*2.1. BUD:HP*β*CD Complex and HP*β*CD Attenuate H2O2* + *LPS-Induced Cytotoxicity*

suffering from smoking-induced COPD.

Since alveolar cell death is one feature observed in the lung of patients suffering from smoking-induced COPD [31], the potential effect of BUD:HPβCD on A549 human alveolar epithelial cells submitted to oxidant and inflammatory stressors was investigated. Cells were incubated with H2O2 + LPS for 2 h. Cytotoxicity, as reflected by lactate dehydrogenase (LDH) release, was observed with a 1.7-fold increase as compared to untreated cells (Figure 1A). The increase in cytotoxicity between 2 and 6 h is low (1.8-fold at 6 h) suggesting the cytotoxicity almost reached its maximum at 2 h. H2O2 + LPS-induced cytotoxicity seemed to result from the addition of H2O2 and LPS. *2.1. BUD:HPβCD Complex and HPβCD Attenuate H2O2 + LPS-Induced Cytotoxicity*  Since alveolar cell death is one feature observed in the lung of patients suffering from smokinginduced COPD [31], the potential effect of BUD:HPβCD on A549 human alveolar epithelial cells submitted to oxidant and inflammatory stressors was investigated. Cells were incubated with H2O2 + LPS for 2 h. Cytotoxicity, as reflected by lactate dehydrogenase (LDH) release, was observed with a 1.7-fold increase as compared to untreated cells (Figure 1A). The increase in cytotoxicity between 2 and 6 h is low (1.8-fold at 6 h) suggesting the cytotoxicity almost reached its maximum at 2 h. H2O2 + LPS-induced cytotoxicity seemed to result from the addition of H2O2 and LPS.

The effect of the BUD:HPβCD complex on cytotoxicity induced by H2O2 + LPS was followed. Incubation of A549 cells with the BUD:HPβCD complex together with H2O2 + LPS induced a decrease in cytotoxicity (Figure 1D). This protective effect appeared to not evolve further after 2 h of incubation. A similar effect was recorded with HPβCD (Figure 1C), whereas BUD showed no effect whatever the dosage (Figure 1B). These results suggest that the BUD:HPβCD complex and HPβCD would have anticytotoxic potential against H2O2 + LPS-induced cytotoxicity in A549 cells. The effect of the BUD:HPβCD complex on cytotoxicity induced by H2O2 + LPS was followed. Incubation of A549 cells with the BUD:HPβCD complex together with H2O2 + LPS induced a decrease in cytotoxicity (Figure 1D). This protective effect appeared to not evolve further after 2h of incubation. A similar effect was recorded with HPβCD (Figure 1C), whereas BUD showed no effect whatever the dosage (Figure 1B). These results suggest that the BUD:HPβCD complex and HPβCD would have anticytotoxic potential against H2O2 + LPS-induced cytotoxicity in A549 cells.

**Figure 1.** Lactate dehydrogenase (LDH) release after A549 cells incubation with H2O2, Lipopolysaccharides (LPSs), and H2O2 + LPS for up to 6 h (**A**) and effect of budesonide (BUD) (**B**), **Figure 1.** Lactate dehydrogenase (LDH) release after A549 cells incubation with H2O2 , Lipopolysaccharides (LPSs), and H2O2 + LPS for up to 6 h (**A**) and effect of budesonide (BUD) (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced cytotoxicity. Each point represents the mean ± SEM of at least 4 independent means of triplicated measures; where not visible, error bars are included in the symbol. The difference was considered significant for a *p*-value < 0.05. (aaa) indicates *p* < 0.001 versus untreated group; (\*\*) and (\*\*\*) corresponds to *p* < 0.01 and 0.001 versus H2O2 +LPS-treated group, respectively.

