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This work wants to investigate the potential of Cu-Si52, Cu-C52, Cu-Al26N26, Cu-doped nanotubes (6, 0) to adsorb and deliver the Favipiravir as COVID-19 drug by DSD-PBEPBE-D3/aug-cc-pVDZ method. This work aims to propose the suitable materials for drug delivery of Favipiravir as COVID-19 drug. Results indicated that the Cu adoption can be increased the stability of Si52, C52, Al26N26, SiNT (6, 0), CNT (6, 0) and AlNNT (6, 0), significantly. The ΔGadsorption of complexes of Favipiravir with Cu-Si52, Cu-C52, Cu-Al26N26, Cu-doped nanotubes (6, 0) are -3.14, -3.25, -3.40, -3.89, -4.03 and -4.13 eV, respectively. The recovery time (τ) values of complexes of Favipiravir with Cu-Si52, Cu-C52, Cu-Al26N26, Cu-doped nanotubes (6, 0) in gas phase are 50.0, 51.8, 55.0, 56.3, 58.3 and 63.0 s. The Cu-AlNNT (6, 0) and Cu-Al26N26 have higher recovery time (τ) than Cu-Si52, Cu-C52, Cu-doped nanotubes (6, 0). Results shown that the Cu-Si52, Cu-C52, Cu-Al26N26, Cu-doped nanotubes (6, 0) have higher capacitates and abilities to deliver and transfer of the Favipiravir than other nanostructures in previous works. Finally, the Cu-AlNNT (6, 0) and Cu-CNT (6, 0) are proposed as acceptable structures to deliver and transfer of Favipiravir as drug of Coronavirus disease. [ABSTRACT FROM AUTHOR]

Here, the capacities of S-C48, S-C-nanotube, S-B24N24 and S-BN-nanotube in Mg-ion and Na-ion batteries are investigated. The Ecohesive of Si48, C48, S-C48, B24N24, S-B24N24, CNT(7, 0), S-CNT(7, 0), BNNT(7, 0) and S-BNNT(7, 0) are -5.86, -5.98, -6.24, -6.35, -6.47, -6.60, -6.88 and -7.01 eV in gas phase. The electrochemical parameters of Si48, C48, C-nanotube, B24N24, BN-nanotube, S-C48, S-C-nanotube, S-B24N24 and S-BN-nanotube in batteries are calculated. The Vcell and Ctheory of Si48, C48, CNT, B24N24, BNNT, S-C48, S-CNT, S-B24N24 and S-BNNT in Mg-ion batteries are higher than Na-ion batteries. Results demonstrated that the Vcell and Ctheory of C48, S-C48, B24N24, S-B24N24, CNT(7, 0), S-CNT(7, 0), BNNT(7, 0) and S-BNNT(7, 0) in batteries are higher than corresponding values of Si-nanotubes, C-nanocages and Si-nanocages, C-nanotubes, C-nanocages and BN-nanocages and BN-nanotubes. Results indicated that the S-C48, S-B24N24, S-CNT(7, 0) and S-BNNT(7, 0) have acceptable capacities in metal-ion batteries. Finally, the S-Si48, S-BNNT(7, 0) and S-CNT(7, 0) are proposed to utilize in batteries. [ABSTRACT FROM AUTHOR]

This study explores the critical role of inhibitors targeting the mammalian target of rapamycin (mTOR) signaling pathway in breast cancer research and treatment. The mTOR pathway, a central regulator of cellular processes, has been identified as a crucial factor in the development and progression of breast cancer. The essay explains the complex molecular mechanisms through which mTOR inhibitors, such as rapamycin and its analogs, exert their anticancer effects. These inhibitors can stop cell growth, proliferation, and survival in breast cancer cells by blocking critical signaling pathways within the mTOR pathway. Furthermore, the essay discusses the implications of using mTOR inhibitors as a comprehensive therapeutic strategy. It emphasizes the potential benefits of combining mTOR inhibitors with other treatment approaches to enhance the effectiveness of breast cancer treatment. The evolving landscape of breast cancer research underscores the significance of mTOR as a therapeutic target and highlights ongoing efforts to improve and optimize mTOR inhibitors for clinical use. In conclusion, the essay asserts that inhibitors of the mTOR signaling pathway offer a promising approach in the fight against breast cancer. These inhibitors provide a focused and effective intervention targeting specific dysregulations within the mTOR pathway. As research advances, the integration of mTOR inhibitors into customized combination therapies holds excellent potential for shaping a more effective and personalized approach to breast cancer treatment, ultimately leading to improved outcomes for individuals affected by this complex and diverse disease. [ABSTRACT FROM AUTHOR]

