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Heavy metals can cause serious environmental and human health problems, and their removal from wastewater is critical to protect our planet and communities. This study investigated the ability of crushed pomegranate peel to remove mercury and cadmium ions from contaminated water as a function of different experimental parameters. The experimental results showed that the pH of the solution influenced the adsorptive removal of heavy metals, with the best performance observed at pH 4.8. Optimization studies and process balance modeling were performed to optimize the process for commercial use. The performance of pomegranate peel was compared with that of other materials, and the highest adsorption capacities for both cadmium (Ca (II)) and mercury (Hg (II)) ions were observed to be 89.59 and 42.125 mg/g, respectively. The results were interpreted using the Langmuir model, which provided the best fit to describe the behavior of the process.

The side effects of chronic exposure to synthetic drugs such as tramadol have become a concern for the health system. Medicinal plants can be used as rich sources of natural compounds with therapeutic properties to reduce the side effects of synthetic drugs such as tramadol. Hence, this study sought to review the published research concerning the protective role of medicinal plants against tramadol toxicity. This systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. This study included all published articles evaluating the efficacy of the medicinal plants against tramadol toxicity until December, 2021. For this systematic review, search was performed using keywords including tramadol, toxicity, poisoning, overdose, medicinal plants, and herbal medicines from reliable databases such as PubMed, Google Scholar, Web of Science, Wiley, Elsevier, and Science Direct. The risk of bias tool for animal intervention studies (SYRCLE’s RoB tool) criteria and the OECD guidelines and the WHO Good Laboratory Practice (GLP) handbook were used for quality assessment of animal and in vitro studies, respectively. This review determined 18 medicinal plants and one multi herbal formulation against tramadol toxicity. Plants such as Nigella sativa (Black Seed), Moringa Oleifera (Drumstick tree), and Aloe Vera, pomegranate, wheat, barely, pumpkin, walnut, kiwi fruit, turmeric, apple, fennel, and garlic also displayed therapeutic effects against tramadol toxicity. This review exhibits a wide range of medicinal plants with therapeutic effects such as antioxidant, anti-inflammatory and anti-apoptotic properties which could protect the organs of the body against toxicity caused by tramadol. Hence, the use of these plants or their compounds can be effective in reducing the complications caused by many diseases.

In this study, a facile, environmentally friendly, room-temperature synthesis of Ag-coated on microporous TiO2-based catalysts and their application as a photocatalyst to degradation of penicillin as an antibiotic from pharmaceutical wastewater was investigated. The sol-gel method was used for the preparation of SiO2 and SiO2@TiO2. Then, the SiO2@TiO2 was wrinkled using hydrothermal treatment. Finally, Ag as plasmonic material was doped on wrinkled photocatalyst via wet chemistry approach. The synthesised photocatalysts were characterized using different analyses such as XRD, FTIR, RAMAN, FESEM, TEM, XPS. The results showed that the Ag was successfully coated on the wrinkled TiO2 layer. The performance of the synthesised photocatalyst was studied in terms of penicillin antibiotic removal from pharmaceutical wastewater in the range of visible light. The band gap energy (Eg) of SiO2 and after addition of TiO2 and Ag was obtained 4.5 and 2.8–3.2 eV. Specific surface of SiO2 and SiO2@WS-TiO2 was found 293 and 329 m2/g respectively. The results indicated that wrinkling and coating Ag can enhance the SiO2@TiO2 photocatalyst activity for degradation of penicillin. Furthermore, the operating parameter of degradation of penicillin such pH, contact time, initial penicillin concentration, temperature, and the amount of synthesized photocatalyst was optimized. Finally, it was found that Langmuir isotherm model is well fitted with experimental data to predict kinetic of penicillin degradation.

