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Background Hydatidosis of the thoracic wall differs from other hydatid localizations in its pathophysiology, diagnostic, and therapeutic management. It is a little-studied entity. The objectives of our work were to describe its surgical management and to analyze the factors that may influence recurrence and mortality. Methods A retrospective, descriptive, longitudinal, and multicenter study on four university hospital surgical centers of Tunis, from January 1995 to December 2022 including operated hydatid cysts of the thoracic wall. Overall survival (OS) and cumulative recurrence rates were calculated. Univariate and multivariable Cox regression analyses were performed to identify recurrence and mortality risk factors. Results Forty-nine patients were included. The mean age was 41 ± 17 years [8-76]. The main presenting sign was thoracic parietal swelling (n=22). Chest ultrasound and CT scan showed multivesicular formation in 17 and 33 cases, respectively. Muscle involvement was in the intercostal (n=4), paravertebral (n=13), and pectoralis major (n=3) muscles. Bone involvement was vertebral (n=11), costal (n=12), costo-vertebral (n=21) and sternal (n=2). A posterolateral thoracotomy was performed (n=20). Surgical excision at various levels of the chest wall with spinal stabilization (n=15) was performed. Sixty-three percent of the patients received antiparasitic medical treatment. Recurrence occurred in 37% of cases. Four patients died from hydatidosis-related complications. Factors could be independently associated with recurrence such as male gender, and vertebral involvement. The presence of a visceral hydatid cyst located at a distance from the parietal lesion at the time of diagnosis and the occurrence of postoperative infectious complications could increase mortality. Conclusions Chest wall hydatidosis represents a rare medical condition where surgery remains the preferred treatment modality. However, it carries a substantial burden of morbidity and mortality, influenced by various factors. Further large-scale studies are necessary to gain a deeper understanding of these factors and to optimize management strategies accordingly.

Lithium-ion batteries (LIBs) play a vital role in advancing the hybrid industry, especially in electric vehicles, as clean and sustainable electrochemical energy sources. However, the prevalent use of organic solvents in the liquid electrolytes of these energy storage systems raises environmental concerns. In this study, we investigated the impact of a polar aprotic solvent, ethylene carbonate (EC), on the structural, dynamic and dielectric properties of the LiF electrolyte using molecular dynamics simulations. By employing the CHARMM 36 force field, our goal was to comprehend the various physicochemical phenomena occurring in this electrolytic system across different temperatures within the saturation region. The structural properties were analyzed through the computation of the radial distribution function (RDF) for various pairs, while the dynamic and dielectric behaviors were elucidated by simulating the self-diffusion coefficient (D) and the dielectric constant (ε).

Potassium-ion-based batteries have emerged as promising alternatives to traditional lithium-ion batteries for energy storage systems due to their affordability, wide accessibility and comparable chemical characteristics to lithium. This study employs molecular dynamics simulations to explore the physical phenomena of potassium fluoride in aqueous solutions. The interatomic interactions were defined using the OPLS-AA force field, while the SPC/E water model and ions were represented as charged Lennard–Jones particles. The simulations were conducted across concentrations ranging from 0.1 to 1.0 mol kg-1. The insights derived from this investigation provide valuable understanding into the behaviour of KF electrolytes and their potential utility in energy storage systems. A comprehensive comprehension of the impact of KF electrolyte concentration on structural, dynamic and dielectric properties is pivotal for the design and optimization of potassium-ion batteries, as well as other electrochemical devices leveraging KF-based electrolytes. This research significantly contributes to the ongoing endeavours aimed at developing efficient and economically viable energy storage solutions that transcend the confines of traditional lithium-ion batteries.

Background: Angiogenesis is a crucial process in the growth and proliferation of cancer, enabling tumor growth through the formation of new vasculature and the supply of nutrients and oxygen to growing malignant cells. This disease-promoting process can be targeted through the inhibition of tyrosine kinase enzymes. Objectives: The objective of this study is to evaluate the anticancer potential of various Moroccan plants from different regions. While these plants have a rich history of traditional medicinal use, they have not been extensively investigated as anticancer therapies. Methods: This study employed a multifaceted approach to evaluate the anticancer potential of various Moroccan plants. Receptor–ligand docking and virtual screening were used to assess the binding affinity of phytocompounds to the EGFR and VEGFR2 receptors. Additionally, predictive pharmacokinetic analyses were conducted to evaluate the ADMET properties of the selected compounds, followed by molecular dynamics simulations to analyze the stability of the receptor–ligand complexes. Results: In our research, we identified three notable active compounds—catechin, 4-O-glucoside ferulic acid, and 3-glucoside resveratrol—in the Moroccan plant Ajuga iva L. These findings suggest that Ajuga iva L. may possess significant potential for cancer inhibition. Conclusions: This research highlights the potential of the Moroccan plant Ajuga iva L. as a source of active compounds with significant anticancer properties. Further investigation is essential to validate these findings and explore new therapeutic avenues based on these traditional resources.

