Comparative study on Perfluoro(2-methyl-3-oxahexanoic) acid removal by quaternary ammonium functionalized silica gel and granular activated carbon from batch and column experiments and molecular simulation-based interpretation.

Removing perfluoro(2-methyl-3-oxahexanoic) acid (HFPO-DA) in water treatment is hindered by its hydrophobicity and negative charge. Two adsorbents, quaternary-ammonium-functionalized silica gel (Qgel), specifically designed for anionic hydrophobic compounds, and conventional granular activated carbon (GAC) were investigated for HFPO-DA removal. ANOVA results (p â‰ª 0.001) revealed significant effects on initial concentration, contact time, and adsorbent type. Langmuir model-derived capacities were 285.019 and 144.461 mg/g for Qgel and GAC, respectively, with Qgel exhibiting higher capacity irrespective of pH. In column experiments, selective removal of HFPO-DA removal with Qgel was observed; specifically, in the presence of NaCl, the breakthrough time was extended by 10 h from 26 to 36 h. Meanwhile, the addition of NaCl decreased the breakthrough time from 32 to 14 h for GAC. However, in the presence of carbamazepine, neither of the adsorbents significantly changed the breakthrough time for HFPO-DA. Molecular simulations were also used to compare the adsorption energies and determine the preferential interactions of HFPO-DA and salts or other chemicals with Qgel and GAC. Molecular simulations compared adsorption energies, revealing preferential interactions with Qgel and GAC. Notably, HFPO-DA adsorption energy on GAC surpassed other ions during coexistence. Specifically, with Cl- concentrations from 1 to 10 times, Qgel showed lower adsorption energy for HFPO-DA (-62.50 ± 5.44 eV) than Cl- (-52.89 ± 2.59 eV), a significant difference (p = 0.036). Conversely, GAC exhibited comparable or higher adsorption energy for HFPO-DA (-18.33 ± 40.38 eV) than Cl- (-32.36 ± 29.89 eV), with no significant difference (p = 0.175). This suggests heightened selectivity of Qgel for HFPO-DA removal compared to GAC. Consequently, our study positions Qgel as a promising alternative for effective HFPO-DA removal, contributing uniquely to the field. Additionally, our exploration of molecular simulations in predicting micropollutant removal adds novelty to our study.

Identification of organic chemical indicators for tracking pollution sources in groundwater by machine learning from GC-HRMS-based suspect and non-target screening data.

In this study, the strong analytical power of gas chromatography coupled to a high resolution mass spectrometry (GC-HRMS) in suspect and non-target screening (SNTS) of organic micropollutants was combined with machine learning tools for proposing a novel and robust systematic environmental forensics workflow, focusing on groundwater contamination. Groundwater samples were collected from four different regions with diverse contamination histories (namely oil [OC], agricultural [AGR], industrial [IND], and landfill [LF]), and a total of 252 organic micropollutants were identified, including pharmaceuticals, personal care products, pesticides, polycyclic aromatic hydrocarbons, plasticizers, phenols, organophosphate flame retardants, transformation products, and others, with detection frequencies ranging from 3 % to 100 %. Amongst the SNTS identified compounds, a total of 51 chemical indicators (i.e., OC: 13, LF: 12, AGR: 19, IND: 7) which included level 1 and 2 SNTS identified chemicals were pinpointed across all sampling regions by integrating a bootstrapped feature selection method involving the bootfs algorithm and a partial least squares discriminant analysis (PLS-DA) model to determine potential prevalent contamination sources. The proposed workflow showed good predictive ability (Q2) of 0.897, and the suggested contamination sources were gasoline, diesel, and/or other light petroleum products for the OC region, anthropogenic activities for the LF region, agricultural and human activities for the AGR region, and industrial/human activities for the IND region. These results suggest that the proposed workflow can select a subset of the most diagnostic features in the chemical space that can best distinguish a specific contamination source class.

Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma: Meta-Analysis and International Stereotactic Radiosurgery Society Practice Guidelines.