In this study, laminar mixed convection of water/Ag nanofluid with volume fraction of nanoparticles φ = 0, 2, 4, and 6% and Grashof numbers Gr = 50,000, 150,000, 250,000 and 400,000 and Richardson numbers Ri = 0.1, 1, and 10 are simulated using finite volume method. Obtained results indicate that adding a higher volume fraction of nanoparticles at lower Richardson numbers leads to the enhancement of heat transfer and Nusselt number. Streamlines behavior in the cavity is under the influence of two main factors including lid-driven motion (which is the basic factor) and the viscosity of fluid (which transfers the fluid motion to bottom layers and affects the flow domain). Every factor stimulating the flow domain causes uniform temperature distribution in the cavity. The increase of Richardson number leads to the enhancement of lid-driven velocity, temperature penetration and a better mixture of fluid layers, and by increasing Grashof number; this issue can have a great effect on uniform temperature distribution.

Abstract Concanavalin A (ConA), the most studied plant lectin, has been known as a potent anti-neoplastic agent for a long time. Since initial reports on its capacity to kill cancer cells, much attention has been devoted to unveiling the lectin's exact molecular mechanism. It has been revealed that ConA can bind to several receptors on cancerous and normal cells and modulate the related signaling cascades. The most studied host receptor for ConA is MT1-MMP, responsible for most of the lectin's modulations, ranging from activating immune cells to killing tumor cells. In this study, in addition to studying the effect of ConA on signaling and immune cell function, we will focus on the most up-to-date advancements that unraveled the molecular mechanisms by which ConA can induce autophagy and apoptosis in various cancer cell types, where it has been found that P73 and JAK/STAT3 are the leading players. Moreover, we further discuss the main signaling molecules causing liver injury as the most significant side effect of the lectin injection. Altogether, these findings may shed light on the complex signaling pathways controlling the diverse responses created via ConA treatment, thereby modulating these complex networks to create more potent lectin-based cancer therapy. Video Abstract

Abstract Conductive gels are a special class of soft materials. They harness the 3D micro/nanostructures of gels with the electrical and optical properties of semiconductors, producing excellent novel attributes, like the formation of an intricate network of conducting micro/nanostructures that facilitates the easy movement of charge carriers. Conductive gels encompass interesting properties, like adhesion, porosity, swelling, and good mechanical properties compared to those of bulk conducting polymers. The porous structure of the gels allows the easy diffusion of ions and molecules and the swelling nature provides an effective interface between molecular chains and solution phases, whereas good mechanical properties enable their practical applications. Due to these excellent assets, conductive gels are promising candidates for applications like energy conversion and storage, sensors, medical and biodevices, actuators, superhydrophobic coatings, etc. Conductive gels offer promising applications, e.g., as soft sensors, energy storage, and wearable electronics. Hydrogels with ionic species have some potential in this area. However, they suffer from dehydration due to evaporation when exposed to the air which limits their applications and lifespan. In addition to conductive polymers and organic charge transfer complexes, there is another class of organic matter called “conductive gels” that are used in the organic nanoelectronics industry. The main features of this family of organic materials include controllable photoluminescence, use in photon upconversion technology, and storage of optical energy and its conversion into electricity. Various parameters change the electronic and optical behaviors of these materials, which can be changed by controlling some of the structural and chemical parameters of conductive gels, their electronic and optical behaviors depending on the applications. If the conjugated molecules with π bonds come together spontaneously, in a relative order, to form non-covalent bonds, they form a gel-like structure that has photoluminescence properties. The reason for this is the possibility of excitation of highest occupied molecular orbital level electrons of these molecules due to the collision of landing photons and their transfer to the lowest unoccupied molecular orbital level. This property can be used in various nanoelectronic applications such as field-effect organic transistors, organic solar cells, and sensors to detect explosives. In this paper, the general introduction of conductive or conjugated gels with π bonds is discussed and some of the physical issues surrounding electron excitation due to incident radiation and the mobility of charge carriers, the position, and role of conductive gels in each of these applications are discussed.