To determine if apoptosis is involved in the cell death process for which BUD:HPβCD could protect, apoptosis was monitored by counting condensed/fragmented nuclei using HOECHST dye on H2O2 + LPS-treated cells. We also determined if the BUD:HPβCD complex as well as BUD, and HPβCD could attenuate apoptosis. To determine if apoptosis is involved in the cell death process for which BUD:HPβCD could protect, apoptosis was monitored by counting condensed/fragmented nuclei using HOECHST dye on H2O2 + LPS-treated cells. We also determined if the BUD:HPβCD complex as well as BUD, and HPβCD could attenuate apoptosis.

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HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced cytotoxicity. Each point represents the mean ± SEM of at least 4 independent means of triplicated measures; where not visible, error bars are included in the symbol. The difference was considered significant for a *p*-value < 0.05. (aaa) indicates *p* < 0.001 versus untreated group; (\*\*) and (\*\*\*) corresponds to *p* < 0.01 and 0.001 versus

A549 cells were incubated for 2 h with H2O2 + LPS with/without BUD:HPβCD in comparison with BUD or HPβCD. H2O2 + LPS induced significant apoptosis, which appeared to result from the addition of the individual effects of H2O2 and LPS (Figure 2A). Concomitant incubation with each of the selected compounds induced a concentration-dependent decrease in H2O2 + LPS-induced apoptosis. These results suggest that the BUD:HPβCD complex (Figure 2D) and HPβCD (Figure 2C), at the highest selected dosages could protect cells against H2O2 + LPS-induced apoptosis in A549 cells. A non-significant decrease was observed with BUD (Figure 2B). A549 cells were incubated for 2 h with H2O2 + LPS with/without BUD:HPβCD in comparison with BUD or HPβCD. H2O2 + LPS induced significant apoptosis, which appeared to result from the addition of the individual effects of H2O2 and LPS (Figure 2A). Concomitant incubation with each of the selected compounds induced a concentration-dependent decrease in H2O2 + LPS-induced apoptosis. These results suggest that the BUD:HPβCD complex (Figure 2D) and HPβCD (Figure 2C), at the highest selected dosages could protect cells against H2O2 + LPS-induced apoptosis in A549 cells. A non-significant decrease was observed with BUD (Figure 2B).

**Figure 2.** A549 cells apoptosis after treatment with H2O2, LPS, and H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced apoptosis. Apoptosis was quantified by counting condensed/fragmented nuclei after HOECHST staining. Each bar represents the mean of 3 ± SEM or 2 independent measures. A one-way ANOVA with Dunett posttest was used to compare the mean of a test group with the mean of the untreated group or H2O2 +LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aa) indicates *p* < 0.01 versus untreated group, (\*) indicates *p* < 0.05 versus H2O2 +LPS-treated group. **Figure 2.** A549 cells apoptosis after treatment with H2O2 , LPS, and H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced apoptosis. Apoptosis was quantified by counting condensed/fragmented nuclei after HOECHST staining. Each bar represents the mean of 3 ± SEM or 2 independent measures. A one-way ANOVA with Dunett post-test was used to compare the mean of a test group with the mean of the untreated group or H2O2 +LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aa) indicates *p* < 0.01 versus untreated group, (\*) indicates *p* < 0.05 versus H2O2 +LPS-treated group.

#### *2.2. BUD:HPβCD Complex and HPβCD Protect against H2O2 + LPS-Induced Oxidative Stress in A549 2.2. BUD:HP*β*CD Complex and HP*β*CD Protect against H2O2* + *LPS-Induced Oxidative Stress in A549 Cells: Dose and Time-Dependent E*ff*ects*

*Cells: Dose and Time-Dependent Effects*  Because oxidative stress is critical for numerous pathologies including smoking-induced COPD [32], and with the aim to understand the mechanism of action behind the effects observed with BUD:HPβCD, the potential antioxidant effect of the BUD:HPβCD complex in A549 human alveolar epithelial cells was monitored. A549 cells were incubated for 2 h with a H2O2 + LPS mix to model a Because oxidative stress is critical for numerous pathologies including smoking-induced COPD [32], and with the aim to understand the mechanism of action behind the effects observed with BUD:HPβCD, the potential antioxidant effect of the BUD:HPβCD complex in A549 human alveolar epithelial cells was monitored. A549 cells were incubated for 2 h with a H2O2 + LPS mix to model a concomitant oxidative and inflammatory environment. ROS generation induced by the BUD:HPβCD complex was monitored in comparison with the effect induced by budesonide or HPβCD.

