The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.

All areas of the modern society are affected by fluorine chemistry. In particular, fluorine plays an important role in medical, pharmaceutical and agrochemical sciences. Amongst various fluoro-organic compounds, trifluoromethyl (CF3) group is valuable in applications such as pharmaceuticals, agrochemicals and industrial chemicals. In the present study, following the strict OECD modelling principles, a quantitative structure-toxicity relationship (QSTR) modelling for the rat acute oral toxicity of trifluoromethyl compounds (TFMs) was established by genetic algorithm-multiple linear regression (GA-MLR) approach. All developed models were evaluated by various state-of-the-art validation metrics and the OECD principles. The best QSTR model included nine easily interpretable 2D molecular descriptors with clear physical and chemical significance. The mechanistic interpretation showed that the atom-type electro-topological state indices, molecular connectivity, ionization potential, lipophilicity and some autocorrelation coefficients are the main factors contributing to the acute oral toxicity of TFMs against rats. To validate that the selected 2D descriptors can effectively characterize the toxicity, we performed the chemical read-across analysis. We also compared the best QSTR model with public OPERA tool to demonstrate the reliability of the predictions. To further improve the prediction range of the QSTR model, we performed the consensus modelling. Finally, the optimum QSTR model was utilized to predict a true external set containing many untested/unknown TFMs for the first time. Overall, the developed model contributes to a more comprehensive safety assessment approach for novel CF3-containing pharmaceuticals or chemicals, reducing unnecessary chemical synthesis whilst saving the development cost of new drugs.

Mechanism of AGT-Mediated Repair of dG-dC Cross-Links in the Drug Resistance to Chloroethylnitrosoureas: Molecular Docking, MD Simulation, and ONIOM (QM/MM) Investigation.

Chloroethylnitrosoureas (CENUs) are important chemotherapies applied in the treatment of cancer. They exert anticancer activity by inducing DNA interstrand cross-links (ICLs) via the formation of two O6-alkylguanine intermediates, O6-chloroethylguanine (O6-ClEtG) and N1,O6-ethanoguanine (N1,O6-EtG). However, O6-alkylguanine-DNA alkyltransferase (AGT), a DNA-repair enzyme, can restore the O6-alkylguanine damages and thereby obstruct the formation of ICLs (dG-dC cross-link). In this study, the inhibitory mechanism of ICL formation was investigated to elucidate the drug resistance of CENUs mediated by AGT in detail. Based on the structures of the substrate-enzyme complexes obtained from docking and MD simulations, two ONIOM (QM/MM) models with different sizes of the QM region were constructed. The model with a larger QM region, which included the substrate (O6-ClEtG or N1,O6-EtG), a water molecule, and five residues (Tyr114, Cys145, His146, Lys165, and Glu172) in the active pocket of AGT, accurately described the repairing reaction and generated the results coinciding with the experimental outcomes. The repair process consists of two sequential steps: hydrogen transfer to form a thiolate anion on Cys145 and alkyl transfer from the O6 site of guanine (the rate-limiting step). The repair of N1,O6-EtG was more favorable than that of O6-ClEtG from both kinetics and thermodynamics aspects. Moreover, the comparison of the repairing process with the formation of dG-dC cross-link and the inhibition of AGT by O6-benzylguanine (O6-BG) showed that the presence of AGT could effectively interrupt the formation of ICLs leading to drug resistance, and the inhibition of AGT by O6-BG that was energetically more favorable than the repair of O6-ClEtG could not prevent the repair of N1,O6-EtG. Therefore, it is necessary to completely eliminate AGT activity before CENUs medication to enhance the chemotherapeutic effectiveness. This work provides reasonable explanations for the supposed mechanism of AGT-mediated drug resistance of CENUs and will assist in the development of novel CENU chemotherapies and their medication strategies.

Computer-Aided Rational Design Strategy to Improve the Thermal Stability of Alginate Lyase AlyMc.

