Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models.

Knowing odor sensory attributes of odorants lies at the core of odor tracking when addressing waterborne odor issues. However, experimental determination covering tens of thousands of odorants in authentic water is not pragmatic due to the complexity of odorant identification and odor evaluation. In this study, we propose the first machine learning (ML) model to predict odor perception/threshold aiming at odorants in water, which can use either molecular structure or MS2 spectra as input features. We demonstrate that model performance using MS2 spectra is nearly as good as that using unequivocal structures, both with outstanding accuracy. We particularly show the model's robustness in predicting odor sensory attributes of unidentified chemicals by using the experimentally obtained MS2 spectra from nontarget analysis on authentic water samples. Interpreting the developed models, we identify the intricate interaction of functional groups as the predominant influence factor on odor sensory attributes. We also highlight the important roles of carbon chain length, molecular weight, etc., in the inherent olfactory mechanisms. These findings streamline the odor sensory attribute prediction and are crucial advancements toward credible tracking and efficient control of off-odors in water.

CpCAF1 from Chimonanthus praecox Promotes Flowering and Low-Temperature Tolerance When Expressed in Arabidopsis thaliana.

CCR4-associated factor I (CAF1) is a deadenylase that plays a critical role in the initial step of mRNA degradation in most eukaryotic cells, and in plant growth and development. Knowledge of CAF1 proteins in woody plants remains limited. Wintersweet (Chimonanthus praecox) is a highly ornamental woody plant. In this study, CpCAF1 was isolated from wintersweet. CpCAF1 belongs to the DEDDh (Asp-Glu-Asp-Asp-His) subfamily of the DEDD (Asp-Glu-Asp-Asp) nuclease family. The amino acid sequence showed highest similarity to the homologous gene of Arabidopsis thaliana. In transgenic Arabidopsis overexpressing CpCAF1, the timing of bolting, formation of the first rosette, and other growth stages were earlier than those of the wild-type plants. Root, lateral branch, rosette leaf, and silique growth were positively correlated with CpCAF1 expression. FLOWERING LOCUS T (FT) and SUPPRESSOROF OVEREXPRESSION OF CO 1 (SOC1) gene expression was higher while EARLY FLOWERING3 (ELF3) and FLOWERING LOCUS C (FLC) gene expression of transgenic Arabidopsis was lower than the wild type grown for 4 weeks. Plant growth and flowering occurrences were earlier in transgenic Arabidopsis overexpressing CpCAF1 than in the wild-type plants. The abundance of the CpCAF1 transcript grew steadily, and significantly exceeded the initial level under 4 °C in wintersweet after initially decreasing. After low-temperature exposure, transgenic Arabidopsis had higher proline content and stronger superoxide dismutase activity than the wild type, and the malondialdehyde level in transgenic Arabidopsis was decreased significantly by 12 h and then increased in low temperature, whereas it was directly increased in the wild type. A higher potassium ion flux in the root was detected in transgenic plants than in the wild type with potassium deficiency. The CpCAF1 promoter was a constitutive promoter that contained multiple cis-acting regulatory elements. The DRE, LTR, and MYB elements, which play important roles in response to low temperature, were identified in the CpCAF1 promoter. These findings indicate that CpCAF1 is involved in flowering and low-temperature tolerance in wintersweet, and provide a basis for future genetic and breeding research on wintersweet.

Insight into the mechanisms of trichloronitromethane formation by vacuum ultraviolet: QSAR model and FTICR-MS analysis.

Vacuum ultraviolet (VUV) photolysis is recognized as an environmental-friendly treatment process. Nitrate (NO3-) and natural organic matter (NOM) are widely present in water source. We investigated trichloronitromethane (TCNM) formation during chlorination after VUV photolysis, because TCNM is an unregulated highly toxic disinfection byproduct. In this study: (1) we found reactive nitrogen species that is generated under VUV photolysis of NO3- react with organic matter to form nitrogen-containing compounds and subsequently form TCNM during chlorination; (2) we found the mere presence of 0.1 mmol/L NO3- can result in the formation of up to 63.96 µg/L TCNM; (3) we found the changes in pH (6.0-8.0), chloride (1-4 mmol/L), and bicarbonate (1-4 mmol/L) cannot effectively diminish TCNM formation; and, (4) we established the quantitative structure-activity relationship (QSAR) model, which indicated a linear relationship between TCNM formation and the Hammett constant (σ) of model compounds; and, (5) we characterized TCNM precursors in water matrix after VUV photolysis and found 1161 much more nitrogen-containing compounds with higher aromaticity were generated. Overall, this study indicates more attention should be paid to reducing the formation risk of TCNM when applying VUV photolysis process at scale.

