Green whitening of polyester fabric using fluorescent brightener OB-1 in a mixture of water and decamethylcyclopentasiloxane media.

Fluorescent brightening agent OB-1 (OB-1) is often used in plastic goods because of its non-toxic nature, chemical stability, remarkable heat resistance, and light stability. Raw OB-1 is challenging to use in textiles using the exhaustion method. This study used a novel method using raw OB-1 powder to whiten polyester fabric in water and decamethylcyclopentasiloxane (D5). The Taguchi approach investigated the interaction between whitening process parameters such as temperature, OB-1 mass, water: D5 ratio, and treatment time with four levels. The study shows that the temperature and water: D5 ratio during the whitening process significantly affect the whiteness of polyester fabric (P < 0.05), with contribution percentages of 74.2 % and 25.2 %. Subsequently, various analytical techniques were employed, including FTIR, SEM, TGA, and XRD, to characterise the whitened fabric. The findings imply that using water: D5 medium was effective in whitening polyester fabric without causing major alterations to the structure of the PET fabric. The study also examined the fastness of washing and crocking to determine their whitening stability. Overall, polyester fabric whitened with water and D5 medium exhibited satisfactory whitening performance and might be a potential scope for use on a larger scale in developing the sustainable textile industry.

Prediction of g-C3N4-based photocatalysts in tetracycline degradation based on machine learning.

Investigating the effects of g-C3N4-based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learning methods can avoid the problems of high cost, time-consuming and possible instrumental errors in experimental methods, which have been proven to be an effective alternative for evaluating the entire experimental process. Eight typical machine learning models were explored for their effectiveness in predicting the TC degradation efficiencies of g-C3N4 based photocatalysts. XGBoost (XGB) was the most reliable model with R2, RMSE and MAE values of 0.985, 4.167 and 2.900, respectively. In addition, XGB's feature importance and SHAP method were used to rank the importance of features to provide interpretability to the results. This study provided a new idea for developing g-C3N4-based photocatalysts for TC degradation and intelligent algorithms for predicting the photocatalytic activity of g-C3N4-based photocatalysts.

Hydrolytic nanozymes: Preparation, properties, and applications.

Hydrolytic nanozymes, as promising alternatives to hydrolytic enzymes, can efficiently catalyze the hydrolysis reactions and overcome the operating window limitations of natural enzymes. Moreover, they exhibit several merits such as relatively low cost, easier recovery and reuse, improved operating stability, and adjustable catalytic properties. Consequently, they have found relevance in practical applications such as organic synthesis, chemical weapon degradation, and biosensing. In this review, we highlight recent works addressing the broad topic of the development of hydrolytic nanozymes. We review the preparation, properties, and applications of six types of hydrolytic nanozymes, including AuNP-based nanozymes, polymeric nanozymes, surfactant assemblies, peptide assemblies, metal and metal oxide nanoparticles, and MOFs. Last, we discuss the remaining challenges and future directions. This review will stimulate the development and application of hydrolytic nanozymes.

Optimization and prediction of the cotton fabric dyeing process using Taguchi design-integrated machine learning approach.

The typical textile dyeing process calls for a wide range of operational parameters, and it has always been difficult to pinpoint which of these qualities is the most important in dyeing performance. Consequently, this research used a combined design of experiments and machine learning prediction models' method to offer a sustainable and beneficial reactive cotton fabric dyeing process. To be more precise, we built a least square support vector regression (LSSVR) model based on Taguchi's statistical orthogonal design (L27) to predict exhaustion percentage (E%), fixation rate (F%), and total fixation efficiency (T%) and color strength (K/S) in the reactive cotton dyeing process. The model's prediction accuracy was assessed using many measures, including root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Principal component regression (PCR), partial least square regression (PLSR), and fuzzy modelling were some of the other types of regression models used to compare results. Our findings reveal that the LSSVR model greatly outperformed competing models in predicting the E%, F%, T%, and K/S. This is shown by the LSSVR model's much smaller RMSE and MAE values. Overall, it provided the highest possible R2 values, which reached 0.9819.

Enhancement of peroxymonosulfate activation by humic acid-modified sludge biochar: Role of singlet oxygen and electron transfer pathway.

Sludge biochar (SBC) modified by humic acid (HA) was used to activate peroxymonosulfate (PMS) for degrading naproxen (NPX). HA-modified biochar (SBC-50HA) boosted the catalytic performance of SBC for PMS activation. The SBC-50HA/PMS system had good reusability and structural stability, and was unaffected by complex water bodies. The results of Fourier transform infrared (FTIR) and X-ray diffraction spectroscopy (XPS) indicated that graphitic carbon (CC), graphitic N, and C-O on SBC-50HA played a vital part on the removal of NPX. The key role of non-radical pathways such as singlet oxygen (1O2) and electron transfer in the SBC-50HA/PMS/NPX system was verified by inhibition experiments, electron paramagnetic resonance (EPR), electrochemistry, and PMS consumption. The possible degradation pathway of NPX was proposed by density functional theory (DFT) calculations, and the toxicity of NPX and its degradation intermediates were evaluated.