In comparison with control cells, we observed a 1.6-fold significant increase in intracellular ROS production when cells were incubated with H2O2 + LPS (Figure 3A) This effect was similar to the effect induced by treatment with H2O2 alone (1.5-fold increase), unlike the treatment with LPS alone, would be mainly driven by H2O2 in A549 cells.

which did not show any significant effects, suggesting that H2O2 + LPS-induced oxidative stress would be mainly driven by H2O2 in A549 cells. H2O2 + LPS. A similar effect was observed with increasing concentrations of HPβCD (25–2500 µM; Figure 3C). In contrast no effect of BUD (1–100 µM; Figure 3B) was observed.

This suggests a protective effect of the BUD:HPβCD complex against the oxidative stress induced by

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concomitant oxidative and inflammatory environment. ROS generation induced by the BUD:HPβCD

In comparison with control cells, we observed a 1.6-fold significant increase in intracellular ROS production when cells were incubated with H2O2 + LPS (Figure 3A) This effect was similar to the effect induced by treatment with H2O2 alone (1.5-fold increase), unlike the treatment with LPS alone, which did not show any significant effects, suggesting that H2O2 + LPS-induced oxidative stress

A concomitant incubation of A549 cells with H2O2 + LPS and increasing concentrations of the BUD:HPβCD complex (1:25, 10:250, 100:2500 µM; Figure 3D) was associated with a decrease in ROS

complex was monitored in comparison with the effect induced by budesonide or HPβCD.

**Figure 3.** ROS generation in A549 cells after treatment with H2O2, LPS, or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced ROS generation. ROS generation was evaluated by measuring the fluorescence of dichlorofluorescein (DCF). Each bar represents the mean ± SEM of 4 independent means of triplicated measures. A one-way ANOVA with Dunett post-test was used to compare the mean of a test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aa), and (aaa), indicate *p* < 0.01, and 0.001 versus untreated group, respectively); (\*\*), and (\*\*\*), correspond to **Figure 3.** ROS generation in A549 cells after treatment with H2O2 , LPS, or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced ROS generation. ROS generation was evaluated by measuring the fluorescence of dichlorofluorescein (DCF). Each bar represents the mean ± SEM of 4 independent means of triplicated measures. A one-way ANOVA with Dunett post-test was used to compare the mean of a test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aa), and (aaa), indicate *p* < 0.01, and 0.001 versus untreated group, respectively); (\*\*), and (\*\*\*), correspond to *p* < 0.01 and 0.001 versus H2O2 + LPS-treated group, respectively.

*p* < 0.01 and 0.001 versus H2O2 + LPS-treated group, respectively. Regarding the effect of time (Figure 4), ROS production in the presence of H2O2 + LPS was already marked after 30 min compared to untreated cells. This effect was maintained throughout the entire time period investigated (6h) and seemed to evolve in parallel with untreated cells after 2 h. When the BUD:HPβCD complex was added together with H2O2 + LPS, a lowering effect on ROS production was observed throughout the entire time period investigated (Figure 4B). The extent of A concomitant incubation of A549 cells with H2O2 + LPS and increasing concentrations of the BUD:HPβCD complex (1:25, 10:250, 100:2500 µM; Figure 3D) was associated with a decrease in ROS production as compared with the experimental conditions in which the complex was not present. This suggests a protective effect of the BUD:HPβCD complex against the oxidative stress induced by H2O2 + LPS. A similar effect was observed with increasing concentrations of HPβCD (25–2500 µM; Figure 3C). In contrast no effect of BUD (1–100 µM; Figure 3B) was observed.

