate, chitosan, and ABA, the resulting ALG-CS-ABA blend can potentially offer enhanced stability, controlled release, and improved protection of ABA. These characteristics make it a promising biotechnological approach for various applications, including the targeted delivery of ABA in agricultural practices or in the development of innovative plant-based products. Further evaluation and characterization of the ALG-CS-ABA blend will provide valuable insights into its potential applications in the fields of biomedicine, agriculture, and tissue engineering.

Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach.

Pesticides have a significant negative impact on the environment, non-target organisms, and human health. To address these issues, sustainable pest management practices and government regulations are necessary. However, biotechnology can provide additional solutions, such as the use of polyelectrolyte complexes to encapsulate and remove pesticides from water sources. We introduce a computational methodology to evaluate the capture capabilities of Calcium-Alginate-Chitosan (CAC) nanoparticles for a broad range of pesticides. By employing ensemble-docking and molecular dynamics simulations, we investigate the intermolecular interactions and absorption/adsorption characteristics between the CAC nanoparticles and selected pesticides. Our findings reveal that charged pesticide molecules exhibit more than double capture rates compared to neutral counterparts, owing to their stronger affinity for the CAC nanoparticles. Non-covalent interactions, such as van der Waals forces, π-π stacking, and hydrogen bonds, are identified as key factors which stabilized the capture and physisorption of pesticides. Density profile analysis confirms the localization of pesticides adsorbed onto the surface or absorbed into the polymer matrix, depending on their chemical nature. The mobility and diffusion behavior of captured compounds within the nanoparticle matrix is assessed using mean square displacement and diffusion coefficients. Compounds with high capture levels exhibit limited mobility, indicative of effective absorption and adsorption. Intermolecular interaction analysis highlights the significance of hydrogen bonds and electrostatic interactions in the pesticide-polymer association. Notably, two promising candidates, an antibiotic derived from tetracycline and a rodenticide, demonstrate a strong affinity for CAC nanoparticles. This computational methodology offers a reliable and efficient screening approach for identifying effective pesticide capture agents, contributing to the development of eco-friendly strategies for pesticide removal.

Cost-Effective Pipeline for a Rational Design and Selection of Capsaicin Analogues Targeting TRPV1 Channels.

Transient receptor potential (TRP) channels constitute a large group of membrane receptors associated with sensory pathways in vertebrates. One of the most studied is TRPV1, a polymodal receptor tuned for detecting heat and pungent compounds. Specific inhibition of the nociceptive transduction at the peripheral nerve represents a convenient approach to pain relief. While acting as a chemoreceptor, TRPV1 shows high sensitivity and selectivity for capsaicin. In contrast to the drugs available on the market that target the inflammatory system, TRPV1 antagonists act as negative modulators of nociceptive transduction. Therefore, the development of compounds modulating TRPV1 activity has expanded dramatically over time. Experimental data suggest that most agonist and antagonist drugs interact at or near capsaicin's binding site. In particular, the properties of capsaicin's head play an essential role in modulating potency and affinity. Here, we explored a cost-efficient pipeline to predict the effects of introducing chemical modifications into capsaicin's head region. An extensive set of molecules was selected by first considering the geometrical properties of capsaicin's binding site and then molecular docking. Finally, the novel ligands were ranked by combining molecular and pharmacokinetic predictions.

Minimally invasive surgery versus laparotomy in women with high risk endometrial cancer: A multi-center study performed in Argentina.

Objective: Compare the perioperative outcomes and disease-free survival between minimally invasive and open surgery in women with stage I-II high-risk endometrial cancer. Methods: A retrospective, cohort study was performed involving twenty-four centers from Argentina. Patients with grade 3 endometrioid, serous, clear cell, undifferentiated carcinoma or carcinosarcoma who underwent hysterectomy, bilateral salpingo-oophorectomy, and staging between January 2010-2018 were included. Cox hazard regression analysis and Kaplan-Meier curves evaluated the association of surgical technique with survival. Results: Of 343 eligible patients, 214 (62 %) underwent open surgery and 129 (38 %) underwent laparoscopic surgery. No significant differences were seen between the two groups with respect to greater or equal grade III Clavien-Dindo postoperative complications (11 % in the open surgery group vs 9 % minimally invasive surgery group; P = 0.34) Minimally invasive surgery was not associated with worse disease-free survival at four years (79.14 % [95 % CI 69.42- 86.08] vs 78.80 % [95 % CI 70.61-84.96]), (p = 0.25), even after creating a Cox proportional model (hazard ratio [HR] 1.08 95 % CI 0.63-1.84); (p = 0.76). Conclusion: There was no difference between postoperative complications nor oncologic outcomes comparing minimally invasive and open surgery among patients with high-risk endometrial cancer.