Impact of pre-oxidation on the formation of byproducts in algae-laden water disinfection: Insights from fluorescent and molecular weight.

Pre-oxidation has been reported to be an effective way to remove algal cells in water, but the released algal organic matter (AOM) could be oxidized and lead to the increment in disinfection by-product (DBP) formation. The relationship between pre-oxidation and AOM-derived DBP formation needs to be approached more precisely. This study compared the impact of four pre-oxidants, ozone (O3), chlorine dioxide (ClO2), potassium permanganate (KMnO4) and sodium hypochlorite (NaClO), on the formation of nitrogenous (N-) and carbonaceous (C-) DBPs in AOM chlorination. The characterization (fluorescent properties, molecular weight distribution and amino acids concentration) on AOM samples showed that the characterization properties variations after pre-oxidation were highly dependent on the oxidizing ability of oxidants. The disinfection experiments showed that O3 increased DBP formation most significantly, which was consistent with the result of characterization properties variations. Then canonical correspondent analysis (CCA) and Pearson's correlation analysis were conducted based on the characterization data and DBP formation. CCA indicated that C-DBPs formation was highly dependent on fluorescent data. The formation of haloacetic acids (HAAs) had a positive correlation with aromatic protein-like component while trichloromethane (TCM) had a positive correlation with fulvic acid-like component. Pearson's correlation analysis showed that low molecular weight fractions were favorable to form N-DBPs. Therefore, characterization data could provide the advantages in the control of DBP formation, which further revealed that KMnO4 and ClO2 were better options for removing algal cells as well as limiting DBP formation.

Computerized Pathway Generator for the UV/Free Chlorine Process: Prediction of Byproducts and Reactions.

The ultraviolet (UV)/free chlorine process is a very promising treatment technology to remove persistent organic contaminants (POCs, e.g., pharmaceutical and personal care products) from water. The radical chain reactions involved in the UV/free chlorine process are very complicated, and the reaction pathways for organic contaminants degradation are largely unknown. Therefore, we developed a computerized pathway generator that uses graph theory and experimentally determined reaction rules that were reported for the UV/free chlorine process. Our pathway generator predicts all possible intermediates, byproducts, and elementary reactions that are involved in the oxidation of organic contaminants. For example, the degradation of tricholoroethylene (TCE) produces 497 species (i.e., intermediates and byproducts) and 6608 elementary reactions. The predicted species from our pathway generator not only predict the major and stable byproducts that were observed in our experiments (e.g., CHCl2COOH, CHCl(OCl)COOH, etc.) but also include many other minor and toxic byproducts that were produced but not measured because they have a short lifetime. Overall, our pathway generator significantly improves our understanding of the reaction pathways that are involved in organic contaminant degradation in the UV/free chlorine process.

Computed Tomography-Guided Trans-scapular Coil Localization for Pulmonary Nodules.

BACKGROUND: The aim of the study is to evaluate the feasibility, safety, and effectiveness of preoperative computed tomography (CT)-guided trans-scapular coil localization (TSCL) of scapula-blocked pulmonary nodules (PNs). METHODS: Between November 2015 and May 2020, 11 patients underwent preoperative CT-guided TSCL procedures owing to PN occlusion by scapula. RESULTS: A 100% technical success rate was achieved for CT-guided TSCL, with one coil being used for each PN. One patient (9.1%) developed pneumothorax. Successful video-assisted thoracoscopic surgery (VATS)-guided wedge resection of these scapula-blocked PNs was conducted in all patients. CONCLUSION: CT-guided TSCL can be simply and safely used to facilitate successful VATS-guided wedge resection of scapula-blocked PNs.