This systematic review and meta-analysis reports on outcomes and hepatic toxicity rates after stereotactic body radiation therapy (SBRT) for liver-confined hepatocellular carcinoma (HCC) and presents consensus guidelines regarding appropriate patient management. Using the Preferred Reporting Items for Systemic Review and Meta-Analyses guidelines, a systematic review was performed from articles reporting outcomes at ≥5 years published before October 2022 from the Embase, MEDLINE, Cochrane, and Scopus databases with the following search terms: ("stereotactic body radiotherapy" OR "SBRT" OR "SABR" OR "stereotactic ablative radiotherapy") AND ("hepatocellular carcinoma" OR "HCC"). An aggregated data meta-analysis was conducted to assess overall survival (OS) and local control (LC) using weighted random effects models. In addition, individual patient data analyses incorporating data from 6 institutions were conducted as their own subgroup analyses. Seventeen observational studies, comprising 1889 patients with HCC treated with ≤9 SBRT fractions, between 2003 and 2019, were included in the aggregated data meta-analysis. The 3- and 5-year OS rates after SBRT were 57% (95% confidence interval [CI], 47%-66%) and 40% (95% CI, 29%-51%), respectively. The 3- and 5-year LC rates after SBRT were 84% (95% CI, 77%-90%) and 82% (95% CI, 74%-88%), respectively. Tumor size was the only prognostic factor for LC. Tumor size and region were significantly associated with OS. Five-year LC and OS rates of 79% (95% CI, 0.74-0.84) and 25% (95% CI, 0.20-0.30), respectively, were observed in the individual patient data analyses. Factors prognostic for improved OS were tumor size <3 cm, Eastern region, Child-Pugh score ≤B7, and the Barcelona Clinic Liver Cancer stage of 0 and A. The incidence of severe hepatic toxicity varied according to the criteria applied. SBRT is an effective treatment modality for patients with HCC with mature follow-up. Clinical practice guidelines were developed on behalf of the International Stereotactic Radiosurgery Society (ISRS).

Role of Necroptosis in Intervertebral Disc Degeneration.

Apoptosis has historically been considered the primary form of programmed cell death (PCD) and is responsible for regulating cellular processes during development, homeostasis, and disease. Conversely, necrosis was considered uncontrolled and unregulated. However, recent evidence has unveiled the significance of necroptosis, a regulated form of necrosis, as an important mechanism of PCD alongside apoptosis. The activation of necroptosis leads to cellular membrane disruption, inflammation, and vascularization. This process is crucial in various pathological conditions, including intervertebral disc degeneration (IVDD), neurodegeneration, inflammatory diseases, multiple cancers, and kidney injury. In recent years, extensive research efforts have shed light on the molecular regulation of the necroptotic pathway. Various stimuli trigger necroptosis, and its regulation involves the activation of specific proteins such as receptor-interacting protein kinase 1 (RIPK1), RIPK3, and the mixed lineage kinase domain-like (MLKL) pseudokinase. Understanding the intricate mechanisms governing necroptosis holds great promise for developing novel therapeutic interventions targeting necroptosis-associated IVDD. The objective of this review is to contribute to the growing body of scientific knowledge in this area by providing a comprehensive overview of necroptosis and its association with IVDD. Ultimately, these understandings will allow the development of innovative drugs that can modulate the necroptotic pathway, offering new therapeutic avenues for individuals suffering from necroptosis.

Use of thermally activated Fenton sludge for Cd removal in zinc smelter wastewater: Mechanism and feasibility of Cd removal.

Fenton sludge is a byproduct of the Fenton process that contains large amounts of Fe and Ca. Because of the secondary contamination generated during the disposal of this byproduct, ecofriendly treatment methods are needed. In this study, we used Fenton sludge to remove the Cd discharged from a zinc smelter factory, using thermal activation to enhance the Cd adsorption capacity. Among the various temperatures considered (300-900 °C), the Fenton sludge that was thermally activated at 900 °C (TA-FS-900) adsorbed the highest amount of Cd because of its high specific surface area and high Fe content. Cd was adsorbed onto TA-FS-900 via complexation with C-OH, C-COOH, FeO-, and FeOH and cation exchange with Ca2+. The maximum adsorption of TA-FS-900 was 260.2 mg/g, indicating that TA-FS-900 is an efficient adsorbent, comparable to those reported in the literature. The initial Cd concentration in the zinc smelter wastewater discharged was 105.7 mg/L, 98.4% of which was removed by applying TA-FS-900, suggesting the applicability of TA-FS-900 for real wastewater containing high concentrations of various cations and anions. The leaching of heavy metals from TA-FS-900 was within the EPA standard limits. We concluded that the environmental impact of Fenton sludge disposal can be reduced, and the use of Fenton sludge can add value to the treatment of industrial wastewater in terms of the circular economy and environment.