Alginate lyase degrades alginate by the ß-elimination mechanism to produce unsaturated alginate oligosaccharides (UAOS), which have better bioactivities than saturated AOS. Enhancing the thermal stability of alginate lyases is crucial for their industrial applications. In this study, a feasible and efficient rational design strategy was proposed by combining the computer-aided ΔΔG value calculation with the B-factor analysis. Two thermal stability-enhanced mutants, Q246V and K249V, were obtained by site-directed mutagenesis. Particularly, the t1/2, 50 °C for mutants Q246V and K249V was increased from 2.36 to 3.85 and 3.65 h, respectively. Remarkably, the specific activities of Q246V and K249V were enhanced to 2.41- and 2.96-fold that of alginate lyase AlyMc, respectively. Structural analysis and molecular dynamics simulations suggested that mutations enhanced the hydrogen bond networks and the overall rigidity of the molecular structure. Notably, mutant Q246V exhibited excellent thermal stability among the PL-7 alginate lyase family, especially considering the heightened enzymatic activity. Moreover, the rational design strategy used in this study can effectively improve the thermal stability of enzymes and has important significance in advancing applications of alginate lyase.

Prioritization of the ecotoxicological hazard of PAHs towards aquatic species spanning three trophic levels using 2D-QSTR, read-across and machine learning-driven modelling approaches.

Polycyclic aromatic hydrocarbons (PAHs) represent a common group of environmental pollutants that endanger various aquatic organisms via various pathways. To better prioritize the ecotoxicological hazard of PAHs to aquatic environment, we used 2D descriptors-based quantitative structure-toxicity relationship (QSTR) to assess the toxicity of PAHs toward six aquatic model organisms spanning three trophic levels. According to strict OECD guideline, six easily interpretable, transferable and reproducible 2D-QSTR models were constructed with high robustness and reliability. A mechanistic interpretation unveiled the key structural factors primarily responsible for controlling the aquatic ecotoxicity of PAHs. Furthermore, quantitative read-across and different machine learning approaches were employed to validate and optimize the modelling approach. Importantly, the optimum QSTR models were further applied for predicting the ecotoxicity of hundreds of untested/unknown PAHs gathered from Pesticide Properties Database (PPDB). Especially, we provided a priority list in terms of the toxicity of unknown PAHs to six aquatic species, along with the corresponding mechanistic interpretation. In summary, the models can serve as valuable tools for aquatic risk assessment and prioritization of untested or completely new PAHs chemicals, providing essential guidance for formulating regulatory policies.

Recent advances in chemometric modelling of inhibitors against SARS-CoV-2.

The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused great harm to all countries worldwide. This disease can be prevented by vaccination and managed using various treatment methods, including injections, oral medications, or aerosol therapies. However, the selection of suitable compounds for the research and development of anti-SARS-CoV-2 drugs is a daunting task because of the vast databases of available compounds. The traditional process of drug research and development is time-consuming, labour-intensive, and costly. The application of chemometrics can significantly expedite drug R&D. This is particularly necessary and important for drug development against pandemic public emergency diseases, such as COVID-19. Through various chemometric techniques, such as quantitative structure-activity relationship (QSAR) modelling, molecular docking, and molecular dynamics (MD) simulations, compounds with inhibitory activity against SARS-CoV-2 can be quickly screened, allowing researchers to focus on the few prioritised candidates. In addition, the ADMET properties of the screened candidate compounds should be further explored to promote the successful discovery of anti-SARS-CoV-2 drugs. In this case, considerable time and economic costs can be saved while minimising the need for extensive animal experiments, in line with the 3R principles. This paper focuses on recent advances in chemometric modelling studies of COVID-19-related inhibitors, highlights current limitations, and outlines potential future directions for development.

Molecular Toxicology and Cancer Prevention.

Molecular toxicology is a field that investigates the interactions between chemical or biological molecules and organisms at the molecular level [...].

Development and in vitro evaluation of carmustine delivery platform: A hypoxia-sensitive anti-drug resistant nanomicelle with BBB penetrating ability.