Sustainable fashion: Design of the experiment assisted machine learning for the environmental-friendly resin finishing of cotton fabric.

Given the carcinogenic properties of formaldehyde-based chemicals, an alternative method for resin-finishing cotton textiles is urgently needed. Therefore, the primary objective of this study is to introduce a sustainable resin-finishing process for cotton fabric via an industrial procedure. For this purpose, Bluesign® approved a formaldehyde-free Knittex RCT® resin was used, and the process parameters were designed and optimized according to the Taguchi L27 method. XRD analysis confirmed the crosslinking formation between resin and neighboring molecules of cotton fabric, as no change in the cellulose crystallization phase. Several machine learning models were built in a sequence to predict the crease recovery angle (CRA), tearing strength (TE) and whiteness index (WI). Assessment of modelling was evaluated through the use of various metrics such as root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results were compared to those from other regression models, such as principal component regression (PCR), partial least squares regression (PLSR), and fuzzy modelling. Based on the results of our research, the LSSVR model predicted the CRA, TE, and WI with substantially more accuracy than other models, as shown by the fact that its RMSE and MAE values were significantly lower. In addition, it offered the greatest possible R2 values, reaching up to 0.9627.

The Formation Mechanism Investigations of Nano-Tungsten Carbide Powder.

Formation mechanism of synthesizing nanoparticle tungsten carbide (WC) was studied. WC was synthesized by carbothermal hydrogen reduction (CHR) method under various reaction temperatures for holding different post-treatment time in 20% (v/v) CH4/H2. The phase transformation mechanism of gaining WC was investigated, by combining CHR with X-ray diffraction (XRD) and temperature programmed reduction mass spectroscopy (TPR-MS). The results show that pure phase of WC has been obtained by CHR after isothermal heat treatment for 24 hours at 750 °C and 12 hours at 950 °C, respectively. These results indicated that two key parameters of higher temperature and longer isothermal heat treatment time are necessary for synthesizing pure phase of WC powder. In order to find out the phase transformation mechanism of tungsten trioxide (WO3) to WC, the reduction and carburization process among the temperature range from 600 °C to 1000 °C for holding 3 hours at the final temperature were studied. It was shown that at 600 °C, WO3 was reduced to WO2, and from 600 °C to 750 °C, WO2 was reduced to metallic tungsten (W). Moreover, at the temperature range from 750 °C to 900 °C, the mixture phases of tungsten carbide (WC), metallic tungsten (W), or/and tungsten sub-carbide (W2C) were formed without any oxides species, which indicated that tungsten carbides (WC and W2C) phases appeared because the oxides phase was thoroughly reduced. However, the occurrence of carburization process was still limited due to the presence of oxygen in the solid. Because of the formed CO and CO2 there was not enough activated methane reacting with metallic tungsten, so the phase of WC and W2C were both formed simultaneously, but the reaction of forming WC was the main reaction in the whole carburization process. Moreover, the TPR-MS and XRD results indicated that, WC was formed at lower temperature (750 °C) by the reduced metallic W, which was produced form W2C in the gas mixture for holding a long time, while at a higher temperature (950 °C), WC was formed form W2C with the mixture gas directly.

Curvilinearity of a Maximum Expiratory Flow-Volume Curve: A Useful Indicator for Assessing Airway Obstruction in Children With Asthma.

BACKGROUND: Lung function parameters are used as signs in the diagnosis and evaluation of asthma; however, their sensitivity and specificity are not ideal. We calculated and combined angle ß with lung function parameters to identify the ideal indicator. OBJECTIVE: We aimed to identify an ideal indicator for evaluating the severity of airway obstruction in children with asthma. METHODS: In total, 151 school-age children diagnosed with asthma were selected as the asthma group, and 106 healthy children were selected as the control group. The subjects were divided into the exacerbation group, chronic persistent group, and clinical remission group. Furthermore, the subjects were classified into mild and moderate groups or severe and critical groups. Angle ß was calculated in each group. A receiver operating characteristic curve analysis was performed to determine the cutoff values of angle ß and lung function parameters that together provided high sensitivity and specificity for airway obstruction evaluation in children with asthma. RESULTS: The mean value of angle ß in the asthma group was significantly smaller than that in the control group (178.18° and 196.72°, respectively, P < .001). More exacerbations or greater severity corresponded to smaller angle ß values (P < .001). The best cutoff value of angle ß was 189.43°, and the area under the receiver operating characteristic curve of angle ß was 0.877, which is greater than the area under the receiver operating characteristic curve of FEV1, forced expiratory flow (FEF) at 75% vital capacity (FEF25%), and FEF at 50% vital capacity (FEF50%), but smaller than the area under the receiver operating characteristic curve of FEF75% and FEV1/FVC%. Interestingly, combining these measures can enhance the sensitivity and specificity in assessing airway obstruction. CONCLUSIONS: Angle ß was a useful indicator for assessing airway obstruction. Furthermore, angle ß combined with FEV1, FEV1/FVC%, FEF25%, FEF50%, and FEF75% can enhance the sensitivity and specificity of airway obstruction evaluations.

