The genus Warburgia (family Canellaceae) is widely distributed over Afrotropical and Neotropical realms. Traditionally, W. salutaris (G. Bertol.) Chiov., and other Warburgia species are used as anti-inflammatory, antimalarial, antimicrobial, and for wound healing, and treating several skin complaints as well. Specifically, different extracts from W. salutaris were reported to possess diuretic, anti-inflammatory, and cytotoxic effects. This work aimed to investigate the phytochemical composition of an aqueous extract from W. salutaris bark, and evaluate its antioxidant and anti-aging activities in silico, in vitro, and in vivo. HPLC-PDA-MS/MS was used to investigate the phytochemical components of the extract. The antioxidant potential of the extract was evaluated in vitro using DPPH and FRAP assays. The Caenorhabditis elegans nematodes model was adopted to investigate the antioxidant and the anti-aging effects in vivo by determining the worms' survival rate, level of ROS, HSP16 expression, and nuclear translocation of the transcription factor DAF16. Molecular operating environment (MOE) software was utilized for in silico molecular docking of the extract's components into different enzymes involved in the aging process. Anti-collagenase, anti-elastase, anti-tyrosinase, and anti-hyaluronidase assays were used to evaluate the anti-aging effects in vitro. HPLC-MS analysis furnished 30 compounds, among them catechin, 11α-hydroxy muzigadiolide, mukaadial, pereniporin B, and 11α-hydroxycinnamosmolide. The major components of the extract showed appropriate fitting in the binding site of the target enzymes adopted in the study with considerable minimum free binding energy relative to the standard inhibitors. The extract showed substantial in vitro antioxidant activity in DPPH and FRAP assays and in vitro anti-aging assays against collagenase, elastase, tyrosinase, and hyaluronidase with comparable IC₅₀ values to the reference standards. Moreover, it attenuated oxidative stress in vivo as it significantly increased the survival rate of ROS stressed C. elegans worms, decreased intracellular ROS, decreased the juglone-induced HSP16 expression and enhanced the nuclear localization of DAF16 in a dose-dependent manner. Our results support the traditional use of W. salutaris to counteract inflammation and oxidative stress associated with several pathological conditions. In addition, W. salutaris bark extract can be considered as a substantial source for bioactive metabolites with strong potential as anti-aging and antioxidant agents.

Water scarcity is a global problem affecting millions of people. It can lead to severe economic, social, and environmental consequences. It can also have several impacts on agriculture, industry, and households, leading to a decrease in human quality of life. To address water scarcity, governments, communities, and individuals must work in synergy for the sake of water resources conservation and the implementation of sustainable water management practices. Following this urge, the enhancement of water treatment processes and the development of novel ones is a must. Here, we have investigated the potential of the applicability of “Green Aerogels” in water treatment’s ion removal section. Three families of aerogels originating from nanocellulose (NC), chitosan (CS), and graphene (G) are investigated. In order to reveal the difference between aerogel samples in-hand, a “Principal Component Analysis” (PCA) has been performed on the physical/chemical properties of aerogels, from one side, and the adsorption features, from another side. Several approaches and data pre-treatments have been considered to overcome any bias of the statistical method. Following the different followed approaches, the aerogel samples were located in the center of the biplot and were surrounded by different physical/chemical and adsorption properties. This would probably indicate a similar efficiency in the ion removal of the aerogels in-hand, whether they were nanocellulose-based, chitosan-based, or even graphene-based. In brief, PCA has shown a similar efficiency of all the investigated aerogels towards ion removal. The advantage of this method is its capacity to engage and seek similarities/dissimilarities between multiple factors, with the elimination of the shortcomings for the tedious and time-consuming bidimensional data visualization.

Industrial dye wastewater is one of the major water pollution problems. Adsorbent materials are promising strategies for the removal of water dye contaminants. Herein, we provide a statistical and artificial intelligence study to evaluate the adsorption efficiency of graphene oxide-based hydrogels in wastewater dye removal by applying Principal Component Analysis (PCA). This study aims to assess the adsorption quality of 35 different hydrogels. We adopted different approaches and showed the pros and cons of each one of them. PCA showed that alginate graphene oxide-based hydrogel (without polyvinyl alcohol) had better tolerance in a basic medium and provided higher adsorption capacity. Polyvinyl alcohol sulfonated graphene oxide-based hydrogels are suitable when higher adsorbent doses are required. In conclusion, PCA represents a robust way to delineate factors affecting hydrogel selection for pollutant removal from aqueous solutions.