Glioma is extremely difficult to be completely excised by surgery due to its invasive nature. Thus, chemotherapy still is the mainstay in the treatment of glioma after surgery. However, the natural blood-brain barrier (BBB) greatly restricts the penetration of chemotherapeutic agents into the central nervous system. As a front-line anti-glioma agent in clinical, carmustine (BCNU) exerts antitumor effect by inducing DNA damage at the O6 position of guanine. However, the therapeutic effect of BCNU was largely decreased because of the drug resistance mediated by O6-alkylguanine-DNA alkyltransferase (AGT) and insufficient local drug concentrations. To overcome these obstacles, we synthesized a BCNU-loaded hypoxia-responsive nano-micelle with BBB penetrating capacity and AGT inhibitory activity, named as T80-HA-AZO-BG/BCNU NPs. In this nano-system, Tween 80 (T80) serves as a functional coating on the surface of the micelle, promoting transportation across the BBB. Hyaluronic acid (HA) with active tumor-targeting capability was linked with the hydrophobic O6-benzylguanine (BG) analog via a hypoxia-sensitive azo bond. Under hypoxic tumor microenvironment, the azo bond selectively breaks to release O6-BG as AGT inhibitor and BCNU as DNA alkylating agent. The synthesized T80-HA-AZO-BG/BCNU NPs showed good stability, favorable biocompatibility and hypoxia-responsive drug-releasing ability. T80 modification improved the transportation of the micelle across an in vitro BBB model. Moreover, T80-HA-AZO-BG/BCNU NPs exhibited significantly enhanced cytotoxicity against glioma cell lines with high AGT expression compared with traditional combined medication of BCNU plus O6-BG. We expect that the tumor-targeting nano-micelle designed for chloroethylnitrosourea will provide new tools for the development of effective glioma therapy.

QSAR and Chemical Read-Across Analysis of 370 Potential MGMT Inactivators to Identify the Structural Features Influencing Inactivation Potency.

O6-methylguanine-DNA methyltransferase (MGMT) constitutes an important cellular mechanism for repairing potentially cytotoxic DNA damage induced by guanine O6-alkylating agents and can render cells highly resistant to certain cancer chemotherapeutic drugs. A wide variety of potential MGMT inactivators have been designed and synthesized for the purpose of overcoming MGMT-mediated tumor resistance. We determined the inactivation potency of these compounds against human recombinant MGMT using [3H]-methylated-DNA-based MGMT inactivation assays and calculated the IC50 values. Using the results of 370 compounds, we performed quantitative structure-activity relationship (QSAR) modeling to identify the correlation between the chemical structure and MGMT-inactivating ability. Modeling was based on subdividing the sorted pIC50 values or on chemical structures or was random. A total of nine molecular descriptors were presented in the model equation, in which the mechanistic interpretation indicated that the status of nitrogen atoms, aliphatic primary amino groups, the presence of O-S at topological distance 3, the presence of Al-O-Ar/Ar-O-Ar/R..O..R/R-O-C=X, the ionization potential and hydrogen bond donors are the main factors responsible for inactivation ability. The final model was of high internal robustness, goodness of fit and prediction ability (R2pr = 0.7474, Q2Fn = 0.7375-0.7437, CCCpr = 0.8530). After the best splitting model was decided, we established the full model based on the entire set of compounds using the same descriptor combination. We also used a similarity-based read-across technique to further improve the external predictive ability of the model (R2pr = 0.7528, Q2Fn = 0.7387-0.7449, CCCpr = 0.8560). The prediction quality of 66 true external compounds was checked using the "Prediction Reliability Indicator" tool. In summary, we defined key structural features associated with MGMT inactivation, thus allowing for the design of MGMT inactivators that might improve clinical outcomes in cancer treatment.

A multi-functional hypoxia/esterase dual stimulus responsive and hyaluronic acid-based nanomicelle for targeting delivery of chloroethylnitrosouea.