ANFIS (Adaptive neuro fuzzy inference system) modeling of CO2 capture using chemical absorbent was carried out in this study to correlate the solubility of CO2 to the solvent and operational parameters. In the ANFIS model, the input parameters including temperature, pressure, and physio-chemical properties of the solvent were considered, while the loading of CO2 in the absorbent was considered as the sole target output to be predicted by the model. Indeed, we developed a machine learning based model for predicting the CO2 loading capacity in amino acid salt solutions as the chemical absorbent of carbon dioxide. This model uses a metaheuristic optimized ANFIS based on a wide range of amino acids. This study's novel part is the use of Differential Evolution (DE) and Firefly Algorithm (FA) metaheuristics in order to solve hyper-parameter tuning of ANFIS as an optimization problem based on differential evolution. Accordingly, the optimized ANFIS model has an R2 score of 0.9520 for the test data and a score of 0.9841 for the training data. This indicates that the proposed model is both general and accurate in terms of its predictions for CO2 loading in amino acid salt solutions. The MAPE and RMSE error rates are also 1.17E-01, respectively, while the MAPE error rate is 1.14E-01.

Adsorption process was simulated in this study for removal of Hg and Ni from water using nanocomposite materials. The used nanostructured material for the adsorption study was a combined MOF and layered double hydroxide, which is considered as MOF-LDH in this work. The data were obtained from resources and different machine learning models were trained. We selected three different regression models, including elastic net, decision tree, and Gradient boosting, to make regression on the small data set with two inputs and two outputs. Inputs are Ion type (Hg or Ni) and initial ion concentration in the feed solution (C0), and outputs are equilibrium concentration (Ce) and equilibrium capacity of the adsorbent (Qe) in this dataset. After tuning their hyper-parameters, final models were implemented and assessed using different metrics. In terms of the R2-score metric, all models have more than 0.97 for Ce and more than 0.88 for Qe. The Gradient Boosting has an R2-score of 0.994 for Qe. Also, considering RMSE and MAE, Gradient Boosting shows acceptable errors and best models. Finally, the optimal values with the GB model are identical to dataset optimal: (Ion = Ni, C0 = 250, Ce = 206.0). However, for Qe, it is different and is equal to (Ion = Hg, C0 = 121.12, Ce = 606.15). The results revealed that the developed methods of simulation are of high capacity in prediction of adsorption for removal of heavy metals using nanostructure materials.

BackgroundShorter telomere length is associated with numerous comorbidities. Several studies have investigated the role of obesity in telomere shortening. In the current systematic review and meta-analysis, we summarized the results of studies that evaluated the association between obesity and telomere length.MethodsA systematic search from Scopus, PubMed, Embase, and ProQuest electronic databases up to 19 March 2021 without language restriction was performed and after data extraction and screening, 19 manuscripts were eligible to be included in the final meta-synthesis.ResultsThe highest category of telomere length was associated with an approximate 0.75 kg/m2 reduction in body mass index (BMI; WMD = −0.75 kg/m2; CI = −1.19, −0.31; p < 0.001; I2 = 99.4%). Moreover, overweight/obese individuals had 0.036 kbp shorter telomere length compared with non-overweight/obese adults (WMD = −0.036; CI = −0.05, −0.02; p = 0.030; I2 = 100%). According to the results of subgroupings, continent, age, and sample size could be possible sources of heterogeneity.ConclusionFrom the results, it was clear that obesity was associated with shorter telomere length. Because of the observational design of included studies, the causality inference of results should be done with caution; thus, further longitudinal studies are warranted for better inference of causal association.

Machine learning (ML) methods were developed and optimized for description and understanding a physical separation process. Indeed, this work indicates application of machine learning technique for a real physical system and optimization of process parameters to achieve the target. A bunch of datasets were extracted from resources for physical adsorption process in removal of impurities from water as a case study to test the developed machine learning model. The case study process is adsorption process which has extensive application in science and engineering. The machine learning (ML) method was developed, and the parameters were optimized in order to get the best simulation’s performance for adsorption process. The data are used to correlate the adsorption capacity of the material to the adsorption parameters including dosage and solution pH. Randomized training and validation were performed to predict the process’s output, and great agreement was obtained between the predicted values and the observed values with R2 values greater than 0.9 for all cases of training and validation at the optimum conditions. Three different machine learning techniques including Random Forest (RF), Extra Tree (ET), and Gradient Boosting (GB) were employed for the adsorption data. Quantitatively, R2 scores of 0.958, 0.998, and 0.999 were obtained for RF, GB, and ET, respectively. It was indicated that GB and ET models performed almost the same and better than RF in prediction of adsorption data.