the effect depended upon the dose and was largely similar to the effect observed in the presence of HPβCD (Figure 4C). No significant change was observed after 2 h of incubation with H2O2 + LPS. Again, during the entire period investigated, no significant effect was observed in the presence of BUD (Figure 4A). Altogether, these results suggest that the BUD:HPβCD complex and HPβCD have a similar antioxidant potential against H2O2 + LPS in A549 cells. Regarding the effect of time (Figure 4), ROS production in the presence of H2O2 + LPS was already marked after 30 min compared to untreated cells. This effect was maintained throughout the entire time period investigated (6 h) and seemed to evolve in parallel with untreated cells after 2 h. When the BUD:HPβCD complex was added together with H2O2 + LPS, a lowering effect on ROS production was observed throughout the entire time period investigated (Figure 4B). The extent of the effect depended upon the dose and was largely similar to the effect observed in the presence of HPβCD (Figure 4C). No significant change was observed after 2 h of incubation with H2O2 + LPS. Again, during the entire period investigated, no significant effect was observed in the presence of BUD (Figure 4A). Altogether, these results suggest that the BUD:HPβCD complex and HPβCD have a similar antioxidant potential against H2O2 + LPS in A549 cells.

similar way in A549 cells.

**Figure 4.** Effect of BUD (**A**), BUD:HPβCD complex (**B**) and HPβCD (**C**) on H2O2 + LPS-induced ROS generation for 0 to 6h of incubation. ROS generation was evaluated by measuring the fluorescence of dichlorofluorescein (DCF). Each bar represents the mean ± SEM of 3 independent means of triplicated measures. These results and the results illustrated in Figure 3 are independent. When deviations are not visible they are too small to be seen. The difference was considered significant for a *p*-value < 0.05. (aaa) corresponds to *p* < 0.001 versus untreated group; (\*\*\*) indicates *p* < 0.001 versus H2O2 + LPS-**Figure 4.** Effect of BUD (**A**), BUD:HPβCD complex (**B**) and HPβCD (**C**) on H2O2 + LPS-induced ROS generation for 0 to 6h of incubation. ROS generation was evaluated by measuring the fluorescence of dichlorofluorescein (DCF). Each bar represents the mean ± SEM of 3 independent means of triplicated measures. These results and the results illustrated in Figure 3 are independent. When deviations are not visible they are too small to be seen. The difference was considered significant for a *p*-value < 0.05. (aaa) corresponds to *p* < 0.001 versus untreated group; (\*\*\*) indicates *p* < 0.001 versus H2O2 + LPS-treated group.

#### treated group. *2.3. BUD:HPβCD Complex and HPβCD Attenuate H2O2 + LPS-Induced Phosphoinositide-3-Kinase/Akt 2.3. BUD:HP*β*CD Complex and HP*β*CD Attenuate H2O2* + *LPS-Induced Phosphoinositide-3-Kinase*/*Akt Signaling in A549 Cells*

*Signaling in A549 Cells*  Oxidative stress-induced glucocorticoid insensitivity involves an increase in PI3K/Akt signaling [8,33,34] as reflected by Akt phosphorylation. To validate in in vitro model the relationship between oxidative stress and increase in PI3K/Akt signaling, the phosphorylation of Akt, in the absence or in the presence of antioxidants (N-acetyl-L-cysteine (NAC), vitamin C (Vit C)) and of a PI3K inhibitor (LY294002) (Figure 5A,C) was measured. An incubation of A549 cells with H2O2 + LPS for 2 h increased Akt phosphorylation. Concomitant incubation with NAC or vitamin C or LY294002 was associated with a lower phosphorylation of Akt (of approximately 36% (NAC) and 65% (Vit C)) or a complete suppression of phosphorylation (LY294002) (Figure 5A,C). Regarding the effect of the BUD:HPβCD complex or of HPβCD at a concentration at which a significant antioxidant effect was observed, we demonstrated a decrease in Akt phosphorylation (Figure 5B,D). The decrease was approximately 32% both for the BUD:HPβCD complex and for HPβCD (Figure 5B,D). Thus, the BUD:HPβCD complex and HPβCD inhibited H2O2 + LPS-induced PI3K/Akt signaling increases in a Oxidative stress-induced glucocorticoid insensitivity involves an increase in PI3K/Akt signaling [8,33,34] as reflected by Akt phosphorylation. To validate in in vitro model the relationship between oxidative stress and increase in PI3K/Akt signaling, the phosphorylation of Akt, in the absence or in the presence of antioxidants (N-acetyl-L-cysteine (NAC), vitamin C (Vit C)) and of a PI3K inhibitor (LY294002) (Figure 5A,C) was measured. An incubation of A549 cells with H2O2 + LPS for 2 h increased Akt phosphorylation. Concomitant incubation with NAC or vitamin C or LY294002 was associated with a lower phosphorylation of Akt (of approximately 36% (NAC) and 65% (Vit C)) or a complete suppression of phosphorylation (LY294002) (Figure 5A,C). Regarding the effect of the BUD:HPβCD complex or of HPβCD at a concentration at which a significant antioxidant effect was observed, we demonstrated a decrease in Akt phosphorylation (Figure 5B,D). The decrease was approximately 32% both for the BUD:HPβCD complex and for HPβCD (Figure 5B,D). Thus, the BUD:HPβCD complex and HPβCD inhibited H2O2 + LPS-induced PI3K/Akt signaling increases in a similar way in A549 cells.