Carmustine (BCNU), a vital type of chloroethylnitrosourea (CENU), inhibits tumor cells growth by inducing DNA damage at O6 position of guanine and eventually forming dG-dC interstrand cross-links (ICLs). However, the clinical application of BCNU is hindered to some extent by the absence of tumor selectivity, poor stability and O6-alkylguanine-DNA alkyltransferase (AGT) mediated drug resistance. In recent years, tumor microenvironment has been widely utilized for advanced drug delivery. In the light of the features of tumor microenvironment, we constructed a multifunctional hypoxia/esterase-degradable nanomicelle with AGT inhibitory activity named HACB NPs for tumor-targeting BCNU delivery and tumor sensitization. HACB NPs was self-assembled from hyaluronic acid azobenzene AGT inhibitor conjugates, in which O6-BG analog acted as an AGT inhibitor, azobenzene acted as a hypoxia-responsive linker and carboxylate ester bond acted as both an esterase-sensitive switch and a connector with hyaluronic acid (HA). The obtained HACB NPs possessed good stability, favorable biosafety and hypoxia/esterase-responsive drug-releasing ability. BCNU-loaded HACB/BCNU NPs exhibited superior cytotoxicity and apoptosis-inducing ability toward the human uterine cervix carcinoma HeLa cells compared with traditional combined medication of BCNU plus O6-BG. In vivo studies further demonstrated that after a selective accumulation in the tumor site, the micelles could respond to hypoxic tumor tissue for rapid drug release to an effective therapeutic dosage. Thus, this multifunctional stimulus-responsive nanocarrier could be a new promising strategy to enhance the anticancer efficacy and reduce the side effects of BCNU and other CENUs.

Hypoxia and CD44 receptors dual-targeted nano-micelles with AGT-inhibitory activity for the targeting delivery of carmustine.

Carmustine (BCNU) is a typical chemotherapy used for treatment of cerebroma and other solid tumors, which exerts antitumor effect by inducing DNA damage at O6 position of guanine. However, the clinical application of BCNU was extremely limited due to the drug resistance mainly mediated by O6-alkylguanine-DNA alkyltransferase (AGT) and absence of tumor-targeting ability. To overcome these limitations, we developed a hypoxia-responsive nanomicelle with AGT inhibitory activity, which was successfully loaded with BCNU. In this nano-system, hyaluronic acid (HA) acts as an active tumor-targeting ligand to bind the overexpressing CD44 receptors on the surface of tumor cells. An azo bond selectively breaks in hypoxic tumor microenvironment to release O6-benzylguanine (BG) as AGT inhibitor and BCNU as DNA alkylating agent. The obtained HA-AZO-BG NPs with shell core structure had an average particle size of 176.98 ± 11.19 nm and exhibited good stability. Meanwhile, HA-AZO-BG NPs possessed a hypoxia-responsive drug release profile. After immobilizing BCNU into HA-AZO-BG NPs, the obtained HA-AZO-BG/BCNU NPs exhibited obvious hypoxia-selectivity and superior cytotoxicity in T98G, A549, MCF-7 and SMMC-7721 cells with IC50 at 189.0, 183.2, 90.1 and 100.1 µm, respectively, under hypoxic condition. Near-infrared imaging in HeLa tumor xenograft models showed that HA-AZO-BG/DiR NPs could effectively accumulate in tumor site at 4 h of post-injection, suggesting its good tumor-targetability. In addition, in vivo anti-tumor efficacy and toxicity evaluation indicated that HA-AZO-BG/BCNU NPs was more effective and less harmful compared to the other groups. After treatment, the tumor weight of HA-AZO-BG/BCNU NPs group was 58.46 % and 63.33 % of the control group and BCNU group, respectively. Overall, HA-AZO-BG/BCNU NPs was expected to be a promising candidate for targeted delivery of BCNU and elimination of chemoresistance.

Modulating MGMT expression through interfering with cell signaling pathways.

Guanine O6-alkylating agents are widely used as first-line chemotherapeutic drugs due to their ability to induce cytotoxic DNA damage. However, a major hurdle in their effectiveness is the emergence of chemoresistance, largely attributed to the DNA repair pathway mediated by O6-methylguanine-DNA methyltransferase (MGMT). MGMT plays an important role in removing the alkyl groups from lethal O6-alkylguanine (O6-AlkylG) adducts formed by chemotherapeutic alkylating agents. By doing so, MGMT enables tumor cells to evade apoptosis and develop drug resistance toward DNA alkylating agents. Although covalent inhibitors of MGMT, such as O6-benzylguanine (O6-BG) and O6-(4-bromothenyl)guanine (O6-4-BTG or lomeguatrib), have been explored in clinical settings, their utility is limited due to severe delayed hematological toxicity observed in most patients when combined with alkylating agents. Therefore, there is an urgent need to identify new targets and unravel the underlying molecular mechanisms and to develop alternative therapeutic strategies that can overcome MGMT-mediated tumor resistance. In this context, the regulation of MGMT expression via interfering the specific cell signaling pathways (e.g., Wnt/ß-catenin, NF-κB, Hedgehog, PI3K/AKT/mTOR, JAK/STAT) emerges as a promising strategy for overcoming tumor resistance, and ultimately enhancing the efficacy of DNA alkylating agents in chemotherapy.