6-Methylcoumarin Promotes Melanogenesis through the PKA/CREB, MAPK, AKT/PI3K, and GSK3ß/ß-Catenin Signaling Pathways.

We investigated the effects of four coumarin derivatives, namely, 6-methylcoumarin, 7-methylcoumarin, 4-hydroxy-6-methylcoumarin, and 4-hydroxy-7-methylcoumarin, which have similar structures on melanogenesis in a murine melanoma cell line from a C57BL/6J mouse called B16F10. Our results showed that only 6-methylcoumarin significantly increased the melanin synthesis in a concentration-dependent manner. In addition, the tyrosinase, TRP-1, TRP-2, and MITF protein levels were found to significantly increase in response to 6-methylcoumarin in a concentration-dependent manner. To elucidate the molecular mechanism whereby 6-methylcoumarin-induced melanogenesis influences the melanogenesis-related protein expression and melanogenesis-regulating protein activation, we further assessed the B16F10 cells. The inhibition of the ERK, Akt, and CREB phosphorylation, and conversely, the increased p38, JNK, and PKA phosphorylation activated the melanin synthesis via MITF upregulation, which ultimately led to increased melanin synthesis. Accordingly, 6-methylcoumarin increased the p38, JNK, and PKA phosphorylation in the B16F10 cells, whereas it decreased the phosphorylated ERK, Akt, and CREB expressions. In addition, the 6-methylcoumarin activated GSK3ß and ß-catenin phosphorylation and reduced the ß-catenin protein level. These results suggest that 6-methylcoumarin stimulates melanogenesis through the GSK3ß/ß-catenin signal pathway, thereby affecting the pigmentation process. Finally, we tested the safety of 6-methylcoumarin for topical applications using a primary human skin irritation test on the normal skin of 31 healthy volunteers. We found that 6-methylcoumarin did not cause any adverse effects at concentrations of 125 and 250 µM. Our findings indicate that 6-methylcoumarin may be an effective pigmentation stimulator for use in cosmetics and the medical treatment of photoprotection and hypopigmentation disorders.

Development of an embedded molecular structure-based model for prediction of micropollutant treatability in a drinking water treatment plant by machine learning from three years monitoring data.

In this study, an autoencoder-based molecular structure embedding model was developed to predict treatability of micropollutant in a drinking water treatment plant (DWTP) by machine learning using 69 micropollutants monitoring data at 18 DWTPs for three years. The molecular structure, which contains physicochemical characteristics, was embedded as a fixed-length vector that is advantageous for data-driven analysis and machine learning. First, the molecular structure of the micropollutants was converted to a sequence of tokens using the simplified molecular-input line-entry system (SMILES) pair encoding tokenizer, a frequency-based tokenization method. It was then compressed into fixed-length vectors using an autoencoder trained on various molecular structures within the Chemical Entities of Biological Interest. To validate the proposed models, a binary classification of micropollutant treatability was performed using the embedded molecular structure of micropollutants with various external features, such as concentration, season, and the presence of specific drinking water treatment processes by machine learning. The accuracy of the developed model for the 69 micropollutants in this study was 0.86, and the molecular structure was determined to be the most important feature. Furthermore, an accuracy of 0.71 was obtained in external validation for pharmaceuticals and personal care products that were not used for training. This shows that the proposed embedding vector can be generalized to unseen molecules during the training process, which means that it reflects the characteristics of the molecular structures.

Alkyl chain length of quaternized SBA-15 and solution conditions determine hydrophobic and electrostatic interactions for carbamazepine adsorption.