Formation, speciation and toxicity of CX3R-type disinfection by-products (DBPs) from chlor(am)ination of 2,4-diaminobutyric acid (DAB).

2,4-diaminobutyric acid (DAB), a newly identified algal toxins in water, pose a great threat to human health. DAB may react with chlorine or chloramine to produce CX3R-type disinfection by-products (DBPs) during water treatment processes. This study mainly investigated the formation and speciation of DBPs from chlor(am)ination of DAB. The results revealed that haloacetic acids (HAAs), trihalomethanes (THMs) and haloacetonitriles (HANs) were the main kinds of CX3R-type DBPs generated from DAB during chlor(am)ination, of which dichloroacetic acid yielded the highest. The formation and total toxicity of four CX3R-type DBPs from DAB during chloramination was significantly lower than that during chlorination at each Cl2:N molar ratio. However, more formation of Br-THMs and I-THMs were observed during chloramination in the presence of Br-/I-. Futhermore, the effects of chlor(am)ine dosage, solution pH, reaction time, and the concentration of Br- and I- on the formation and speciation of CX3R-type DBPs were also evaluated during chlor(am)ination. The plausible formation pathways of CX3R-type DBPs from DAB were proposed and verified by theoretical calculation. The quantum chemistry calculations indicate that 1N in DAB and 8N in 2,4-diaminochlorobutyric acid (C4H9O2N2Cl) were more likely to be attacked by electrophiles, supporting the proposed pathway schemes.

Oxidation Mechanisms of the UV/Free Chlorine Process: Kinetic Modeling and Quantitative Structure Activity Relationships.

Recently, the UV/free chlorine process has gained attention as a promising technology for destroying refractory organic contaminants in the aqueous phase. We have developed a kinetic model based on first-principles to describe the kinetics and mechanisms of the oxidation of organic contaminants in the UV/free chlorine process. Substituted benzoic acid compounds (SBACs) were chosen as the target parent contaminants. We determined the second-order rate constants between SBACs and reactive chlorine species (RCS; including [Formula: see text], [Formula: see text] and [Formula: see text]) by fitting our model to the experimental results. We then predicted the concentration profiles of SBACs under various operational conditions. We analyzed the kinetic data and predicted concentration profiles of reactive radicals ([Formula: see text] and RCS), we found that [Formula: see text] was the dominant radicals for SBACs destruction. In addition, we established quantitative structure activity relationships (QSARs) that can help predict the second-order rate constants for SBACs destruction by each type of reactive radicals using SBACs Hammett constants. Our first-principles-based kinetic model has been verified using experimental data. Our model can facilitate a design for the most cost-effective application of the UV/free chlorine process. For example, our model can determine the optimum chlorine dosage and UV light intensity that result in the lowest energy consumption.

Development of a Three-Dimensional Electrochemical System Using a Blue TiO2/SnO2-Sb2O3 Anode for Treating Low-Ionic-Strength Wastewater.

Reducing energy use is crucial to commercialize electrochemical oxidation technologies. We developed a three-dimensional (3-D) electrochemical system that can significantly reduce the applied voltage and effectively degrade organic contaminants in low-ionic-strength wastewaters. The 3-D system consisted of a composite wire mesh anode (composed of blue TiO2 nanotubes covered with SnO2-Sb2O3), a proton exchange membrane, and a stainless-steel wire mesh cathode, which were compressed firmly together. For the 3-D system, we placed the anode of a 3-D electrode toward the wastewater that flowed past the anode. Both the two-dimensional (2-D) and 3-D systems had the same anode and cathode. We found that the 3-D system could reduce the applied voltage by 75.7% and reduce the electrical efficiency per log order reduction (EE/O) by 73% for 0.001 M Na2SO4. For Na2SO4 concentrations greater than 0.05 M, the 2-D system had a slightly lower EE/O. We also compared the EE/O of electrochemical advanced oxidation processes (EAOPs) with that of other advanced oxidation processes (UV/H2O2, UV/persulfate, O3/H2O2, UV/ TiO2, and UV/chlorine). We found that EAOPs have a much higher EE/O for low BA concentrations (20 mg/L) and a much lower EE/O for high BA concentrations (2000 mg/L).