Nowadays, acquiring a water supply for urban and industrial uses is one of the greatest challenges facing humanity for ensuring sustainability. Membrane technology has been considered cost-effective, encompasses lower energy requirements, and at the same time, offers acceptable performance. Electrospun nanofibrous membranes (ENMs) are considered a novel and promising strategy for the production of membranes that could be applied in several treatment processes, especially desalination and ion removal. In this study, we apply an unsupervised machine-learning strategy, the so-called principal component analysis (PCA), for the purpose of seeking discrepancies and similarities between different ENMs. The main purpose was to investigate the influence of membrane fabrication conditions, characteristics, and process conditions in order to seek the relevance of the application of different electrospun nanofibrous membranes (ENMs). Membranes were majorly classified into single polymers/layers, from one side, and dual multiple layer ENMs, from another side. For both classes, variables related to membrane fabrication conditions were not separated from membrane characterization variables. This reveals that membranes’ characteristics not only depend on the chemical composition, but also on the fabrication conditions. On the other hand, the process conditions of ENM fabrication showed an extensive effect on membranes’ performance.

Water pollution is caused by multiple factors, such as industrial dye wastewater. Dye-contaminated water can be treated using hydrogels as adsorbent materials. Recently, composite hydrogels containing metal oxide nanoparticles (MONPs) have been used extensively in wastewater remediation. In this study, we use a statistical and artificial intelligence method, based on principal component analysis (PCA) with different applied parameters, to evaluate the adsorption efficiency of 27 different MONP composite hydrogels for wastewater dye treatment. PCA showed that the hydrogel composites CTS@Fe₃O₄, PAAm/TiO₂, and PEGDMA-rGO/Fe₃O₄@cellulose should be used in situations involving high pH, time to reach equilibrium, and adsorption capacity. However, as the composites PAAm-co-AAc/TiO₂, PVPA/Fe₃O₄@SiO₂, PMOA/ATP/Fe₃O₄, and PVPA/Fe₃O₄@SiO₂, are preferred when all physical and chemical properties investigated have low magnitudes. To conclude, PCA is a strong method for highlighting the essential factors affecting hydrogel composite selection for dye-contaminated water treatment.

This research focuses on creating CuO/PANI nanocomposite films by electrodepositing copper oxide nanoparticles into a polyaniline matrix on ITO substrates. The CuO nanoparticle content was adjusted between 7% and 21%. These nanocomposites are promising for various applications, such as optoelectronic devices, gas sensors, electromagnetic interference shielding, and electrochromic devices. We utilized UV-Vis spectroscopy to examine the nanocomposites’ interaction with light, allowing us to ascertain their refractive indices and absorption coefficients. The Scherrer formula facilitated the determination of the average crystallite size, shedding light on the material’s internal structure. Tauc plots indicated a reduction in the energy-band gap from 3.36 eV to 3.12 eV as the concentration of CuO nanoparticles within the PANI matrix increased, accompanied by a rise in electrical conductivity. The incorporation of CuO nanoparticles into the polyaniline matrix appears to enhance the conjugation length of PANI chains, as evidenced by shifts in the quinoid and benzenoid ring vibrations in FTIR spectra. SEM analysis indicates that the nanocomposite films possess a relatively smooth and homogeneous surface. Additionally, FTIR and XRD analyses demonstrate an increasing degree of interaction between CuO nanoparticles and PANI chains with higher CuO concentrations. At lower concentrations, interactions were minimal. In contrast, at higher concentrations, more significant interactions were observed, which facilitated the stretching of polymer chains, improved molecular packing, and facilitated the formation of larger crystalline structures within the PANI matrix. The incorporation of CuO nanoparticles resulted in nanocomposites with electrical conductivities ranging from 1.2 to 17.0 S cm⁻¹, which are favorable for optimum performance in optoelectronic devices. These results confirm that the nanocomposite films combine pronounced crystallinity, markedly enhanced electrical conductivity, and tunable band-gap energies, positioning them as versatile candidates for next-generation optoelectronic devices.