Santa Barbara Amorphous-15 (SBA) is a stable and mesoporous silica material. Quaternized SBA-15 with alkyl chains (QSBA) exhibits electrostatic attraction for anionic molecules via the N+ moiety of the ammonium group, whereas its alkyl chain length determines its hydrophobic interactions. In this study, QSBA with different alkyl chain lengths were synthesized using the trimethyl, dimethyloctyl, and dimethyoctadecyl groups (C1QSBA, C8QSBA, and C18QSBA, respectively). Carbamazepine (CBZ) is a widely prescribed pharmaceutical compound, but is difficult to remove using conventional water treatments. The CBZ adsorption characteristics of QSBA were examined to determine its adsorption mechanism by changing the alkyl chain length and solution conditions (pH and ionic strength). A longer alkyl chain resulted in slower adsorption (up to 120 min), while the amount of CBZ adsorbed was higher for longer alkyl chains per unit mass of QSBA at equilibrium. The maximum adsorption capacities of C1QSBA, C8QSBA, and C18QSBA, were 3.14, 6.56, and 24.5 mg/g, respectively, as obtained using the Langmuir model. For the tested initial CBZ concentrations (2-100 mg/L), the adsorption capacity increased with increasing alkyl chain length. Because CBZ does not dissociate readily (pKa = 13.9), stable hydrophobic adsorption was observed despite the changes in pH (0.41-0.92, 1.70-2.24, and 7.56-9.10 mg/g for C1QSBA, C8QSBA, and C18QSBA, respectively); the exception was pH 2. Increasing the ionic strength from 0.1 to 100 mM enhanced the adsorption capacity of C18QSBA from 9.27 ± 0.42 to 14.94 ± 0.17 mg/g because the hydrophobic interactions were increased while the electrostatic attraction of the N+ was reduced. Thus, the ionic strength was a stronger control factor determining hydrophobic adsorption of CBZ than the solution pH. Based on the changes in hydrophobicity, which depends on the alkyl chain length, it was possible to enhance CBZ adsorption and investigate the adsorption mechanism in detail. Thus, this study aids the development of adsorbents suitable for pharmaceuticals with controlling molecular structure of QSBA and solution conditions.

Effect of Metal-Precursor Stacking Order on Volume-Defect Formation in CZTSSe Thin Film: Formation Mechanism of Blisters and Nanopores.

In this study, we investigated the effect of the stacking order of metal precursors on the formation of volume defects, such as blisters and nanopores, in CZTSSe thin-film solar cells. We fabricated CZTSSe thin films using three types of metal-precursor combinations, namely, Zn/Cu/Sn/Mo, Cu/Zn/Sn/Mo, and Sn/Cu/Zn/Mo, and studied the blister formation. The blister-formation mechanism was based on the delamination model, taking into consideration the compressive stress and adhesion properties. A compressive stress could be induced during the preferential formation of a ZnSSe shell. Under this stress, the adhesion between the ZnSSe film and the Mo substrate could be maintained by the surface tension of a metallic liquid phase with good wettability, or by the functioning of ZnSSe pillars as anchors, depending on the type of metal precursor used. Additionally, the nanopore formation near the back-contact side was found to be induced by the columnar microstructure of the metal precursor with the Cu/Zn/Mo stacking order and its dezincification. Based on the two volume-defect-formation mechanisms proposed herein, further development of volume-defect-formation suppression technology is expected to be made.

Anti-Inflammatory Effects of Spiramycin in LPS-Activated RAW 264.7 Macrophages.

