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The presence of toxic chemicals in water, including heavy metals like mercury and lead, organic pollutants such as pesticides, and industrial chemicals from runoff and discharges, poses critical public health and environmental risks leading to severe health issues and ecosystem damage; education plays a crucial role in mitigating these effects by enhancing awareness, promoting sustainable practices, and integrating environmental science into curricula to empower individuals to address and advocate for effective solutions to water pollution. However, the educational transformation should be accompanied with a technical process which can be eventually transferred to society to empower environmental education. In this study, carbonaceous material derived from Haematoxylum campechianum (CM-HC) was utilized for removing 3-nitrophenol (3-Nph) from aqueous solutions. The novelty of this research utilizes Haematoxylum campechianum bark and coconut shell, abundant agricultural wastes in Campeche, Mexico, for toxin removal, enhancing the adsorption process through artificial neural networks and genetic algorithms to optimize conditions and maximize the absorption efficiency. CM-HC's surface morphology was analyzed using scanning electron microscopy (SEM/EDS), BET method, X-ray powder diffraction (XRD), and pHpzc. Kinetic models including pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich were applied to fit the data. Adsorption isotherms were determined at varying pH (3-8), adsorbent dosages (2-10 g/L), and temperatures (300.15-330.15 K), employing Langmuir, Freundlich, Temkin, and Redlich-Peterson models. PSO kinetics demonstrated a good fit (R2 > 0.98) for Ci = 50-100 mg/L, indicating a chemical adsorption mechanism. The Langmuir isotherm model exhibited the best fit, confirming chemical adsorption, with a maximum adsorption capacity (Qm) of 236.156 mg/g at T = 300.15 K, pH = 6, contact time = 3 h, and 2 g/L adsorbent dosage. Lower temperatures favored exothermic adsorption. Artificial neural networks (ANNs) were employed for deep learning, optimizing the predictive model for removal percentage. Correlation heat maps highlighted positive correlations between time, dosage, and removal percentage, emphasizing the impact of initial concentration on efficiency. ANN modeling, incorporating iterative optimization, yielded highly accurate predictions, aligned closely with experimental results. The study showcases the success of deep learning in optimizing adsorption processes, emphasizing the importance of diverse correlation algorithms for comprehensive insights into competitive adsorption dynamics. The 5-14-14-1 deep learning architecture, fine-tuned over 228 epochs, demonstrated strong performance with mean squared error (MSE) values of 4.07, 18.406, and 6.2122 for training, testing, and total datasets, respectively, and high R-squared values. Graphical analysis showed a solid linear correlation between experimental and simulated removal percentages, emphasizing the need to consider more than just testing data for optimization. Experimental validation confirmed a 98.77% removal efficiency, illustrating the effectiveness of combining deep learning with genetic algorithms, and highlighting the necessity of experimental trials to verify computational predictions. It is concluded that the carbonaceous material from Haematoxylum campechianum waste (CM-HC) is an effective, low-cost adsorbent for removing 3-nitrophenol from aqueous solutions, achieving optimal removal at pH 6 and 300.15 K with a maximum adsorption capacity of 236.156 mg/g, following Langmuir model and pseudo-second order kinetics. The validated ANN model offers a reliable tool for practical applications in environmental remediation, advancing both environmental science and educational innovation by integrating artificial neural networks and data science methodologies into student learning experiences.

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The influence of ultrasound-assisted extraction of phytochemicals from Ardisia compressa Kunth on the antioxidant capacity was investigated. The factors evaluated were: ultrasound extraction time (10, 20 and 30 min), ethanol concentration (0, 35, 70 %) and solid/liquid ratio (1:4, 1:8 and 1:12 g mL-1). The L9 (3)3 array was applied, and the DPPH• scavenging capacity of treatments was evaluated to obtain optimal extraction conditions. Finally, the phytochemicals were characterized by high-performance liquid chromatography electrospray ionization mass spectrometry (HPLC-ESI-MS). Ten minutes of ultrasound extraction using 0 % of ethanol and solid/liquid ratio 1:12 g mL-1 were the optimal conditions of extraction. The HPLC-ESI-MS analysis revealed the presence of gluconic acid, quercetin-3-O-glucoside, isorhamnetin-3-O-rutinoside, demethylligstroside, ponicidin, 4-caffeoylquinic acid, rosmarinic acid, and galloyl-hexoside. The optimal ultrasound-assisted extraction conditions were defined by applying the Taguchi methodology. The phytochemicals identified in A. compressa fruits suggest its use as a potential source of bioactive compounds.