Intracellular Helix-Loop-Helix Domain Modulates Inactivation Kinetics of Mammalian TRPV5 and TRPV6 Channels.

TRPV5 and TRPV6 are calcium-selective ion channels expressed at the apical membrane of epithelial cells. Important for systemic calcium (Ca2+) homeostasis, these channels are considered gatekeepers of this cation transcellular transport. Intracellular Ca2+ exerts a negative control over the activity of these channels by promoting inactivation. TRPV5 and TRPV6 inactivation has been divided into fast and slow phases based on their kinetics. While slow inactivation is common to both channels, fast inactivation is characteristic of TRPV6. It has been proposed that the fast phase depends on Ca2+ binding and that the slow phase depends on the binding of the Ca2+/Calmodulin complex to the internal gate of the channels. Here, by means of structural analyses, site-directed mutagenesis, electrophysiology, and molecular dynamic simulations, we identified a specific set of amino acids and interactions that determine the inactivation kinetics of mammalian TRPV5 and TRPV6 channels. We propose that the association between the intracellular helix-loop-helix (HLH) domain and the TRP domain helix (TDh) favors the faster inactivation kinetics observed in mammalian TRPV6 channels.

Rational Design of Hydrogels for Cationic Antimicrobial Peptide Delivery: A Molecular Modeling Approach.

In light of the growing bacterial resistance to antibiotics and in the absence of the development of new antimicrobial agents, numerous antimicrobial delivery systems over the past decades have been developed with the aim to provide new alternatives to the antimicrobial treatment of infections. However, there are few studies that focus on the development of a rational design that is accurate based on a set of theoretical-computational methods that permit the prediction and the understanding of hydrogels regarding their interaction with cationic antimicrobial peptides (cAMPs) as potential sustained and localized delivery nanoplatforms of cAMP. To this aim, we employed docking and Molecular Dynamics simulations (MDs) that allowed us to propose a rational selection of hydrogel candidates based on the propensity to form intermolecular interactions with two types of cAMPs (MP-L and NCP-3a). For the design of the hydrogels, specific building blocks were considered, named monomers (MN), co-monomers (CM), and cross-linkers (CL). These building blocks were ranked by considering the interaction with two peptides (MP-L and NCP-3a) as receptors. The better proposed hydrogel candidates were composed of MN3-CM7-CL1 and MN4-CM5-CL1 termed HG1 and HG2, respectively. The results obtained by MDs show that the biggest differences between the hydrogels are in the CM, where HG2 has two carboxylic acids that allow the forming of greater amounts of hydrogen bonds (HBs) and salt bridges (SBs) with both cAMPs. Therefore, using theoretical-computational methods allowed for the obtaining of the best virtual hydrogel candidates according to affinity with the specific cAMP. In conclusion, this study showed that HG2 is the better candidate for future in vitro or in vivo experiments due to its possible capacity as a depot system and its potential sustained and localized delivery system of cAMP.

A journey from molecule to physiology and in silico tools for drug discovery targeting the transient receptor potential vanilloid type 1 (TRPV1) channel.

The heat and capsaicin receptor TRPV1 channel is widely expressed in nerve terminals of dorsal root ganglia (DRGs) and trigeminal ganglia innervating the body and face, respectively, as well as in other tissues and organs including central nervous system. The TRPV1 channel is a versatile receptor that detects harmful heat, pain, and various internal and external ligands. Hence, it operates as a polymodal sensory channel. Many pathological conditions including neuroinflammation, cancer, psychiatric disorders, and pathological pain, are linked to the abnormal functioning of the TRPV1 in peripheral tissues. Intense biomedical research is underway to discover compounds that can modulate the channel and provide pain relief. The molecular mechanisms underlying temperature sensing remain largely unknown, although they are closely linked to pain transduction. Prolonged exposure to capsaicin generates analgesia, hence numerous capsaicin analogs have been developed to discover efficient analgesics for pain relief. The emergence of in silico tools offered significant techniques for molecular modeling and machine learning algorithms to indentify druggable sites in the channel and for repositioning of current drugs aimed at TRPV1. Here we recapitulate the physiological and pathophysiological functions of the TRPV1 channel, including structural models obtained through cryo-EM, pharmacological compounds tested on TRPV1, and the in silico tools for drug discovery and repositioning.