Drug repurposing is a simple concept with a long history, and is a paradigm shift that can significantly reduce the costs and accelerate the process of bringing a new small-molecule drug into clinical practice. We attempted to uncover a new application of spiramycin, an old medication that was classically prescribed for toxoplasmosis and various other soft-tissue infections; specifically, we initiated a study on the anti-inflammatory capacity of spiramycin. For this purpose, we used murine macrophage RAW 264.7 as a model for this experiment and investigated the anti-inflammatory effects of spiramycin by inhibiting the production of pro-inflammatory mediators and cytokines. In the present study, we demonstrated that spiramycin significantly decreased nitric oxide (NO), interleukin (IL)-1ß, and IL-6 levels in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. Spiramycin also inhibited the expression of NO synthase (iNOS), potentially explaining the spiramycin-induced decrease in NO production. In addition, spiramycin inhibited the phosphorylation of mitogen-activated protein kinases (MAPKs); extracellular signal-regulated kinase (ERK) and c-Jun N terminal kinase (JNK) as well as the inactivation and subsequent nuclear translocation of nuclear factor κB (NF-κB). This indicated that spiramycin attenuates macrophages' secretion of IL-6, IL-1ß, and NO, inducing iNOS expression via the inhibition of the NF-κB and MAPK signaling pathways. Finally, we tested the potential application of spiramycin as a topical material by human skin primary irritation tests. It was performed on the normal skin (upper back) of 31 volunteers to determine whether 100 µM and µM of spiramycin had irritation or sensitization potential. In these assays, spiramycin did not induce any adverse reactions. In conclusion, our results demonstrate that spiramycin can effectively attenuate the activation of macrophages, suggesting that spiramycin could be a potential candidate for drug repositioning as a topical anti-inflammatory agent.

Application of response surface methodology and artificial neural network for the preparation of Fe-loaded biochar for enhanced Cr(VI) adsorption and its physicochemical properties and Cr(VI) adsorption characteristics.

In this study, we optimized and explored the effect of the conditions for synthesizing Fe-loaded food waste biochar (Fe@FWB) for Cr(VI) removal using the response surface methodology (RSM) and artificial neural network (ANN). The pyrolysis time, temperature, and Fe concentration were selected as the independent variables, and the Cr(VI) adsorption capacity of Fe@FWB was maximized. RSM analysis showed that the p-values of pyrolysis temperature and Fe concentration were less than 0.05, indicating that those variables were statically significant, while pyrolysis time was less significant due to its high p-value (0.2830). However, the ANN model results showed that the effect of pyrolysis time was more significant on Cr(VI) adsorption capacity than Fe concentration. The optimal conditions, determined by the RSM analysis with a lower sum of squared error than ANN analysis, were used to synthesize the optimized Fe@FWB (Fe@FWB-OPT) for Cr(VI) removal. From the equilibrium model fitting, the Langmuir model showed a better fit than the Freundlich model, while the Redlich-Peterson isotherm model overlapped. The Cr(VI) sorption capacity of Fe@FWB-OPT calculated from the Langmuir model was 377.71 mg/g, high enough to be competitive to other adsorbents. The kinetic Cr(VI) adsorption was well described by the pseudo-second-order and Elovich models. The XPS results showed that Cr adsorbed on the surface of Fe-FWB-OPT was present not only as Cr(VI) but also as Cr(III) by the reduction of Cr(VI). The results of Cr(VI) adsorption by varying the pH indicate that electrostatic attraction is a key adsorption mechanism.

Phosphorus recovery from cattle manure bottom ash by extraction and precipitation methods.

Phosphorus, a limiting element, is essential for living organisms, but the total amount available is decreasing with its increasing use. This problem can be solved by studying the methods of phosphorus recovery from waste. Phosphorus (P2O5, 13.75%) is abundantly present in cattle manure bottom ash (CMBA), indicating its potential as a source for phosphorus recovery. Herein, phosphorus recovery from CMBA was investigated by acid extraction and precipitation methods. The optimum concentration of sulfuric acid for extraction was 1.4 M, which eluted approximately 90% of the phosphorus contained in CMBA. In the precipitation method, sodium hydroxide and calcium silicate hydrate (CSH, CaSiO3∙nH2O) were used to adjust the solution pH to 4 and 8, where more than 99% of the eluted phosphorus was recovered when the pH was adjusted to 8 using CSH alone. The chemical composition and crystal forms of the recovered precipitates were analyzed using X-ray fluorescence and an X-ray powder diffractometer. The results indicated monetite and brushite were the main crystal forms of precipitates at pH 4, and struvite, hydroxyapatite, and tricalcium phosphate were the main crystal forms at pH 8. The availability of phosphorus in the precipitates was also evaluated by quinoline gravimetric analysis using water and 2% citric acid, and the water-soluble precipitate was less than 35%, whereas it ranged from 65 to 97% in 2% citric acid. This study suggests that CMBA can be used as a promising source to recover phosphorus via acid extraction and precipitation processes.