The most widely used equation to calculate water saturation or suitable shaly water saturation in clean or shaly formation, respectively, is the modified Archie formula. The quality of Archie parameters including saturation exponent affects the preciseness of water saturation, and thus estimated oil and gas in place. Therefore, estimating the saturation exponent by the soft computation methods deems to be necessary. In this study, intelligent models such as multilayer perceptron neural network, least squares support vector machine, radial basis function neural network, and adaptive neuro-fuzzy inference system are developed to predict saturation exponent in terms of petrophysical data including porosity, absolute permeability, water saturation, true resistivity, and resistivity index by utilizing a databank for middle east oil and gas reservoirs. The introduced models are optimized using particle swarm optimization, genetic algorithm, and levenberg marquardt techniques. Graphical and statistical methods are used to demonstrate the capability of the constructed models. Based on the statistical indexes obtained for each model, it is found that radial basis function neural network, multilayer perceptron neural network, and least squares support vector machine are the most robust models as they possess the smallest mean squared error, root mean squared error and average absolute relative error as well as highest coefficient of determination. Moreover, the sensitivity analysis indicates that water saturation has the most effect and porosity has the least effect on the saturation exponent. The developed models are simple-to-use and time-consuming tools to predict saturation exponent without needing laboratory methods which are tedious and arduous. [ABSTRACT FROM AUTHOR]

In this research, a novel core-shell nanocatalyst with silica bi-shell around Fe3O4 and nickel active center, i.e. Fe3O4@xSiO2@ySiO2@BisPyP-Ni was synthesized and its characteristics were comprehensively discussed. This nanocatalyst was successfully used to synthesize biaryls (18 examples, 15–30 min, 92–98%) and diaryl sulfides (10 examples, 20–140 min, 79–98%) at 80 °C. Excellent performance in speeding up the reaction time, magnetic nature, high porosity, and immobilization of two layers around Fe3O4 are four prominent characteristics of this catalyst. Coating the magnetic core with silica layers led to saving the consumption of the catalyst because this trick leads to the bonding of more organic groups to the substrate, as a result, more nickel enters the mesoporous cavities, and the reaction with a smaller amount of catalyst is finished (in a shorter time). Other advantages of both our production lines are: the ability to recover and reuse the catalyst for up to 8 runs (without a noticeable decrease in its catalytic performance), extensive substrate scope, the employ of commercially accessible materials, simple workup, environmental safety and the heterogeneous nature of the catalyst (by confirming the reusability and hot filtration test results). [ABSTRACT FROM AUTHOR]

Cancer stem cells (CSCs) are associated with the tumor microenvironment (TME). CSCs induce tumorigenesis, tumor recurrence and progression, and resistance to standard therapies. Indeed, CSCs pose an increasing challenge to current cancer therapy due to their stemness or self‐renewal properties. The molecular and cellular interactions between heterogeneous CSCs and surrounding TME components and tumor‐supporting immune cells show synergistic effects toward treatment failure. In the immunosuppressive TME, CSCs express various immunoregulatory proteins, growth factors, metabolites and cytokines, and also produce exosomes, a type of extracellular vesicles, to protect themselves from host immune surveillance. Among these, the identification and application of CSC‐derived exosomes could be considered for the development of therapeutic approaches to eliminate CSCs or cancer, in addition to targeting the modulators that remodel the composition of the TME, as reviewed in this study. Here, we introduce the role of CSCs and how their interaction with TME complicates immunotherapies, and then present the CSC‐based immunotherapy and the limitation of these therapies. We describe the biology and role of tumor/CSC‐derived exosomes that induce immune suppression in the TME, and finally, introduce their potentials for the development of CSC‐based targeted immunotherapy in the future. Highlights: Immunotherapies targeting cancer stem cells (CSCs) require reprogramming of tumor microenvironment to recruit immune cells.Targeting CSCs with novel immunogens may improve treatment of resistant tumors.Targeted exosomes in combination with immunotherapies may improve cancer treatment. [ABSTRACT FROM AUTHOR]