Ecotoxicological QSAR study of fused/non-fused polycyclic aromatic hydrocarbons (FNFPAHs): Assessment and priority ranking of the acute toxicity to Pimephales promelas by QSAR and consensus modeling methods.

Fused/non-fused polycyclic aromatic hydrocarbons (FNFPAHs) have a variety of toxic effects on ecosystems and human body, but the acquisition of their toxicity data is greatly limited by the limited resources available. Here, we followed the EU REACH regulation and used Pimephales promelas as a model organism to investigate the quantitative structure-activity relationship (QSAR) between the FNFPAHs and their toxicity for the aquatic environment for the first time. We developed a single QSAR model (SM1) containing five simple and interpretable 2D molecular descriptors, which met the validation of OECD QSAR-related principles, and analyzed their mechanistic relationships with toxicity in detail. The model had good degree of fitting and robustness, and had better external prediction performance (MAEtest = 0.4219) than ECOSAR model (MAEtest = 0.5614). To further enhance its prediction accuracy, the three qualified single models (SMs) were used for constructing consensus models (CMs), the best one CM2 (MAEtest = 0.3954) had a significantly higher prediction accuracy for test compounds than SM1, and also outperformed the T.E.S.T. consensus model (MAEtest = 0.4233). Subsequently, the toxicity of 252 true external FNFPAHs from Pesticide Properties Database (PPDB) was predicted by SM1, the prediction results showed that 94.84 % compounds were reliably predicted within the model's application domain (AD). We also applied the best CM2 to predict the untested 252 FNFPAHs. Furthermore, we provided a mechanistic analysis and explanation for pesticides ranked as top 10 most toxic FNFPAHs. In summary, all developed QSAR and consensus models can be used as efficient tools for predicting the acute toxicity of unknown FNFPAHs to Pimephales promelas, thus being important for the risk assessment and regulation of FNFPAHs contamination in aquatic environment.

Aerobic C-C Bond Cleavage of Allylic Alcohols via Co-Catalyzed Hydrogen Atom Transfer.

A simple, efficient method has been developed for the CoIII-H-catalyzed aerobic C-C bond cleavage of tertiary allylic alcohols to access ketones. This novel approach presents excellent chemoselectivity, good functional group compatibility, and high yields. This reaction occurs through a HAT-initiated peroxide intermediate, and an adjacent glycol-type diradical fragmentation process is recommended.

Effect of drying processes on the occurrence of lipid oxidation-derived 4-hydroxy-2-hexenal and 4-hydroxy-2-nonenal in Spanish mackerel (Scomberomorus niphonius).

In this study, dry-cured Spanish mackerel (Scomberomorus niphonius, DCSM) was prepared via three different methods (hot-air drying, cold-air drying, and sun drying). The content of 4-hydroxy-2-hexenal (HHE) and 4-hydroxy-2-nonenal (HNE) derived from lipid oxidation in whole processes was investigated by HPLC-MS/MS. The changes in fatty acid composition were detected by GC-MS, and the degree of lipid oxidation was evaluated by the levels of acid values (AV), peroxide values (POV), and thiobarbituric acid-reactive substances (TBARS). The results showed that the drying process significantly accelerated lipid oxidation in DCSM. The contents of HHE and HNE were significantly increased after processing. The content of HHE was higher by 18.44-, 13.45-, and 16.32-folds compared with that of HNE after three different processes, respectively. The HHE and HNE contents fluctuated upward during the hot-air and cold-air drying process. However, the contents of HHE and HNE increased time-dependent during the sun drying process, with the highest values of 86.33 ± 10.54 and 5.29 ± 0.54 mg/kg fish among the three different processes. Besides, there was a significant positive correlation between HHE contents and n-3 fatty acids content in hot-air drying and sun drying processes (Pearson's r = .991/.996), and HNE occurrence was closely related to n-6 fatty acid content in sun drying process (Pearson's r = .989). Regression analysis indicated that the content of HHE and TOTOXTBA values in DCSM showed good linear relationships (R 2 value = .907), which suggested that the content of HHE could be used to estimate the oxidative deterioration of dry-cured fish products.