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**Figure 5.** Akt phosphorylation induced by H2O2 + LPS in A549 cells. Effect of *N*-acetyl-L-cysteine (NAC), vitamin C (VitC) and LY294002 (**A** and **C**) and BUD:HPβCD complex and HPβCD (**B** and **D**) after 2 h of incubation. Data are expressed in absolute values (A/B; with representative blots) or in relative values (in comparison with the pAkt/Akt ration of cells incubated with H2O2 + LPS; C/D). Akt phosphorylation was quantified after a Western blot by measuring the proportion of phosphorylated-Akt (p-Akt) blot luminescence intensity/total Akt (Akt) blot luminescence intensity. Each bar represents the mean of 3 independent measures. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aaa) correspond to *p* < 0.001 versus untreated group, (\*) and (\*\*\*) indicate *p* < 0.05, and 0.001 versus H2O2 + LPS-treated group, **Figure 5.** Akt phosphorylation induced by H2O2 + LPS in A549 cells. Effect of *N*-acetyl-L-cysteine (NAC), vitamin C (VitC) and LY294002 (**A**,**C**) and BUD:HPβCD complex and HPβCD (**B**,**D**) after 2 h of incubation. Data are expressed in absolute values (A/B; with representative blots) or in relative values (in comparison with the pAkt/Akt ration of cells incubated with H2O2 + LPS; C/D). Akt phosphorylation was quantified after a Western blot by measuring the proportion of phosphorylated-Akt (p-Akt) blot luminescence intensity/total Akt (Akt) blot luminescence intensity. Each bar represents the mean of 3 independent measures. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05. (aaa) correspond to *p* < 0.001 versus untreated group, (\*) and (\*\*\*) indicate *p* < 0.05, and 0.001 versus H2O2 + LPS-treated group, respectively.

#### respectively. *2.4. Cholesterol Might Limit the Effects of BUD:HPβCD Complex and HPβCD in ROS Generation and 2.4. Cholesterol Might Limit the E*ff*ects of BUD:HP*β*CD Complex and HP*β*CD in ROS Generation and PI3K*/*Akt Signaling Induced by H2O2* + *LPS*

*PI3K/Akt Signaling Induced by H2O2 + LPS*  To give insight on the molecular mechanisms involved in the protective effect of BUD:HPBCD and HPBCD, the potential role of cholesterol on ROS generation and PI3/Akt phosphorylation induced by H2O2 + LPS as well as the protective effects of the BUD:HPβCD complex and HPβCD were investigated. The rationale was derived from the ability of cyclodextrins to interact with cholesterol [35], the effects of BUD:HPβCD and HPβCD on the biophysical membrane properties of cholesterol-enriched domains [27], the importance of lipid-ordered domains enriched in cholesterol To give insight on the molecular mechanisms involved in the protective effect of BUD:HPBCD and HPBCD, the potential role of cholesterol on ROS generation and PI3/Akt phosphorylation induced by H2O2 + LPS as well as the protective effects of the BUD:HPβCD complex and HPβCD were investigated. The rationale was derived from the ability of cyclodextrins to interact with cholesterol [35], the effects of BUD:HPβCD and HPβCD on the biophysical membrane properties of cholesterol-enriched domains [27], the importance of lipid-ordered domains enriched in cholesterol in membrane called rafts for ROS generation [36,37] and PI3K/Akt signaling [23,26].