Role of Liraglutide Use in Patients With Heart Failure.

Heart failure is a clinical condition in which the heart is unable to maintain adequate cardiac output. Liraglutide is a glucagon-like peptide 1 (GLP-1) analogue that is used for the treatment of type 2 diabetes mellitus, but recent evidence suggests that it might have a beneficial role in treating heart failure. We conducted a review of existing literature and found five relevant studies. Data from these studies were extracted and then extrapolated into results following analysis. Four of the five studies found an increase in heart rate in heart failure patients. All five studies reported an increased rate of hospitalization. The five studies also showed an increased risk of adverse effects such as arrhythmia, ventricular tachycardia, atrial fibrillation, and worsening of heart failure. Given the scarcity of evidence in the available literature on liraglutide in heart failure, more research on this population is required.

Selective TASK-1 Inhibitor with a Defined Structure-Activity Relationship Reduces Cancer Cell Proliferation and Viability.

Chemical structures of selective blockers of TASK channels contain aromatic groups and amide bonds. Using this rationale, we designed and synthesized a series of compounds based on 3-benzamidobenzoic acid. These compounds block TASK-1 channels by binding to the central cavity. The most active compound is 3-benzoylamino-N-(2-ethyl-phenyl)-benzamide or F3, blocking TASK-1 with an IC50 of 148 nM, showing a reduced inhibition of TASK-3 channels and not a significant effect on different K+ channels. We identified putative F3-binding sites in the TASK-1 channel by molecular modeling studies. Mutation of seven residues to A (I118A, L122A, F125A, Q126A, L232A, I235A, and L239A) markedly decreased the F3-induced inhibition of TASK-1 channels, consistent with the molecular modeling predictions. F3 blocks cell proliferation and viability in the MCF-7 cancer cell line but not in TASK-1 knockdown MCF-7 cells, indicating that it is acting in TASK-1 channels. These results indicated that TASK-1 is necessary to drive proliferation in the MCF-7 cancer cell line.

Structural Insights into the Inhibition Site in the Phosphorylcholine Phosphatase Enzyme of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a highly pathogenic Gram-negative microorganism associated with high mortality levels in burned or immunosuppressed patients or individuals affected by cystic fibrosis. Studies support a colonization mechanism whereby P. aeruginosa can breakdown the host cell membrane phospholipids through the sequential action of two enzymes: (I) hemolytic phospholipase C acting upon phosphatidylcholine or sphingomyelin to produce phosphorylcholine (Pcho) and (II) phosphorylcholine phosphatase (PchP) that hydrolyzes Pcho to generate choline and inorganic phosphate. This coordinated action provides the bacteria with carbon, nitrogen, and inorganic phosphate to support growth. Furthermore, PchP exhibits a distinctive inhibition mechanism by high substrate concentration. Here, we combine kinetic assays and computational approaches such as molecular docking, molecular dynamics, and free-energy calculations to describe the inhibitory site of PchP, which shares specific residues with the enzyme's active site. Our study provides insights into a coupled inhibition mechanism by the substrate, allowing us to postulate that the integrity of the inhibition site is needed to the correct functioning of the active site. Our results allow us to gain a better understanding of PchP function and provide the basis for a rational drug design that might contribute to the treatment of infections caused by this important opportunistic pathogen.

Use of slow atomization ramp in high resolution continuum source graphite furnace atomic absorption spectrometry for the simultaneous determination of Cd and Ni in slurry powdered chocolate samples.