Chromosome aberration dynamics in breast cancer patients treated with radiotherapy: Implications for radiation biodosimetry.

Although radiological accidents often result in partial-body radiation exposure, most biodosimetry studies focus on estimating whole-body exposure doses. We have evaluated time-dependent changes in chromosomal aberrations before, during, and after localized fractionated radiotherapy. Twelve patients with carcinoma in situ of the breast who underwent identical adjuvant radiation therapy (50 Gy in 25 fractions) were included in the study. Lymphocytes were collected from patients before, during, and after radiotherapy, to measure chromosome aberrations, such as dicentric chromosomes and translocations. Chromosome aberrations were then used to calculate whole- and partial-body biological absorbed doses of radiation. Dicentric chromosome frequencies in all study participants increased during radiotherapy (p < 0.05 in Kruskal-Wallis test). Increases of translocation frequencies during radiotherapy were observed in seven of the twelve patients. The increased levels of dicentric chromosomes and translocations persisted throughout our 1-year follow-up, and evidence of partial-body exposure (such as Papworth's U-value > 1.96) was observed more than 1 year after radiotherapy. We found that cytogenetic biomarkers reflected partial-body fractionated radiation exposure more than 1 year post-exposure. Our findings suggest that chromosome aberrations can be used to estimate biological absorbed radiation doses and can inform medical intervention for individuals suspected of fractionated or partial-body radiation exposure.

Atomic Layer Deposition of Ultrathin ZnO Films for Hybrid Window Layers for Cu(Inx,Ga1-x)Se2 Solar Cells.

The efficiency of thin-film chalcogenide solar cells is dependent on their window layer thickness. However, the application of an ultrathin window layer is difficult because of the limited capability of the deposition process. This paper reports the use of atomic layer deposition (ALD) processes for fabrication of thin window layers for Cu(Inx,Ga1-x)Se2 (CIGS) thin-film solar cells, replacing conventional sputtering techniques. We fabricated a viable ultrathin 12 nm window layer on a CdS buffer layer from the uniform conformal coating provided by ALD. CIGS solar cells with an ALD ZnO window layer exhibited superior photovoltaic performances to those of cells with a sputtered intrinsic ZnO (i-ZnO) window layer. The short-circuit current of the former solar cells improved with the reduction in light loss caused by using a thinner ZnO window layer with a wider band gap. Ultrathin uniform A-ZnO window layers also proved more effective than sputtered i-ZnO layers at improving the open-circuit voltage of the CIGS solar cells, because of the additional buffering effect caused by their semiconducting nature. In addition, because of the precise control of the material structure provided by ALD, CIGS solar cells with A-ZnO window layers exhibited a narrow deviation of photovoltaic properties, advantageous for large-scale mass production purposes.

Anti-Inflammatory Effects of 6-Methylcoumarin in LPS-Stimulated RAW 264.7 Macrophages via Regulation of MAPK and NF-κB Signaling Pathways.

Persistent inflammatory reactions promote mucosal damage and cause dysfunction, such as pain, swelling, seizures, and fever. Therefore, in this study, in order to explore the anti-inflammatory effect of 6-methylcoumarin (6-MC) and suggest its availability, macrophages were stimulated with lipopolysaccharide (LPS) to conduct an in vitro experiment. The effects of 6-MC on the production and levels of pro-inflammatory cytokines (interleukin (IL)-1ß, IL-6, tumor necrosis factor (TNF)-α) and inflammatory mediators (nitric oxide (NO), prostaglandin E2 (PGE2)) in LPS-stimulated RAW 264.7 cells were examined. The results showed that 6-MC reduced the levels of NO and PGE2 without being cytotoxic. In addition, it was demonstrated that the increase in the expression of pro-inflammatory cytokines caused by LPS stimulation, was decreased in a concentration-dependent manner with 6-MC treatment. Moreover, Western blot results showed that the protein levels of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), which increased with LPS treatment, were decreased by 6-MC treatment. Mechanistic studies revealed that 6-MC reduced the phosphorylation of the mitogen-activated protein kinase (MAPK) family and IκBα in the MAPK and nuclear factor-kappa B (NF-κB) pathways, respectively. These results suggest that 6-MC is a potential therapeutic agent for inflammatory diseases that inhibits inflammation via the MAPK and NF-κB pathways.

