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Wastewater containing a mixture of heavy metals, a byproduct of chemical, petrochemical, and refinery activities driven by urbanization and industrial expansion, poses significant environmental threats. Analyzing such wastewater through adsorbate-adsorbent experiments yields extensive datasets. However, traditional methodologies like the Box–Behnken design (BBD) within the response surface methodology (RSM) struggle with managing large datasets and capturing the complex, nonlinear relationships inherent in such experimental data. To address these challenges, ML techniques have emerged as promising tools for accurately predicting the removal percentage of heavy metals from wastewater. In this study, we utilized tree-based regression models—specifically decision tree regression (DTR), random forest regression (RFR), and extra tree regression (ETR)—to forecast the efficiency of gooseberry seed powder in removing chromium (Cr(VI)) from wastewater. Additionally, we employed an ML-based Nelder–Mead optimization approach to identify the optimal values for key features (initial Cr(VI) concentration, pH, and Indian gooseberry powder dosage) which maximized the Cr(VI) removal percentage. Our experimental results reveal that the ETR model achieved an impressive R 2 score of 0.99, demonstrating a low error rate in predicting the Cr(VI) removal percentage. Furthermore, we used DTR-Nelder–Mead, RFR-Nelder–Mead, and ETR-Nelder–Mead optimization approaches on a synthesized dataset of 2000 instances while varying the initial Cr(VI) concentration, pH, and Indian gooseberry powder dosage. The analysis determined that the DTR-Nelder–Mead and RFR-Nelder–Mead approaches yielded the highest Cr(VI) removal percentages of 78.21% and 78.107% at an initial concentration of 95.55 mg/L, respectively, a pH level of four, and an adsorbent dosage of 8 g/L of gooseberry seed powder. Furthermore, the ETR-Nelder–Mead approach obtained the maximum Cr(VI) removal percentage of 85.11% at an initial concentration of 99.25 mg/L, a pH level of 4.97, and an adsorbent dosage of 9.62 g/L of gooseberry seed powder. These results reported an increase in the Cr(VI) removal percentage ranging from 4.66% to 11.56% more than the Cr(VI) removal percentage obtained by experimentation. These findings underscore the efficacy of tree-based regression models and ML-based Nelder–Mead optimization in elucidating chromium removal processes from wastewater, offering valuable insights into effective treatment strategies. [ABSTRACT FROM AUTHOR]

Pyridine derivatives are the most common and significant heterocyclic compounds, which play an important role in various fields ranging from medicinal to chemosensing applications. Pyridine derivatives possess different biological activities such as antifungal, antibacterial, antioxidant, antiglycation, analgesic, antiparkinsonian, anticonvulsant, anti-inflammatory, ulcerogenic, antiviral, and anticancer activity. Furthermore, these derivatives have a high affinity for various ions and neutral species and can be used as a highly effective chemosensor for the determination of different species. In this review article, generally used synthetic routes of pyridine, structural characterization, medicinal applications, and potential of pyridine derivatives in analytical chemistry as chemosensors have been discussed. We hope this study will support the new thoughts to design biological active compounds and highly selective and effective chemosensors for the detection of various species (anions, cations, and neutral species) in various samples (environmental, agricultural, and biological). [ABSTRACT FROM AUTHOR]

We designed and synthesized a fluorescent "turn-on" and colorimetric chemosensor ((E)-1-((p-tolylimino)methyl)naphthalen-2-ol) SB. The structure of the synthesized chemosensor was investigated by 1H NMR, FT-IR, and fluorescence spectroscopy, and its sensing properties were studied toward Mn2+, Cu2+, Pb2+, Cd2+, Na+, Ni2+, Al3+, K+, Ag+, Zn2+, Co2+, Cr3+, Hg2+, Ca2+, and Mg2+. SB showed an excellent colorimetric (yellow to yellowish brown) in MeOH and fluorescence "turn-on" sensing response to Cu2+ in MeOH/Water (10/90, v/v) media. The sensing mechanism of SB toward Cu2+ was investigated by FT-IR, 1H NMR titration, DFT studies, and Job's plot analysis. The detection limit was calculated to be very low 0.0025 µg mL−1 (0.0025 ppm). Furthermore, the test strip containing SB also showed excellent selectivity and sensitivity toward Cu2+ in a solution medium and when supported on a solid medium. [ABSTRACT FROM AUTHOR]

Polymeric nanoparticles are widely studied in the treatment of colorectal cancer. Kaempferitrin‐loaded nontoxic and biodegradable poly(d,l‐lactic‐co‐glycolic acid) (PLGA) nanoparticles (NPs) developed by the solvent emulsion evaporation method by improving its solubility and bioavailability. In order to improve the delivery of kaempferitrin (KM) to cancerous cells, folic acid (FA) combined kaempfertrin PLGA NPs were prepared. The goal of the study was whether PLGA NPs with surface KM and FA could help to prevent colorectal cancer. The synthesis of KM with FA in a nanomedicine could be crucial in the development of colon cancer chemotherapeutics. The physicochemical characteristics of synthesized KM‐entrapped PLGA NPs were investigated by XRD, FTIR, zeta potential, and TEM. The KM + FA + PLGA NPs showed particle size with 132.9 ± 1.4 nm, zeta potential ‒15.0 ± 1.73 mV, encapsulation efficiency 67.92 ± 4.8, and drug‐loading capacity 0.463 ± 0.173. In vitro cytotoxicity study on HT‒29 cell lines using the MTT assay, the apoptotic study revealed that KM + FA + PLGA NPs have an enhanced cytotoxic effect compared to the KM + PLGA NPs drug solution. These findings suggested that KM + FA + PLGA NPs could be an effective chemotherapeutic drug delivery system in colon adenocarcinoma HT‐29 cells. [ABSTRACT FROM AUTHOR]