Oxidation of Microcystic-LR via the solar/chlorine process: Radical mechanism, pathways and toxicity assessment.

Microcystin-LR (MC-LR) is the most widely distributed and harmful variant toxins released by cyanobacteria, which poses potential threaten to people and aquatic animals when entering natural water. In our research, solar/chlorine process was comprehensively investigated to degrade and detoxify MC-LR. Under the chlorine concentration of 1.0 mg L-1, MC-LR (1.0 µM) was decreased by 96.7%, 26%, and 9% by solar/chlorine process, chlorination, and solar irradiation respectively. Quenching experiments confirmed that reactive chlorine species (RCS) and hydroxyl radical (HO) were the predominant reactive species in solar/chlorine process at neutral condition, and ozone was generated because of the participation of triplet-state oxygen (O(3P)). The respective contributions of each reactive species were calculated with the order as: RCS, HO, ozone, and solar irradiation. The presence of HCO3- and natural organic matter in water inhibited the degradation efficiency of MC-LR. Moreover, the transformation products of MC-LR generated during the solar/chlorine process were identified and a possible pathway was proposed. The hepatotoxicity of MC-LR and its transformation products was compared using protein phosphatase 2A. Our experimental results revealed that the concentration and hepatotoxicity of MC-LR both significantly decreased, and most products were not hepatoxic. Overall, the solar/chlorine process is a promising alternative technology to degrade MC-LR during eutrophication.

Impact of Chloride Ions on UV/H2O2 and UV/Persulfate Advanced Oxidation Processes.

Chloride ion (Cl-) is one of the most common anions in the aqueous environment. A mathematical model was developed to determine and quantify the impact of Cl- on the oxidization rate of organic compounds at the beginning stage of the UV/persulfate (PS) and UV/H2O2 processes. We examined two cases for the UV/PS process: (1) when the target organic compounds react only with sulfate radicals, the ratio of the destruction rate of the target organic compound when Cl- is present to the rate when Cl- is not present (designated as rRCl-/ rR) is no larger than 1.942%; and (2) when the target organic compounds can react with sulfate radicals, hydroxyl radicals and chlorine radicals, rRCl-/ rR, can be no larger than 60%. Hence, Cl- significantly reduces the organic destruction rate in the UV/PS process. In the UV/H2O2 process, we found that Cl- has a negligible effect on the organic-contaminant oxidation rate. Our simulation results agree with the experimental results very well. Accordingly, our mathematical model is a reliable method for determining whether Cl- will adversely impact organic compounds destruction by the UV/PS and UV/H2O2 processes.

Oxidation of Microcystin-LR via Activation of Peroxymonosulfate Using Ascorbic Acid: Kinetic Modeling and Toxicity Assessment.

Advanced oxidation processes (AOPs) have been widely used for the destruction of organic contaminants in the aqueous phase. In this study, we introduce an AOP on activated peroxymonosulfate (PMS) by using ascorbic acid (H2A) to generate sulfate radicals (SO4•-). Sulfate radicals, hydroxyl radicals (HO•), and ascorbyl radicals (A•-) were found using electron spin resonance (ESR). But we found A•- is negligible in the degradation of microcystin-LR (MCLR) due to its low reactivity. We developed a first-principles kinetic model to simulate the MCLR degradation and predict the radical concentrations. The MCLR degradation rate decreased with increasing pH. The scavenging effect of natural organic matter (NOM) on SO4•- was relatively small compared to that for HO•. Considering both energy consumption and MCLR removal, the optimal H2A and PMS doses for H2A/PMS process were determined at 1.0 × 10-6 M and 1.6 × 10-5 M, respectively. In addition, we determined the toxicity using the protein phosphatase 2A (PP2A) test and the results showed that MCLR was readily detoxified and its oxidation byproducts were not hepatotoxic. Overall, our work provides a new type of AOP and a promising, efficient, and environmental-friendly method for removing microcystins in algae-laden water.

Impact of pre-ozonation on disinfection by-product formation and speciation from chlor(am)ination of algal organic matter of Microcystis aeruginosa.