Sodium fluoride has many applications in various fields, such as dentistry, geochemistry, and rechargeable battery technology. Indeed, the determination of the hydration structures, dynamics, and dielectric properties of the NaF electrolyte in aqueous solutions is a crucial element in order to optimize its performance and predict its intervention mechanisms in industrial processes. In this study, we used the molecular dynamics approach to study the NaF(aq) binary system at different concentrations ranging from 0.1 to 1.0 mol.kg−1 using the OPLS-AA force field combined with the extended simple point load water model (SPC/E). Thus, the ions were represented as charged Lennard-Jones particles. The radial distribution functions (RDF) have been calculated to analyze the hydration shell structures of different ion pairs. The microstructures, self-diffusion coefficient, and dielectric constant were determined by molecular dynamics at various concentrations. Moreover, our FTIR spectroscopy data confirm the results obtained from molecular simulations.

In this work, the effect of a new quinoxaline derivative, 2-phenyl-3-(prop-2-yn-1-yloxy) quinoxaline (PYQX), was evaluated as a corrosion inhibitor for carbon steel (CS) in 1 M HCl electrolyte. Weight loss measurement, atomic absorption spectroscopy, potentio­dynamic polarization, electrochemical impedance spectroscopy, scanning electron microscopy with energy dispersive spectroscopy, and UV-vis spectroscopy were employed to assess the inhibitory activity. The electronic properties of the interaction between the inhibitor molecule and the CS substrate were studied using molecular dynamics (MD) simulation, density functional theory (DFT), and Fukui functions. According to AC impedance experiments, the inhibitor under consideration showed a maximum level of 98.1 % inhibition efficiency at 1 mM and 30 °C. The Langmuir adsorption isotherm model explains the adsorption of PYQX on the CS surface. A slope of 1 denotes a strong molecule-substrate interaction, suggesting that the binding occurs at specific surface locations. To understand the functioning of the adsorption mechanism, various thermodynamic and activation parameters were evaluated. PDP tests demonstrated that PYQX functions as a mixed-type inhibitor. Computational correlations (DFT, MD, and Fukui indices) supported the experimental findings.

The novelty of the work is to scrutinize for the first time the 4R,5S- 2,4,5-tris(4-ethoxy­phenyl)-4,5-dihydro-1H-imidazole (TEPI) as a corrosion inhibitor for carbon steel (C35E) in the acidic medium. The inhibitory properties of TEPI were assessed through various methods, including electrochemical, spectroscopic, and surface analysis, as well as quantum chemical calculations. The protective effect of C35E was seen to expand as the TEPI amount was extended but to diminish as temperature was augmented, fulfilling 98.3 % at 1 mM under 303 K. Certain thermodynamic and kinetic indices were estimated and explored. The TEPI complied with the Langmuir adsorption isotherm when it adsorbs on the C35E surface. TEPI behaviour was revealed by polarization trials to be of mixed type. The establishment of an adsorption-linked preventive TEPI layer on the C35E surface has been disclosed thanks to surface analysis. The outcomes of scanning electron microscopy coupled with energy dispersive X-ray spectroscopy clearly illustrate that TEPI can effi­ci­ently adsorb at the C35E interface, substantially reducing C35E steel corrosion. UV-visible analysis of the inhibited electrolyte clearly reveals the complexation of iron cations with TEPI molecules. The density functional theory, Monte Carlo and molecular dynamic simulation were adopted to check out the adsorption characteristics of the TEPI onto C35E surface. The laboratory outcomes have been proven by DFT and MDS.