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Various ion channels, including ATP-sensitive potassium (KATP) channels, are expressed in cancer and have been suggested as potential tumor markers and therapeutic targets. KATP channels are composed of at least two types of subunit, an inwardly rectifying K+ channel (Kir6.x) and a sulfonylurea receptor (SUR). However, the association between KATP channels and cervical cancer remains elusive. The present study determined that the Kir6.2, SUR1 and SUR2 subunits are expressed in cervical cancer cell lines and/or human biopsies. The potential association of subunit expression with tumor differentiation and invasion was analyzed. The effect of the KATP channel blocker glibenclamide on the proliferation of cervical cancer cell lines was also studied. Five cervical cancer cell lines, two primary cultures of cervical cancer cells, one normal keratinocyte cell line and 74 human biopsies were used in the experiments. The mRNA and protein levels of the Kir6.2 subunit were assessed by reverse transcription-polymerase chain reaction and immunochemistry, respectively. Cell proliferation was evaluated by MTT assay. Kir6.2 subunit overexpression compared with control, was observed in some cervical cancer cell lines and cervical tumor tissues. Additionally, increased KATP channel expression was observed in high-grade, poorly differentiated and invasive human cervical cancer biopsies. Kir6.2 subunit expression was not observed in the majority of the non-cancerous cervical tissues. The effect of the KATP channel blocker glibenclamide on the proliferation of five different cervical cancer cell lines was studied, revealing that as Kir6.2 mRNA expression increased, the inhibitory effect of glibenclamide also increased. The results of the present study suggest, for the first time to the best of our knowledge, that the KATP channel subunits, Kir6.2 and SUR2, could potentially represent tools for diagnosing and treating cervical cancer.

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Oxidative stress results from a disturbed balance between oxidation and antioxidant systems. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) may be either harmful or beneficial to the cells. Ion channels are transmembrane proteins that participate in a large variety of cellular functions and have been implicated in the development of a variety of diseases. A significant amount of the available drugs in the market targets ion channels. These proteins have sulfhydryl groups of cysteine and methionine residues in their structure that can be targeted by ROS and RNS altering channel function including gating and conducting properties, as well as the corresponding signaling pathways associated. The regulation of ion channels by ROS has been suggested to be associated with some pathological conditions including liver diseases. This review focuses on understanding the role and the potential association of ion channels and oxidative stress in liver diseases including fibrosis, alcoholic liver disease, and cancer. The potential association between ion channels and oxidative stress conditions could be used to develop new treatments for major liver diseases.

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Oncogenic ether à-go-go-1 (Eag1) potassium channels are overexpressed in most primary human solid tumors. Low oxygen and nutrient/growth factor concentrations play critical roles in tumorigenesis. However, the mechanisms by which tumor cells survive and proliferate under growth factor-depleted conditions remain elusive. Here, we investigated whether serum-deprived conditions and epidermal growth factor (EGF) regulate Eag1 expression in human lung and breast cancer cells. The human cancer cell lines A549 and MCF-7 (from the lungs and breast, respectively) were obtained from the American Type Culture Collection and cultured following the manufacturer's recommendations. Eag1 gene and protein expression were studied by real-time PCR and immunocytochemistry, respectively. Cell proliferation was evaluated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, and ERK1/2 phosphorylation was investigated by Western blot. Serum-deprived conditions increased Eag1 mRNA and protein expression in both cell lines. This Eag1 upregulation was prevented by EGF and the ERK1/2 inhibitor U0126 in only lung cancer cells; vascular endothelial growth factor did not prevent Eag1 upregulation. Our results suggest that Eag1 may act as a survival and mitogenic factor under low-serum and nutrient conditions and may be a clinical target during the early stages of tumor development.