The increasing use of algal-impacted source waters is increasing concerns over exposure to disinfection byproducts (DBPs) in drinking water disinfection, due to the higher concentrations of DBP precursors in these waters. The impact of pre-ozonation on the formation and speciation of DBPs during subsequent chlorination and chloramination of algal organic matter (AOM), including extracellular organic matter (EOM) and intracellular organic matter (IOM), was investigated. During subsequent chlorination, ozonation pretreatment reduced the formation of haloacetonitriles from EOM, but increased the yields of trihalomethanes, dihaloacetic acid and trichloronitromethane from both EOM and IOM. While in chloramination, pre-ozonation remarkably enhanced the yields of several carbonaceous DBPs from IOM, and significantly minimized the nitrogenous DBP precursors. Also, the yield of 1,1-dichloro-2-propanone from IOM was decreased by 24.0% after pre-ozonation during chloramination. Both increases and decreases in the bromine substitution factors (BSF) of AOM were observed with ozone pretreatment at the low bromide level (50µg/L). However, pre-ozonation played little impact on the bromide substitution in DBPs at the high bromide level (500µg/L). This information was used to guide the design and practical operation of pre-ozonation in drinking water treatment plants using algae-rich waters.

Chlorination and chloramination of tetracycline antibiotics: disinfection by-products formation and influential factors.

Formation of disinfection by-products (DBPs) from chlorination and chloramination of tetracycline antibiotics (TCs) was comprehensively investigated. It was demonstrated that a connection existed between the transformation of TCs and the formation of chloroform (CHCl3), carbon tetrachloride (CCl4), dichloroacetonitrile (DCAN) and dichloroacetone (DCAce). Factors evaluated included chlorine (Cl2) and chloramine(NH2Cl) dosage, reaction time, solution pH and disinfection modes. Increased Cl2/NH2Cl dosage and reaction time improved the formation of CHCl3 and DCAce. Formation of DCAN followed an increasing and then decreasing pattern with increasing Cl2 dosage and prolonged reaction time. pH affected DBPs formation differently, with CHCl3 and DCAN decreasing in chlorination, and having maximum concentrations at pH 7 in chloramination. The total concentrations of DBPs obeyed the following order: chlorination>chloramination>pre-chlorination (0.5h)>pre-chlorination (1h)>pre-chlorination (2h).

Molecularly Imprinted Heterostructure-Based Electrochemosensor for Ultratrace and Precise Detection of 2-Methylisoborneol in Water.

Ultratrace 2-methylisoborneol (2-MIB, ∼ng/L) in source water is the main odorant in the algae-derived odor episodes, whose accurate on-site detection will have a promising application potential. Due to the chemical inertness of 2-MIB, sensitive and selective detection of 2-MIB remains much challenging. Herein, molecularly imprinted polymer cavities were polymerized on the heterostructure Ti3C2Tx@CuFc-metal-organic framework to selectively capture 2-MIB, where the heterostructure could catalyze the probe redox reaction of [Fe(CN)63-/4-] and amplify the corresponding current signals. The prepared electrochemical sensor showed higher sensitivity on 2-MIB detection than the reported ones. Excellent stability, reusability, and selectivity for 2-MIB detection were also verified. The linear range and limit of detection of our sensor for 2-MIB were optimized to 0.0001-100 µg/L and 30 pg/L, respectively, performing much better than the reported sensors. Comparable performance to gas chromatography-mass spectrometry was achieved when the sensor was applied to real water samples with or without 2-MIB standards. Overall, our research has made great progress in the application of an on-site sensor in 2-MIB detection and well advances the development of molecularly imprinted polymer-based electrochemical sensors.

Integration of nontarget analysis with machine learning modeling for prioritization of odorous volatile organic compounds in surface water.