Bisphenol A degradation using waste antivirus copper film with enhanced sono-Fenton-like catalytic oxidation.

This study investigated the applicability of waste antivirus copper film (CF) as a Fenton-like catalyst. The reaction activity of H2O2 and CF in combination was significantly enhanced by ultrasound (US) irradiation, and the synergy factor calculated from bisphenol A (BPA) degradation using CF-H2O2-US was 9.64 compare to that of dual factors. Photoluminescence analyses were conducted to compare the generation of hydroxyl radicals during both processes. In this sono-Fenton-like process, BPA degradation was affected by solution pH, temperature, ultrasound power, CF size, H2O2 dose, and initial BPA concentration. The BPA degradation curves showed an induction period (first stage) and a rapid degradation period (second stage). Process efficiency was totally and partially enhanced in the presence of chloride and carbonate ions, respectively. Chemical scavenger tests showed that both free and surface-bound hydroxyl radicals participate in BPA degradation under the sono-Fenton-like process using CF. The functional groups and copper crystals on the CF surface remained unchanged after five consecutive reuses, and the BPA degradation efficiency of CF was maintained over 80% during the reuse processes as a sono-Fenton-like catalyst.

As(III) adsorption onto Fe-impregnated food waste biochar: experimental investigation, modeling, and optimization using response surface methodology.

Biochar derived from food waste was modified with Fe to enhance its adsorption capacity for As(III), which is the most toxic form of As. The synthesis of Fe-impregnated food waste biochar (Fe-FWB) was optimized using response surface methodology (RSM), and the pyrolysis time (1.0, 2.5, and 4.0 h), temperature (300, 450, and 600 °C), and Fe concentration (0.1, 0.3, and 0.5 M) were set as independent variables. The pyrolysis temperature and Fe concentration significantly influenced the As(III) removal, but the effect of pyrolysis time was insignificant. The optimum conditions for the synthesis of Fe-FWB were 1 h and 300 °C with a 0.42-M Fe concentration. Both physical and chemical properties of the optimized Fe-FWB were studied. They were also used for kinetic, equilibrium, thermodynamic, pH, and competing anion studies. Kinetic adsorption experiments demonstrated that the pseudo-second-order model had a superior fit for As(III) adsorption than the pseudo-first-order model. The maximum adsorption capacity derived from the Langmuir model was 119.5 mg/g, which surpassed that of other adsorbents published in the literature. Maximum As(III) adsorption occurred at an elevated pH in the range from 3 to 11 owing to the presence of As(III) as H2AsO3- above a pH of 9.2. A slight reduction in As(III) adsorption was observed in the existence of bicarbonate, hydrogen phosphate, nitrate, and sulfate even at a high concentration of 10 mM. This study demonstrates that aqueous solutions can be treated using Fe-FWB, which is an affordable and readily available resource for As(III) removal.

Thermally treated Mytilus coruscus shells for fluoride removal and their adsorption mechanism.

We evaluated Mytilus coruscus shells (MCS) as an adsorbent for fluoride removal. Its removal efficiency was enhanced by thermal treatment and MCS at 800 °C (MCS-800) increased significantly its fluoride adsorption capacity from 0 to 12.28 mg/g. While raw MCS is mainly composed of calcium carbonate (CaCO3), MCS-800 consisted of 56.9% of CaCO3 and 43.1% of calcium hydroxide (Ca(OH)2). The superior adsorption capacity of MCS-800 compared to untreated MCS can be also explained by its larger specific surface area and less negative charge after the thermal treatment. X-ray photoelectron spectroscopy and X-ray diffraction analysis revealed that the fluoride adsorption of MCS-800 occurred via the formation of calcium fluorite (CaF2). Fluoride adsorption of MCS-800 approached equilibrium within 6 h and this kinetic adsorption was well-described by a pseudo-second-order model. The Langmuir model was suitable for describing the fluoride adsorption of MCS-800 under different initial concentrations. The maximum fluoride adsorption amount of MCS-800 was 82.93 mg/g, which was superior to those of other adsorbents derived from industrial byproducts. The enthalpy change of fluoride adsorption was 78.75 kJ/mol and the negative sign of free energy indicated that this phenomenon was spontaneous. The increase of pH from 3.0 to 11.0 slightly decreased the fluoride adsorption capacity of MCS-800. The adsorption was inhibited in the presence of anions and their impact increased with following trend: chloride < sulfate < carbonate < phosphate. The fluoride adsorption capacities of MCS-800 after washing with deionized water and 0.1 M NaOH were reduced by 31.5% and 57.4%, respectively.