Conservation agriculture (CA), which could contribute to sustainable agriculture, maintains or improves soil nitrogen fertility by eliminating tillage (no-tillage). Quantitative assessment of soil constituents is enhanced by stable isotope techniques such as 15N, which are used to better understand nitrogen dynamics. This study was therefore carried out to assess the impact of tillage type and fertilizer application on soil and plant nitrogen fractionation. The trial consisted of two tillage types: no-tillage (NT) and conventional tillage (CT). Three nitrogen doses (82, 115, and 149 kg ha−1) were applied. The experimental design was a randomized complete block with three replications. The Louiza variety of durum wheat was used in this study. Soil nitrogen sequestration was assessed using the stable nitrogen isotope (15N) method. The statistical analysis (ANOVA) showed that, overall, there was no significant difference between tillage types and nitrogen doses for grain and straw yields and grain total nitrogen. In contrast, the effect of both factors and their interaction were significant for straw total nitrogen. There was no difference between tillage types for grain nitrogen use efficiency (NUE), even though NT was superior to CT by 3.5%, but nitrogen doses had a significant effect and a significant interaction with tillage type. When comparing nitrogen doses for each tillage type separately, results showed that the average NUE for grain was 20.5, 8.4, and 16.5%, respectively, for the three nitrogen doses for CT compared with 26.8, 19.0, and 30.6% for NT, indicating clearly the better performance of NT compared to CT. Regarding straw, the NUE is 3.2, 3.5, and 5.4% for CT compared with 3.4, 4.9, and 9.2% for NT. NUE in grain and straw under no-tillage was higher than under conventional tillage in all three nitrogen doses. These results show that soil conservation techniques such as no-tillage and the integrated application of nitrogen fertilizer can be good strategies for reducing soil nitrogen losses.

Candida albicans and Aspergillus fumigatus are recognized as significant fungal pathogens, responsible for various human infections. The rapid emergence of drug-resistant strains among these fungi requires the identification and development of innovative antifungal therapies. We undertook a comprehensive screening of 297 naturally occurring compounds to address this challenge. Using computational docking techniques, we systematically analyzed the binding affinity of each compound to key proteins from Candida albicans (PDB ID: 1EAG) and Aspergillus fumigatus (PDB ID: 3DJE). This rigorous in silico examination aimed to unveil compounds that could potentially inhibit the activity of these fungal infections. This was followed by an ADMET analysis of the top-ranked compound, providing valuable insights into the pharmacokinetic properties and potential toxicological profiles. To further validate our findings, the molecular reactivity and stability were computed using the DFT calculation and molecular dynamics simulation, providing a deeper understanding of the stability and behavior of the top-ranking compounds in a biological environment. The outcomes of our study identified a subset of natural compounds that, based on our analysis, demonstrate notable potential as antifungal candidates. With further experimental validation, these compounds could pave the way for new therapeutic strategies against drug-resistant fungal pathogens.

Lippia Alba, a plant commonly utilized in traditional folk medicine, particularly in Brazil, is renowned for its essential oil possessing anti-inflammatory, antibacterial, anesthetic, and antiviral properties. In this study, we conducted molecular analysis, density function calculations, and molecular dynamics simulations to evaluate 13 novel anticoagulant compounds derived from the chemical composition of Lippia Alba, with potential anti-SARS-CoV-2 activity. Our investigation focused on the SARS-CoV-2-associated protein, PDB ID: 6Y2G. Comparative analysis with the reference drug Calpain Inhibitor II revealed that all compounds exhibited a high binding affinity to the SARS-CoV-2 Mpro protein, ranging from -7,5 to -9,9 kcal/mol. Among them, three compounds (C10, C12, and C13) demonstrated favorable pharmacokinetic properties, complying with Lipinski's rule of five. Additionally, Density Functional Theory (DFT) calculations were performed to determine quantum parameters, and a 100 ns molecular dynamics simulation provided insights into the binding stability of the promising compounds within the target protein pocket. Based on our findings, compound 10 shows potential as an effective drug molecule for inhibiting SARS-CoV-2.

BackgroundThe increasing prevalence of diabetes and the side effects associated with current medications necessitate the development of novel candidate drugs targeting alpha-glucosidase as a potential treatment option.MethodsThis study employed computer-aided drug design techniques to identify potential alpha-glucosidase inhibitors from the PubChem database. Molecular docking was used to evaluate 81,197 compounds, narrowing the set for further analysis and providing insights into ligand-target interactions. An ADMET study assessed the pharmacokinetic properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity. Molecular dynamics simulations validated the docking results.Results9 compounds were identified as potential candidate drugs based on their ability to form stable complexes with alpha-glucosidase and their favorable pharmacokinetic profiles, three of these compounds were subjected to the molecular dynamics, which showed stability throughout the entire 100 ns simulation.ConclusionThese findings suggest promising new alpha-glucosidase inhibitors for diabetes treatment. Further validation through in vitro and in vivo studies is recommended to confirm their efficacy and safety.

Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer’s disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model’s robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer’s activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (−12.6 kcal/mol), (−13 kcal/mol), and (−12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (−10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.

A series of 32 molecules derived from 7-prenyloxy-2,3-dihydroflavanone and 5‑hydroxy-7-prenyloxy-2,3-dihydro-flavanone possessing an inhibitory activity against the Acetylcholinesterase (AChE) enzyme were studied using the structure-activity (QSAR) investigations. Electronic descriptors of studied molecules were calculated using Gaussian software using DFT method at the B3YP/6–31G(d, p) level. In addition, constitutional, physicochemical, and topological descriptors were calculated using Chem3D software.The best model obtained by the multiple linear regression (MLR) method was subjected to external and internal statistical validations. What is more, the applicability domain (ad) has been defined for the built model using Williams plot. We have designed new molecular structures similar to the basis of giving of the studied dataset and their activity is predicted by the built model. Then, the molecular docking was used to predict the affinity between the newly inhibitors candidates and the AChE protein. This study was completed by the molecular dynamic simulation (MDs) to predict the stability of the formed complexes, the RMSD and RMSF plots of studied complexes were analyzed.

This study assessed the efficiency of a new in vitro tick feeding system for the adult Rhipicephalus appendiculatus tick and compared the impact of different blood anticoagulating factors on their feeding process. A total of 10 feeders were each seeded with 30 or 60 R. appendiculatus adults. Bovine blood was added into each unit and changed every 12 h for 4 to 10 days during which tick attachment and engorgement was assessed. The tick attachment observed 4 days after feeding was 80.0% (48/60), 75.8% (182/240), and 70.8% (170/240) for lithium heparin, citrate phosphate dextrose, and defibrinated blood, respectively, with no significant difference (p > 0.05) between the anticoagulants used. However, the ticks fed on heparinized and defibrinated blood reached repletion status. The in vitro tick feeding system was successfully used to feed adult R. appendiculatus ticks until repletion. This system could be used to facilitate studies on tick-pathogen interactions, such as those involved in the East Coast fever disease.

Diabetes Mellitus is one of the deadliest diseases in the world, while the current medications against this disease like acarbose represent many side effects such as diarrhea and abdominal discomfort. Many studies based on natural plants used in traditional medicine were performed to find or invent new drugs to treat diabetes mellitus disease. The traditional drug design based on the synthesis and analysis of compounds wanted to study expenses a lot of time and the cost of the synthesis process, while we can resolve these problems by using computational methods that help us to predict the efficacity, stability, and pharmacokinetics properties as a main step in the drugs design chain. In this study, the virtual screening was performed on a set of 49 compounds extracted from cannabis plants by using molecular docking simulation to examine their ability to create a stable complex with the alpha-amylase inhibitor which reduces blood glucose levels in the human body. Acarbose, a widely used anti-alpha amylase activity, was employed as a reference medicine. Further, the selected compounds which showed good binding affinity were subjected to the ADMET screening to predict the pharmacokinetics properties, Additionally, molecular dynamics testing was done to confirm the outcomes. The result was that 50 compounds docked in the binding site of the alpha-amylase protein, and 25 of those compounds demonstrated the ability to create a stable complex with the target. While the ADMET analysis indicated that two substances amongst would have favorable oral bioavailability and pharmacokinetics characteristics.

Originating in Wuhan, the COVID-19 pandemic wave has had a profound impact on the global healthcare system. In this study, we used a 2D QSAR technique, ADMET analysis, molecular docking, and dynamic simulations to sort and evaluate the performance of thirty-nine bioactive analogues of 9,10-dihydrophenanthrene. The primary goal of the study is to use computational approaches to create a greater variety of structural references for the creation of more potent SARS-CoV-2 3Clpro inhibitors. This strategy is to speed up the process of finding active chemicals. Molecular descriptors were calculated using ‘PaDEL’ and ‘ChemDes’ software, and then redundant and non-significant descriptors were eliminated by a module in ‘QSARINS ver. 2.2.2’. Subsequently, two statistically robust QSAR models were developed by applying multiple linear regression (MLR) methods. The correlation coefficients obtained by the two models are 0.89 and 0.82, respectively. These models were then subjected to internal and external validation tests, Y-randomization, and applicability domain analysis. The best model developed is applied to designate new molecules with good inhibitory activity values against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). We also examined various pharmacokinetic properties using ADMET analysis. Then, through molecular docking simulations, we used the crystal structure of the main protease of SARS-CoV-2 (3CLpro/Mpro) in a complex with the covalent inhibitor ''Narlaprevir'' (PDB ID: 7JYC). We also supported our molecular docking predictions with an extended molecular dynamics simulation of a docked ligand-protein complex. We hope that the results obtained in this study can be used as good anti-SARS-CoV-2 inhibitors.