In this work, the catalytic activity of Co-Si48, Co-Si60, Co-SiNT (5, 0), Co-SiNT (6, 0), Fe-Si48, Fe-Si60, Fe-SiNT (5, 0), Fe-SiNT (6, 0) as catalysts of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are examined. The Fe doped Si-nanotubes and Si-nanocages have more negative the formation energy and adoption energy values than Co doped Si-nanotubes and Si-nanocages. Results indicated that the reactions step of OOH* creation for OER and OH* elimination for ORR are the potential-determining steps. The *O has the most negative adsorption energy than *OH, *OOH, *H, O2 and H2O species. The H2O is desorbed on Si-nanostructures with low adsorption energy. The Gibbs free energy values of reaction step 1 and step 2 (OH− + Si-nanostructure → Si-nanostructure-*OH + e− → Si-nanostructure -*O + H2O + e−) on Co and Fe doped Si-nanostructures are negative values. The overpotential of ORR processes on Co-Si48, Co-Si60, Co-SiNT (5, 0), Co-SiNT (6, 0), Fe-Si48, Fe-Si60, Fe-SiNT (5, 0), Fe-SiNT (6, 0) in water are 1.24, 1.20, 1.15, 1.11, 1.07, 1.04, 1.00 and 0.97 eV. The metal doped Si-nanotubes and Si-nanocages have acceptable potential to catalyze the OER and ORR reactions. [ABSTRACT FROM AUTHOR]

This article analyzes the forced and free vibrations of bi-directional functionally graded (BDFG) porous nanobeams under moving loads by considering the thickness effect based on the nonlocal strain gradient theory (NSGT). It is assumed that the material properties of the system are graded across the transverse and axial directions according to power and exponential laws, respectively. Various porosity models, including even, uneven, and asymmetric porosity distribution patterns, are considered to model the porosity effects. The dynamic equation of the system is derived by implementing the physical neutral surface concept. Analytical and numerical approaches are adopted to acquire the vibration response of the system. Mathematical closed-form expressions are provided for various dynamic phenomena, such as two types of cancelation, two types of resonance, maximum resonance, cancelation disappearance, and resonance disappearance. In addition, for the first time in this article, it is demonstrated that BDFG porous nanobeams under moving loads are prone to experience the double cancelation phenomenon. Several comparison studies with published data are conducted to validate the results. Also, comprehensive parametric studies are carried out to elucidate the impacts of system parameters such as thickness power index, axial gradient parameter, scale parameter ratio, axial force, porosity coefficient, and porosity distribution pattern on the dynamic magnification factor, critical load speed, and maximum free-response. The outcomes established that by considering the thickness effect, the stiffening behavior of the system is amplified depending on the slenderness ratio. Also, it is concluded that, among the considered porous models, the critical load speed for the system with an even porosity distribution is more dependent on the thickness power index. [ABSTRACT FROM AUTHOR]

AbstractThe selective and sensitive diagnosis of diseases is a significant matter in the early stages of the cure of illnesses. To elaborate, although several types of probes have been broadly applied in clinics, magnetic nanomaterials-aptamers, as new-generation probes, are becoming more and more attractive. The presence of magnetic nanomaterials brings about quantification, purification, and quantitative analysis of biomedical, especially in complex samples. Elaborately, the superparamagnetic properties and numerous functionalized groups of magnetic nanomaterials are considered two main matters for providing separation ability and immobilization substrate, respectively. In addition, the selectivity and stability of aptamer can present a high potential recognition element. Importantly, the integration of aptamer and magnetic nanomaterials benefits can boost the performance of biosensors for biomedical analysis by introducing efficient and compact probes that need low patient samples and fast diagnosis, user-friendly application, and high repeatability in the quantification of biomolecules. The primary aim of this review is to suggest a summary of the effect of the employed other types of nanomaterials in the fabrication of novel aptasensors-based magnetic nanomaterials and to carefully explore various applications of these probes in the quantification of bioagents. Furthermore, the application of these versatile and high-potential probes in terms of the detection of cancer cells and biomarkers, proteins, drugs, bacteria, and nucleoside were discussed. Besides, research gaps and restrictions in the field of biomedical analysis by magnetic nanomaterials-aptamers will be discussed. [ABSTRACT FROM AUTHOR]