Introduction of multilayered magnetic core-dual shell SERS tags into lateral flow immunoassay: A highly stable and sensitive method for the simultaneous detection of multiple veterinary drugs in complex samples.

Direct, convenient, and sensitive monitoring of the residues of multiple drugs in complex environments is important but remains a challenge. Here, we report a surface-enhanced Raman scattering (SERS)-based multiplexed lateral flow immunoassay (LFA) that supports the simultaneous and sensitive detection of commonly used drugs kanamycin, ractopamine, clenbuterol, and chloramphenicol in unprocessed complex samples through the dual signal amplification strategy of numerous efficient hotspots and magnetic enrichment. Multilayered magnetic-core dual-shell nanoparticles (MDAu@Ag) with controllable subtle nanogaps were fabricated via the polyethyleneimine-mediated layer-by-layer (LBL) assembly of two layers of Au@Ag satellites onto superparamagnetic Fe3O4 cores and conjugated with specific antibodies as multifunctional tags in the LFA system for rapid capture, separation, and quantitative analysis. Two Raman reporters were embedded in internal nanogaps and modified on the surface of MDAu@Ag for the simultaneous and ultrasensitive detection of four targets on two test lines, which greatly simplified the fabrication and signal reading of SERS-LFA. The proposed assay can rapidly detect multiple drug residues in 35 min with detection limits down to pg/mL level. Moreover, the MDAu@Ag-based SERS-LFA demonstrated better stability, higher throughput, and superior sensitivity (at least 400 times) than traditional colloidal gold immunochromatography, showing its great potential in the field of point-of-care testing.

Ecotoxicological QSAR modelling of the acute toxicity of fused and non-fused polycyclic aromatic hydrocarbons (FNFPAHs) against two aquatic organisms: Consensus modelling and comparison with ECOSAR.

Fused and non-fused polycyclic aromatic hydrocarbons (FNFPAHs) are a type of organic compounds widely occurring in the environment that pose a potential hazard to ecosystem and public health, and thus receive extensive attention from various regulatory agencies. Here, quantitative structure-activity relationship (QSAR) models were constructed to model the ecotoxicity of FNFPAHs against two aquatic species, Daphnia magna and Oncorhynchus mykiss. According to the stringent OECD guidelines, we used genetic algorithm (GA) plus multiple linear regression (MLR) approach to establish QSAR models of the two aquatic toxicity endpoints: D. magna (48 h LC50) and O. mykiss (96 h LC50). The models were established using simple 2D descriptors with explicit physicochemical significance and evaluated using various internal/external validation metrics. The results clearly show that both models are statistically robust (QLOO2 = 0.7834 for D. magna and QLOO2 = 0.8162 for O. mykiss), have good internal fitness (R2 = 0.8159 for D. magna and R2 = 0.8626 for O. mykiss and external predictive ability (D. magna: Rtest2 = 0.8259, QFn2 = 0.7640∼0.8140, CCCtest = 0.8972; O. mykiss:Rtest2 = 0.8077, QFn2 = 0.7615∼0.7722, CCCtest = 0.8910). To prove the predictive performance of the developed models, an additional comparison with the standard ECOSAR tool obviously shows that our models have lower RMSE values. Subsequently, we utilized the best models to predict the true external set compounds collected from the PPDB database to further fill the toxicity data gap. In addition, consensus models (CMs) that integrate all validated individual models (IMs) were more externally predictive than IMs, of which CM2 has the best prediction performance towards the two aquatic species. Overall, the models presented here could be used to evaluate unknown FNFPAHs inside the domain of applicability (AD), thus being very important for environmental risk assessment under current regulatory frameworks.