Assessing the odor risk caused by volatile organic compounds (VOCs) in water has been a big challenge for water quality evaluation due to the abundance of odorants in water and the inherent difficulty in obtaining the corresponding odor sensory attributes. Here, a novel odor risk assessment approach has been established, incorporating nontarget screening for odorous VOC identification and machine learning (ML) modeling for odor threshold prediction. Twenty-nine odorous VOCs were identified using two-dimensional gas chromatography-time of flight mass spectrometry from four surface water sampling sites. These identified odorants primarily fell into the categories of ketones and ethers, and originated mainly from biological production. To obtain the odor threshold of these odorants, we trained an ML model for odor threshold prediction, which displayed good performance with accuracy of 79%. Further, an odor threshold-based prioritization approach was developed to rank the identified odorants. 2-Methylisoborneol and nonanal were identified as the main odorants contributing to water odor issues at the four sampling sites. This study provides an accessible method for accurate and quick determination of key odorants in source water, aiding in odor control and improved water quality management. ENVIRONMENTAL IMPLICATION: Water odor episodes have been persistent and significant issues worldwide, posing severe challenges to water treatment plants. Unpleasant odors in aquatic environments are predominantly caused by the occurrence of a wide range of volatile organic chemicals (VOCs). Given the vast number of newly-detected VOCs, experimental identification of the key odorants becomes difficult, making water odor issues complex to control. Herein, we propose a novel approach integrating nontarget analysis with machine learning models to accurate and quick determine the key odorants in waterbodies. We use the approach to analyze four samples with odor issues in Changsha, and prioritized the potential odorants.

Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization.

Hydrogel-based sorbents show promise in the removal of toxic metals from water. However, optimizing their performance through conventional trial-and-error methods is both costly and challenging due to the inherent high-dimensional parameter space associated with complex condition combinations. In this study, machine learning (ML) was employed to uncover the relationship between the fabrication condition of hydrogel sorbent and their efficiency in removing toxic metals. The developed XGBoost models demonstrated exceptional accuracy in predicting hydrogel adsorption coefficients (Kd) based on synthesis materials and fabrication conditions. Key factors such as reaction temperature (50-70 °C), time (5-72 h), initiator ((NH4)2S2O8: 2.3-10.3 mol%), and crosslinker (Methylene-Bis-Acrylamide: 1.5-4.3 mol%) significantly influenced Kd. Subsequently, ten hydrogels were fabricated utilizing these optimized feature combinations based on Bayesian optimization, exhibiting superior toxic metal adsorption capabilities that surpassed existing limits (logKd (Cu): increased from 2.70 to 3.06; logKd (Pb): increased from 2.76 to 3.37). Within these determined combinations, the error range (0.025-0.172) between model predictions and experimental validations for logKd (Pb) indicated negligible disparity. Our research outcomes not only offer valuable insights but also provide practical guidance, highlighting the potential for custom-tailored hydrogel designs to combat specific contaminants, courtesy of ML-based Bayesian optimization.

Predicting reactivity dynamics of halogen species and trace organic contaminants using machine learning models.

Reactions of reactive halogen species (Cl•, Br•, and Cl2•-) with trace organic contaminants (TrOCs) have received much attention in recent years, and their k values are fundamental parameters for understanding their reaction mechanisms. However, k values are usually unknown. In this study, we developed machine learning (ML)-based quantitative structure-activity relationship (QSAR) models to predict k values. We tested five algorithms, namely, random forest, neural network, XGBoost, support vector machine (SVM), and multilinear regression, using molecular descriptors (MDs) and molecular fingerprints (MFs) as inputs. The optimal algorithms were MD-XGBoost for Cl• and Br•, and MF-SVM for Cl2•-, respectively, with R2test values of 0.876, 0.743, and 0.853. We found that electron-withdrawing/donating groups tended to interfere with the reactivity of Cl2•- more than Cl• and Br•. This explains why MFs are better inputs for predictive models of Cl2•-, whereas MDs are more suitable for Cl• and Br•. Furthermore, we interpreted the models using SHAP analysis, and the results indicated that our models accurately predicted k values both statistically and mechanistically. Our models provide useful tools for obtaining unknown k values and help researchers understand the inherent relationships between the models.

Experimental Verification of Erchen Decoction Plus Huiyanzhuyu Decoction in the Treatment of Laryngeal Squamous Cell Carcinoma Based on Network Pharmacology.