Breast cancer is the most common invasive cancer in women and the second leading cause of cancer death in women after lung cancer. The purpose of this study is a targeted delivery toward in vitro (on MCF7 and 4T1 breast cancer cell lines) through niosomes-based nanocarriers. To this end, different bioactive molecules, including hyaluronic acid (HA), folic acid (FA), and polyethylene glycol (PEG), were used and compared for surface modification of niosomes to enhance endocytosis. FA-functionalized niosomes (Nio/5-FU/FA) were able to increase cell cytotoxicity and reduce cell migration and invasion compared to PEG-functionalized niosomes (Nio/5-FU/PEG), and HA-functionalized niosomes (Nio/5-FU/HA) groups in MCF-7 and 4T1 cell lines. Although the Nio/5-FU/PEG and Nio/5-FU/HA demonstrated MCF7 cell uptake, the Nio/5-FU/FA exhibited the most preponderant endocytosis in pH 5.4. Remarkably, in this study 5-FU loaded niosomes (nonionic surfactant-based vesicles) were decorated with various bioactive molecules (FA, PEG, or HA) to compare their ability for breast cancer therapy. The fabricated nanoformulations were readily taken up by breast cancer cells (in vitro) and demonstrated sustained drug release characteristics, inducing cell apoptosis. Overall, the comprehensive comparison between different bioactive molecules-decorated nanoniosomes exhibited promising results in finding the best nano formulated candidates for targeted delivery of drugs for breast cancer therapy.

Traumatic brain injury (TBI) is still a major cause of concern for public health, and out of all the trauma-related injuries, it makes the highest contribution to death and disability worldwide. Patients of TBI continue to suffer from brain injury through an intricate flow of primary and secondary injury events. However, when treatment is provided in a timely manner, there is a significant window of opportunity to avoid a few of the serious effects. Pioglitazone (PG), which has a neuroprotective impact and can decrease inflammation after TBI, activates peroxisome proliferator-activated receptor-gamma (PPARγ). The objective of the study is to examine the existing literature to assess the neuroprotective and anti-inflammatory impact of PG in TBI. It also discusses the part played by microglia and cytokines in TBI. According to the findings of this study, PG has the ability to enhance neurobehavior, decrease brain edema and neuronal injury following TBI. To achieve the protective impact of PG the following was required: (1) stimulating PPARγ; (2) decreasing oxidative stress; (3) decreasing nuclear factor kappa B (NF-κB), interleukin 6 (IL-6), interleukin-1β (IL-1β), cyclooxygenase-2 (COX-2), and C-C motif chemokine ligand 20 (CCL20) expression; (4) limiting the increase in the number of activated microglia; and (5) reducing mitochondrial dysfunction. The findings indicate that when PIG is used clinically, it may serve as a neuroprotective anti-inflammatory approach in TBI.

Species, known as mixture herbal products, are compositions of several types of crushed, sometimes whole, medicinal plant materials with additives; they are a widely used dosage form in the Russian Federation. A large range of species are produced at the pharmaceutical companies. In pharmacopoeial analysis, the most popular and widely used method for the determination of flavonoids, suitable for the standardization of species, is the method of differential spectrophotometry, based on the complexation of flavonoids with aluminum chloride. In accordance with modern requirements for the drugs production, the validation of analytical methods is a prerequisite for the creation of pharmacopoeial monographs projects regulating the quality of pharmaceutical substances of plant origin. Therefore, it is necessary to validate analytical methods for their intended use in evaluating the drug quality. This article discusses/presents the main stages of development and validation (by parameters: accuracy, precision, specificity, linearity) of the methodology for determining total flavonoid content using original species “Fitourol” as a model.