An asymmetric Mn/TEMPO-Salen complex was utilized as a reducing agent and template for the synthesis of Mn/TEMPO-doped Fe3O4 NPs in situ. The subsequent thermal decomposition of Mn/TEMPO-doped Fe3O4 NPs, as a precursor, provides the highly porous (641 m2 g–1) Mn2O3-doped Fe3O4 NPs. The highly porous NPs was characterized by FTIR, BET, TGA, VSM, ICP, TEM, XRD, UV–Vis, and XPS analyses. High stability and catalytic activity was found for the NPs in the synthesis of α-aminonitriles via the Strecker synthesis from primary and secondary alcohols under mild conditions. TAIm[CN] ionic liquid (IL) was used as an efficient solvent and nitrile-required reagent to synthesis of α-aminonitriles. TAIm[CN] IL could be recycled for several times by a simple recovery and subsequent treatment. Also, the catalytic activity of the NPs was evaluated toward the selective alcohol oxidation to carbonyl compounds and the direct transformation of imines from alcohols and aryl amines. Mn2O3-doped Fe3O4 NPs could be recovered and reused for several consecutive cycles without any considerable reactivity loss. Highly porous MnO-doped Fe3O4 NPs were synthesized via thermal decomposition of Mn/TEMPO-doped Fe3O4 NPs as a precursor, and used as an efficient recyclable catalyst for the Strecker synthesis from alcohols in TAIm[CN] ionic liquid [ABSTRACT FROM AUTHOR]

This research was conducted to forecast the uniaxial compressive strength (UCS) of rocks via the random forest, artificial neural network, Gaussian process regression, support vector machine, K-nearest neighbor, adaptive neuro-fuzzy inference system, simple regression, and multiple linear regression approaches. For this purpose, geo-mechanical and petrographic characteristics of sedimentary rocks in southern Iran were measured. The effect of petrography on geo-mechanical characteristics was assessed. The carbonate and sandstone samples were classified as mudstone to grainstone and calc-litharenite, respectively. Due to the shallow depth of the studied mines and the low amount of quartz minerals in the samples, the rock bursting phenomenon does not occur in these mines. To develop UCS predictor models, porosity, point load index, water absorption, P-wave velocity, and density were considered as inputs. Using variance accounted for, mean absolute percentage error, root-mean-square-error, determination coefficient (R2), and performance index (PI), the efficiency of the methods was evaluated. Analysis of model criteria using multiple linear regression allowed for the development of a user-friendly equation, which proved to have adequate accuracy. All intelligent methods (with R2 > 90%) had excellent accuracy for estimating UCS. The percentage difference of the average of all six intelligent methods with the measured value was equal to +0.28%. By comparing the methods, the accuracy of the support vector machine with radial basis function in predicting UCS was (R2 = 0.99 and PI = 1.92) and outperformed all the other methods investigated. [ABSTRACT FROM AUTHOR]

A new series of 1,4-bis(1-(5-(aryldiazenyl)thiazol-2-yl)-5-(thiophen-2-yl)-4,5-dihydro-1H-pyrazol-3-yl)benzenes 3a-i were synthesized via reaction of 5,50-(1,4-phenylene)bis(3-(thiophen-2-yl)-4,5-dihydro-1H-pyrazole-1-carbothioamide) (1) with hydrazonoyl halides 2a-i. In addition, reaction of 1 with ethyl chloroacetate afforded bis-thiazolone derivative 8 as the end product. Reaction of compound 8 with methyl glyoxalate gave bis-thiazolone derivative 10. The structures of the newly synthesized compounds were established on the basis of spectroscopic evidences and their alternative syntheses. All the synthesized compounds were evaluated for their anti-tumor activities against hepatocellular carcinoma (HepG2) cell lines, and the results revealed promising activities of compounds 3g, 5e, 3e, 10, 5f, 3i, and 3f with IC50 equal 1.37 ± 0.15, 1.41 ± 0.17, 1.62 ± 0.20, 1.86 ± 0.20, 1.93 ± 0.08, 2.03 ± 0.25, and 2.09 ± 0.19 μM, respectively. [ABSTRACT FROM AUTHOR]