In response to the increasing prevalence of diabetes mellitus and the limitations associated with the current treatments, there is a growing need to develop novel medications for this disease. This study is focused on creating new compounds that exhibit a strong inhibition of alpha-glucosidase, which is a pivotal enzyme in diabetes control. A set of 33 triazole derivatives underwent an extensive QSAR analysis, aiming to identify the key factors influencing their inhibitory activity against α-glucosidase. Using the multiple linear regression (MLR) model, seven promising compounds were designed as potential drugs. Molecular docking and dynamics simulations were employed to shed light on the mode of interaction between the ligands and the target, and the stability of the obtained complexes. Furthermore, the pharmacokinetic properties of the designed compounds were assessed to predict their behavior in the human body. The binding free energy was also calculated using MMGBSA method and revealed favorable thermodynamic properties. The results highlighted three novel compounds with high biological activity, strong binding affinity to the target enzyme, and suitability for oral administration. These results offer interesting prospects for the development of effective and well-tolerated medications against diabetes mellitus.

The lack of treatments and vaccines effective against SARS-CoV-2 has forced us to explore natural compounds that could potentially inhibit this virus. Additionally, Morocco is renowned for its rich plant diversity and traditional medicinal uses, which inspires us to leverage our cultural heritage and the abundance of natural resources in our country for therapeutic purposes. In this study, an extensive investigation was conducted to gather a collection of phytoconstituents extracted from Moroccan plants, aiming to evaluate their ability to inhibit the proliferation of the SARS-CoV-2 virus. Molecular docking of the studied compounds was performed at the active sites of the main protease (6lu7) and spike (6m0j) proteins to assess their binding affinity to these target proteins. Compounds exhibiting high affinity to the proteins underwent further evaluation based on Lipinski's rule and ADME-Tox analysis to gain insights into their oral bioavailability and safety. The results revealed that the two compounds demonstrated strong binding affinity to the target proteins, making them potential candidates for oral antiviral drugs against SARS-CoV-2. The molecular dynamics results from this computational analysis supported the overall stability of the resulting complex. [ABSTRACT FROM AUTHOR]

Background: Angiogenesis is a crucial process in the growth and proliferation of cancer, enabling tumor growth through the formation of new vasculature and the supply of nutrients and oxygen to growing malignant cells. This disease-promoting process can be targeted through the inhibition of tyrosine kinase enzymes. Objectives: The objective of this study is to evaluate the anticancer potential of various Moroccan plants from different regions. While these plants have a rich history of traditional medicinal use, they have not been extensively investigated as anticancer therapies. Methods: This study employed a multifaceted approach to evaluate the anticancer potential of various Moroccan plants. Receptor–ligand docking and virtual screening were used to assess the binding affinity of phytocompounds to the EGFR and VEGFR2 receptors. Additionally, predictive pharmacokinetic analyses were conducted to evaluate the ADMET properties of the selected compounds, followed by molecular dynamics simulations to analyze the stability of the receptor–ligand complexes. Results: In our research, we identified three notable active compounds—catechin, 4-O-glucoside ferulic acid, and 3-glucoside resveratrol—in the Moroccan plant Ajuga iva L. These findings suggest that Ajuga iva L. may possess significant potential for cancer inhibition. Conclusions: This research highlights the potential of the Moroccan plant Ajuga iva L. as a source of active compounds with significant anticancer properties. Further investigation is essential to validate these findings and explore new therapeutic avenues based on these traditional resources. [ABSTRACT FROM AUTHOR]

Let Γ be a torsionless grading monoid and R = ⊕ α ∈ Γ R α be a Γ -graded integral domain. In this paper, we present basic properties and give a complete characterization of strongly homogeneous prime ideals of R. These works generalize Ahmed and the authors' characterization of when R is a graded pseudo-valuation domain. [ABSTRACT FROM AUTHOR]