The melting duration in the photovoltaic/phase-change material (PV/PCM) system is a crucial parameter for thermal energy management such that its improvement can realize better energy management in respect to thermal storage capabilities, thermal conditions, and the lifespan of PV modules. An innovative and efficient technique for improving the melting duration is the inclusion of an exterior metal foam layer in the PV/PCM system. For detailed investigations of utilizing different metal foam configurations in terms of their convective heat transfer coefficients, the present paper proposes a newly developed mathematical model for the PV/PCM–metal foam assembly that can readily be implemented with a wide range of operating conditions. Both computational fluid dynamic (CFD) and experimental validations proved the good accuracy of the proposed model for further applications. The present research found that the average PV cell temperature can be reduced by about 12 °C with a corresponding improvement in PCM melting duration of 127%. The addition of the metal foam is more effective at low solar radiation, ambient temperatures far below the PCM solidus temperature, and high wind speeds in nonlinear extension. With increasing of tilt angle, the PCM melting duration is linearly decreased by an average value of (13.4–25.0)% when the metal foam convective heat transfer coefficient is changed in the range of (0.5–20) W/m2.K. The present research also shows that the PCM thickness has a positive linear effect on the PCM melting duration, however, modifying the metal foam configuration from 0.5 to 20 W/m2.K has an effect on the PCM melting duration in such a way that the average PCM melting duration is doubled. This confirms the effectiveness of the inclusion of metal foam in the PV/PCM system.

Due to the potential cost saving and minimal temperature stratification, the energy storage based on phase-change materials (PCMs) can be a reliable approach for decoupling energy demand from immediate supply availability. However, due to their high heat resistance, these materials necessitate the introduction of enhancing additives, such as expanded surfaces and fins, to enable their deployment in more widespread thermal and energy storage applications. This study reports on how circular fins with staggered distribution and variable orientations can be employed for addressing the low thermal response rates in a PCM (Paraffin RT-35) triple-tube heat exchanger consisting of two heat-transfer fluids flow in opposites directions through the inner and the outer tubes. Various configurations, dimensions, and orientations of the circular fins at different flow conditions of the heat-transfer fluid were numerically examined and optimized using an experimentally validated computational fluid-dynamic model. The results show that the melting rate, compared with the base case of finless, can be improved by 88% and the heat charging rate by 34%, when the fin orientation is downward–upward along the left side and the right side of the PCM shell. The results also show that there is a benefit if longer fins with smaller thicknesses are adopted in the vertical direction of the storage unit. This benefit helps natural convection to play a greater role, resulting in higher melting rates. Changing the fins’ dimensions from (thickness × length) 2 × 7.071 mm2 to 0.55 × 25.76 mm2 decreases the melting time by 22% and increases the heat charging rate by 9.6%. This study has also confirmed the importance of selecting the suitable values of Reynolds numbers and the inlet temperatures of the heat-transfer fluid for optimizing the melting enhancement potential of circular fins with downward–upward fin orientations.

Thermal energy storage is an important component in energy units to decrease the gap between energy supply and demand. Free convection and the locations of the tubes carrying the heat-transfer fluid (HTF) have a significant influence on both the energy discharging potential and the buoyancy effect during the solidification mode. In the present study, the impact of the tube position was examined during the discharging process. Liquid-fraction evolution and energy removal rate with thermo-fluid contour profiles were used to examine the performance of the unit. Heat exchanger tubes are proposed with different numbers and positions in the unit for various cases including uniform and non-uniform tubes distribution. The results show that moving the HTF tubes to medium positions along the vertical direction is relatively better for enhancing the solidification of PCM with multiple HTF tubes. Repositioning of the HTF tubes on the left side of the unit can slightly improve the heat removal rate by about 0.2 in the case of p5-u-1 and decreases by 1.6% in the case of p5-u-2. It was found also that increasing the distance between the tubes in the vertical direction has a detrimental effect on the PCM solidification mode. Replacing the HTF tubes on the left side of the unit negatively reduces the heat removal rate by about 1.2 and 4.4%, respectively. Further, decreasing the HTF temperature from 15 °C to 10 and 5 °C can increase the heat removal rate by around 7 and 16%, respectively. This paper indicates that the specific concern to the HTF tube arrangement should be made to improve the discharging process attending free convection impact in phase change heat storage.