The dual role of DNA repair protein MGMT in cancer prevention and treatment.

Alkylating agents are genotoxic chemicals that can induce and treat various types of cancer. This occurs through covalent bonding with cellular macromolecules, in particular DNA, leading to the loss of functional integrity under the persistence of modifications upon replication. O6-alkylguanine (O6-AlkylG) adducts are proposed to be the most potent DNA lesions induced by alkylating agents. If not repaired correctly, these adducts can result, at the molecular level, in DNA point mutations, chromosome aberrations, recombination, crosslinking, and single- and double-strand breaks (SSB/DSBs). At the cellular level, these lesions can result in malignant transformation, senescence, or cell death. O6-methylguanine-DNA methyltransferase (MGMT) is a DNA repair protein capable of removing the alkyl groups from O6-AlkylG adducts in a damage reversal process that can prevent the adverse biological effects of DNA damage caused by guanine O6-alkylation. MGMT can thereby defend normal cells against tumor initiation, however it can also protect tumor cells against the beneficial effects of chemotherapy. Hence, MGMT can play an important role in both the prevention and treatment of cancer; thus, it can be considered as a double-edged sword. From a clinical perspective, MGMT is a therapeutic target, and it is important to explore the rational development of its clinical exploitation.

Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management-The Case of COVID-19.

BACKGROUND: During the outbreak of COVID-19, online public opinion related to the epidemic was rapidly generated and developed rapidly. If some online public opinions cannot be effectively responded to and guided, it will bring risks to social order. The government should understand how to use information on social media to grasp public demands, provide useful information in a timely manner and take countermeasures. Studying the formation mechanism of online public opinion during the outbreak can help the government make scientific decisions and improve risk management capabilities. METHODS: The research selects the public opinion information of online platforms represented by WeChat, online communities, Sina Weibo and search engines, involving 75 relevant texts (1 January to 31 March 2022). According to the grounded theory method, using the QSR NVivo12 qualitative research software, the collected network texts were successively researched using open coding, axial coding and theoretical coding. RESULTS: The structure of online public opinion during the COVID-19 epidemic was obtained. The operation mechanism of the online public opinion system about COVID-19 was mainly affected by the interaction of online public opinion objects, online public opinion subjects, online public opinion intermediaries and government forces. It was based on social facts and citizens' appeals as the starting point, subject behaviors and prevention and control measures as the focus, government's governance as macro-control and citizens' evaluation as the guide. CONCLUSIONS: Scientific analysis of online public opinion is an important tool to identify and manage risks and improve the quality of government activities. Online public opinion has the function of assisting government decision-making, and the government can identify the important information reflected in it, especially the mainstream public opinion, as a reference for decision-making. By taking effective measures and properly responding to citizens' reasonable demands, the government can prevent social risks and avoid new negative public opinions. Contributions: According to the characteristics of the basic model of online public opinion, this study provides risk mitigation suggestions for Chinese public sectors to use online public opinion, optimize epidemic prevention policies and formulate strategic measures.

Environmental toxicity risk evaluation of nitroaromatic compounds: Machine learning driven binary/multiple classification and design of safe alternatives.

Nitroaromatic compounds (NACs) represent a significant source of organic pollutants in the environment. In this study, a well-rounded dataset containing 371 NACs with rat oral median lethal doses (LD50s) was developed. Based on the dataset, binary and multiple classification models were established. Seven machine learning algorithms were used to establish the prediction models in combination with six fingerprints. In the binary classification models, the overall predictive accuracy of 10-fold cross-validation for training set in the top ten models ranged from 0.823 to 0.874. In the multiple classification models, the combination of graph fingerprint and random forest (Graph-RF) yielded the best predictive effects with AUC values of 0.929 and 0.956 for the training set and the test set, respectively. Model prediction performance was further evaluated using the true external set comprising 1366 NACs, including 96.6% belonging to the applicability domain. Further, we determined the structural features influencing the acute oral toxicity based on information gain and substructure frequency analysis. Finally, we identified highly toxic compounds based on the structural alerts and successfully transformed a representative highly toxic compound into low-toxic alternatives via structural modification. Overall, the models constructed facilitate environmental risk assessment and the design of green and safe chemicals.