A methodology for simultaneous (not sequential) determination of Cd and Ni in powder chocolate samples by high-resolution continuum source graphite furnace atomic absorption spectroscopy (HR-CS-GF-AAS) and slurry sample analysis was developed. Acid digestion of the samples was not necessary, considering the high total fat content of this type of matrix (above 10 %), and no apparent deterioration of the graphite tubes was even observed once these samples were subjected to analysis. Despite the volatilities of both elements are quite different, simultaneous quantification was achieved using a slow heating ramp atomization, covering a convenient and wide temperature gradient for Cd volatilization at low temperatures and subsequent atomization of Ni at elevated temperatures, using the same heating program without an apparent change in sensitivity. This slow heating ramp was essayed between 200 and 1500 °C·s-1 and optimized at 400 °C·s-1, achieving the simultaneous measuring of Cd in the principal line (228.8018 nm) and using a secondary for Ni (228.9984 nm). No stop events for sequential changes in wavelength or temperature additional steps were involved in the method and molecular spectral interferences overlapping the analyte signals were corrected appropriately by a pragmatic strategy taking advantage of the fine structure signals adjacent to analyte signals within the same spectrum recorded. Palladium matrix modifier and aqueous standards were used for the calibration and determination of both elements in the samples. The method accuracy was successfully confirmed using a reference material (NIST SRM 1573a). An improvement in the sensitivity of Ni was found using a greater number of pixels for signal integration, central and five adjacent pixels (CP ± 5), while a lengthening of the linear range of Cd was obtained by using an attenuated signal (±2) or using only one pixel (CP). The limits of detection were 0.027 µg g-1 and 0.22 µg g-1 for Cd and Ni respectively by this simple methodology using aqueous standards for calibration and the simultaneous determination of both elements in the same measurement. The respective limits of quantification for Cd and Ni were 0.090 and 0.72 µg g-1 and the relative standard deviations in samples (n = 5) were about 4-20% and 0.3-11% for Cd and Ni respectively. The optimized method was used for the determination of both elements in real samples purchased from retail supermarkets finding variable concentrations between 0.5 and 5.7 µg g-1 for Cd and 2.1-10.9 µg g-1 for Ni, comparable to levels reported in the literature referred to elsewhere in the world.

Structural Effects of pH Variation and Calcium Amount on the Microencapsulation of Glutathione in Alginate Polymers.

Reduced glutathione (GSH) has a high antioxidant capacity and is present in nearly every cell in the body, playing important roles in nutrient metabolism, antioxidant defense, and regulation of cellular events. Conversely, alginate is a macromolecule that has been widely used in the food, pharmaceutical, biomedical, and textile industries due to its biocompatibility, biodegradability, nontoxicity, and nonimmunogenicity as well as for its capabilities of retaining water and stabilizing emulsions. The primary goal of this study was to characterize and optimize the formation of a molecular complex of calcium alginate with GSH using a computational approach. As methods, we evaluated the influence of varying the amount of calcium cations at two different pHs on the structural stability of Ca2+-alginate complexes and thus on GSH liberation from these types of nanostructures. The results showed that complex stabilization depends on pH, with the system having a lower Ca2+ amount that produces the major GSH release. The systems at pH 2.5 retain more molecules within the calcium-alginate complex, which release GSH more slowly when embedded in more acidic media. In conclusions, this study demonstrates the dependence of the amount of calcium and the stabilizing effect of pH on the formation and subsequent maintenance of an alginate nanostructure. The results presented in this study can help to develop better methodological frameworks in industries where the release or capture of compounds, such as GSH in this case, depends on the conditions of the alginate nanoparticle.

A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs.

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.

Use of Poly(vinyl alcohol)-Malic Acid (CLHPMA) Hydrogels and Chitosan Coated Calcium Alginate (CCCA) Microparticles as Potential Sorbent Phases for the Extraction and Quantitative Determination of Pesticides from Aqueous Solutions.

Pesticides are used worldwide to increase crop yields in agriculture. However, their toxicity and accumulation capacity can make them toxic to the environment, animals and humans. In the case of workers chronically exposed to these substances, they must be sampled continuously, so urine is an excellent option. In this sense, this study proposes to use poly(vinyl alcohol)-malic acid hydrogels, and chitosan-coated calcium alginate as new sorbent phases to be used in pesticide determination processes in urine. To better understand the behavior of these materials in the capture and desorption process, molecular dynamics simulations (MDS) were used, and desorption experiments were performed, using mechanical agitation, ultrasound, and pH variation in the desorption process, in order to optimize the parameters to obtain better recoveries. Under the optimal experimental conditions, the maximum recoveries were of the order of 11% (CFN), 3% (KCF), 53% (DMT), 18% (MTD) and 35% (MTL). Although the recoveries were not exhaustive, they are a first approximation for the use of these new sorbent phases in the determination of this type of compound in aqueous solutions and urine.