Metal-organic framework MIL-100(Fe) for dye removal in aqueous solutions: Prediction by artificial neural network and response surface methodology modeling.

In this study, a metal organic framework MIL-100(Fe) was synthesized for rhodamine B (RB) removal from aqueous solutions. An experimental design was conducted using a central composite design (CCD) method to obtain the RB adsorption data (n = 30) from batch experiments. In the CCD approach, solution pH, adsorbent dose, and initial RB concentration were included as input variables, whereas RB removal rate was employed as an output variable. Response surface methodology (RSM) and artificial neural network (ANN) modeling were performed using the adsorption data. In RSM modeling, the cubic regression model was developed, which was adequate to describe the RB adsorption according to analysis of variance. Meanwhile, the ANN model with the topology of 3:8:1 (three input variables, eight neurons in one hidden layer, and one output variable) was developed. In order to further compare the performance between the RSM and ANN models, additional adsorption data (n = 8) were produced under experimental conditions, which were randomly selected in the range of the input variables employed in the CCD matrix. The analysis showed that the ANN model (R2 = 0.821) had better predictability than the RSM model (R2 = 0.733) for the RB removal rate. Based on the ANN model, the optimum RB removal rate (>99.9%) was predicted at pH 5.3, adsorbent dose 2.0 g L-1, and initial RB concentration 73 mg L-1. In addition, pH was determined to be the most important input variable affecting the RB removal rate. This study demonstrated that the ANN model could be successfully employed to model and optimize RB adsorption to the MIL-100(Fe).

Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning-Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation.

BACKGROUND: The early diagnosis of various gastrointestinal diseases can lead to effective treatment and reduce the risk of many life-threatening conditions. Unfortunately, various small gastrointestinal lesions are undetectable during early-stage examination by medical experts. In previous studies, various deep learning-based computer-aided diagnosis tools have been used to make a significant contribution to the effective diagnosis and treatment of gastrointestinal diseases. However, most of these methods were designed to detect a limited number of gastrointestinal diseases, such as polyps, tumors, or cancers, in a specific part of the human gastrointestinal tract. OBJECTIVE: This study aimed to develop a comprehensive computer-aided diagnosis tool to assist medical experts in diagnosing various types of gastrointestinal diseases. METHODS: Our proposed framework comprises a deep learning-based classification network followed by a retrieval method. In the first step, the classification network predicts the disease type for the current medical condition. Then, the retrieval part of the framework shows the relevant cases (endoscopic images) from the previous database. These past cases help the medical expert validate the current computer prediction subjectively, which ultimately results in better diagnosis and treatment. RESULTS: All the experiments were performed using 2 endoscopic data sets with a total of 52,471 frames and 37 different classes. The optimal performances obtained by our proposed method in accuracy, F1 score, mean average precision, and mean average recall were 96.19%, 96.99%, 98.18%, and 95.86%, respectively. The overall performance of our proposed diagnostic framework substantially outperformed state-of-the-art methods. CONCLUSIONS: This study provides a comprehensive computer-aided diagnosis framework for identifying various types of gastrointestinal diseases. The results show the superiority of our proposed method over various other recent methods and illustrate its potential for clinical diagnosis and treatment. Our proposed network can be applicable to other classification domains in medical imaging, such as computed tomography scans, magnetic resonance imaging, and ultrasound sequences.