BACKGROUND: The prescription of Chinese herbal medicine (CHM) consists of multiple herbs that exhibit synergistic effects due to the presence of multiple components targeting various pathways. In clinical practice, the combination of Erchen decoction and Huiyanzhuyu decoction (EHD) has shown promising outcomes in treating patients with laryngeal squamous cell carcinoma (LSCC). However, the underlying mechanism by which EHD exerts its therapeutic effects in LSCC remains unknown. METHODS: Online databases were utilized for the analysis and prediction of the active constituents, targets, and key pathways associated with EHD in the treatment of LSCC. The protein-protein interaction (PPI) network of common targets was constructed and visualized using Cytoscape 3.8.1 software. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the functional roles of core targets within the PPI network. Protein clustering was conducted utilizing the MCODE plug-in. The obtained results highlight the principal targets and pathways involved. Subsequently, clinical samples were collected to validate alterations in the levels of these main targets through Western blotting (WB) and immunohistochemistry (IHC). Furthermore, both in vivo and in vitro experiments were conducted to investigate the therapeutic effects of EHD on healing LSCC and elucidate its underlying mechanism. Additionally, to ensure experimental reliability and reproducibility, quality control measures utilizing HPLC were implemented for EHD herbal medicine. RESULTS: The retrieval and analysis of databases in EHD medicine and LSCC disease yielded a total of 116 overlapping targets. The MCODE plug-in methods were utilized to acquire 8 distinct protein clusters through protein clustering. The findings indicated that both the first and second clusters exhibited a size greater than 6 scores, with key genes PI3K and ErbB occupying central positions, while the third and fourth clusters were associated with proteins in the PI3K, STAT3, and Foxo pathways. GO functional analysis reported that these targets had associations mainly with the pathway of p53 mediated DNA damage and negative regulation of cell cycle in terms of biological function; the death-induced signaling complex in terms of cell function; transcription factor binding and protein kinase activity in terms of molecular function. The KEGG enrichment analysis demonstrated that these targets were correlated with several signaling pathways, including PI3K-Akt, FoxO, and ErbB2 signaling pathway. On one hand, we observed higher levels of key genes such as P-STAT3, P-PDK1, P-Akt, PI3K, and ErbB2 in LSCC tumor tissues compared to adjacent tissues. Conversely, FOXO3a expression was lower in LSCC tumor tissues. On the other hand, the key genes mentioned above were also highly expressed in both LSCC xenograft nude mice tumors and LSCC cell lines, while FOXO3a was underexpressed. In LSCC xenograft nude mice models, EHD treatment resulted in downregulation of P-STAT3, P-PDK1, PI3K, P-AKT, and ErbB2 protein levels but upregulated FOXO3a protein level. EHD also affected the levels of P-STAT3, P-PDK1, PI3K, P-AKT, FOXO3a, and ErbB2 proteins in vitro: it inhibited P-STAT3, P-AKT, and ErbB2, while promoting FOXO3a; however, it had no effect on PDK1 protein. In addition, HPLC identified twelve compounds accounting for more than 30% within EHD. The findings from this study can serve as valuable guidance for future experimental investigations. CONCLUSION: The possible mechanism of EHD medicine action on LSCC disease is speculated to be closely associated with the ErbB2/PI3K/AKT/FOXO3a signaling pathway.

Moderate oxidation of algae-laden water: Principals and challenges.

The occurrence of seasonal algae blooms represents a huge dilemma for water resource management and has garnered widespread attention. Therefore, finding methods to control algae pollution and improve water quality is urgently needed. Moderate oxidation has emerged as a feasible way of algae-laden water treatment and is an economical and prospective strategy for controlling algae and endogenous and exogenous pollutants. Despite this, a comprehensive understanding of algae-laden water treatment by moderate oxidation, particularly principles and summary of advanced strategies, as well as challenges in moderate oxidation application, is still lacking. This review outlines the properties and characterization of algae-laden water, which serve as a prerequisite for assessing the treatment efficiency of moderate oxidation. Biomass, cell viability, and organic matter are key components to assessing moderate oxidation performance. More importantly, the recent advancements in employing moderate oxidation as a treatment or pretreatment procedure were examined, and the suitability of different techniques was evaluated. Generally, moderate oxidation is more promising for improving the solid-liquid separation process by the reduction of cell surface charge (stability) and removal/degradation of the soluble algae secretions. Furthermore, this review presents an outlook on future research directions aimed at overcoming the challenges encountered by existing moderate oxidation technologies. This comprehensive examination aims to provide new and valuable insights into the moderate oxidation process.