Myeloid-derived suppressor cells (MDSCs) and mechanistic target of rapamycin (mTOR) signaling pathway interact through inducible nitric oxide synthase (iNOS) and nitric oxide (NO) in asthma.

BACKGROUND: Down-regulation of mechanistic target of rapamycin (mTOR) activity in myeloid-derived suppressor cells (MDSCs) has been shown to promote inducible nitric oxide (NO) synthase (iNOS) expression and NO production. Importantly, pharmacological inhibition of iNOS blocks MDSCs recruitment in immunological hepatic injury. As bronchial asthma is also an immune disease, whether mTOR could interact with MDSCs via iNOS and NO or not is unclear. OBJECTIVE: The aim of this study was to determine whether mTOR could interact with MDSCs via iNOS and NO in asthma. METHODS: Ovalbumin-induced asthma mouse model was established to perform our investigation, and asthmatic markers were evaluated by hematoxylin and eosin (H&E), immunohistochemistry (IHC), and periodic acid-Schiff (PAS) staining. The levels of iNOS and NO in serum were determined by enzyme linked immunosorbent assay (ELISA). Mice lung tissues were stained with antibodies against phosphorylated (p)-mTOR, and p-p70S6K, and yellow/brown staining was considered as giving a positive signal, meanwhile, the protein levels of p-mTOR, and p-p70S6K were also detected using western blot assay. Mice iNOS activity was determined by radioimmunoassay. RESULTS: Tumor-derived MDSCs in asthmatic mice were regulated by mTOR and iNOS. mTOR pathway activation in asthmatic mice was regulated by iNOS and tumor-derived MDSCs. NO production in asthmatic mice was regulated by mTOR and tumor-extracted MDSCs. Positive correlation of iNOS with mTOR pathway and serum MDSCs was observed. CONCLUSION: The data indicated that rapamycin, an inhibitor of mTOR, blocked iNOS and NO production during asthma onset. Thus, our results revealed potential novel targets for asthma therapy.

Tumor-derived MDSCs inhibit airway remodeling in asthmatic mice through regulating IL-10 and IL-12.

Myeloid-derived suppressor cells (MDSCs), a group of newly discovered and heterogeneous myeloid-derived immunosuppressive cells, play an important role in the progress of asthma, however, the specific mechanism is still largely unclear. Our previous study has indicated that during the onset of asthma, the accumulation of MDSCs and the level of serum interleukin (IL)-10 increased, while the level of IL-12 decreased. The present study aimed to investigate whether tumor-derived MDSCs could inhibit airway remodeling in asthmatic mice through regulating IL-10 and IL-12 secretion. To perform our investigation, we established a mouse model of breast cancer, and the extracted MDSCs from breast caner mouse model were injected into a mouse model of asthma induced by ovalbumin (OVA). Then, asthmatic airway remodeling of mice was analyzed and the levels of IL-10 and IL-12 in the serum and bronchoalveolar lavage fluid (BALF) of mice were detected. In addition, the correlation of MDSCs with the levels of IL-10 and IL-12 in the transplantation group was analyzed. The transplantation of tumor-derived MDSCs into asthmatic mice significantly improved airway remodeling, decreased MDSCs and the expression of IL-10, and significantly increased the expression of IL-12. Besides, we confirmed that IL-10 was positively correlated with MDSCs, while IL-12 was negatively correlated with MDSCs. The results indicated that tumor-derived MDSCs could reduce IL-10 level, increase the level of IL-12, and thus correct the Th1/Th2 imbalance in asthmatic mice. In summary, our results revealed that tumor-derived MDSCs could serve as a potential novel target for asthma therapy.

Materials specificity and directed assembly of a gold-binding peptide.

Adsorption studies of a genetically engineered gold-binding peptide, GBP1, were carried out using a quartz-crystal microbalance (QCM) to quantify its molecular affinity to noble metals. The peptide showed higher adsorption onto and lower desorption from a gold surface compared to a platinum substrate. The material specificity, that is, the preferential adsorption, of GBP1 was also demonstrated using gold and platinum micropatterned on a silicon wafer containing native oxide. The biotinylated three-repeat units of GBP1 were preferentially adsorbed onto gold regions delineated using streptavidin-conjugated quantum dots (SAQDs). These experiments not only demonstrate that an inorganic-binding peptide could preferentially adsorb onto a metal (Au) rather than an oxide (SiO2) but also onto one noble metal (Au) over another (Pt). This result shows the utility of an engineered peptide as a molecular erector in the directed immobilization of a nanoscale hybrid entity (SAQDs) over selected regions (Au) on a fairly complex substrate (Au and Pt micropatterned regions on silica). The selective and controlled adsorption of inorganic-binding peptides may have significant implications in nano- and nanobiotechnology, where they could be genetically tailored for specific use in the development of self-assembled molecular systems.