in membrane called rafts for ROS generation [36,37] and PI3K/Akt signaling [23,26].

ROS Generation Induced by H2O2 + LPS

2.4.1. Cholesterol Content Might Influence the Effects of the BUD:HPβCD Complex and HPβCD in ROS Generation Induced by H2O2 + LPS Compared to non-depleted cells, the ability of the BUD:HPβCD complex (Figure 6C) and HPβCD (Figure 6D) to protect against H2O2 + LPS-induced ROS production was preserved. Moreover, when the difference between H2O2 + LPS-induced ROS production in cholesterol-depleted

cholesterol content plays a role in H2O2 + LPS-related oxidative signaling in A549 cells.

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2.4.1. Cholesterol Content Might Influence the Effects of the BUD:HPβCD Complex and HPβCD in

In conditions where cholesterol was partly depleted (see Figure S1) we observed (Figure 6A) an increase in basal intracellular ROS levels, although non-significant. A greater and significant increase

In conditions where cholesterol was partly depleted (see Figure S1) we observed (Figure 6A) an increase in basal intracellular ROS levels, although non-significant. A greater and significant increase in H2O2- and H2O2 + LPS-induced intracellular oxidant generation was also observed, suggesting that cholesterol content plays a role in H2O2 + LPS-related oxidative signaling in A549 cells. and non-depleted cells was considered, a concentration-dependent increase in this protective effect was observed (Figure 6E,F), although this was non-significant. Again, no matter the cholesterol status of the cells, budesonide did not show any protective effects (Figure 6B). Thus, cholesterol content might influence the antioxidant effect of the BUD:HPβCD complex and HPβCD.

**Figure 6.** ROS generation in cholesterol-non-depleted or cholesterol-depleted A549 cells after treatment with H2O2, LPS, or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), BUD:HPβCD complex (**C**) and HPβCD (**D**) on H2O2 + LPS-induced ROS generation. Panels E and F show the difference (∆) between the effect observed in cholesterol-depleted and -non-depleted cells of BUD:HPβCD complex (**E**) and HPβCD (**F**) on H2O2 + LPS-induced oxidant generation after treatment for 2 h. Each bar represents the mean ± SEM of 4 independent means of triplicated measures. H2O2 + LPS-treated bar is the same for each panel. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group in panels (**E**) and (**F**) with the mean of the H2O2 + LPS-treated group. A two-way ANOVA with Tukey multiple comparison post-test was used to compare the mean of non-depleted group with the mean of cholesterol-depleted group in the same concentration (panels **A**–**D**). The **Figure 6.** ROS generation in cholesterol-non-depleted or cholesterol-depleted A549 cells after treatment with H2O2 , LPS, or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), BUD:HPβCD complex (**C**) and HPβCD (**D**) on H2O2 + LPS-induced ROS generation. Panels E and F show the difference (∆) between the effect observed in cholesterol-depleted and -non-depleted cells of BUD:HPβCD complex (**E**) and HPβCD (**F**) on H2O2 + LPS-induced oxidant generation after treatment for 2 h. Each bar represents the mean ± SEM of 4 independent means of triplicated measures. H2O2 + LPS-treated bar is the same for each panel. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group in panels (**E**,**F**) with the mean of the H2O2 + LPS-treated group. A two-way ANOVA with Tukey multiple comparison post-test was used to compare the mean of non-depleted group with the mean of cholesterol-depleted group in the same concentration (panels **A**–**D**). The difference was considered significant for a *p*-value < 0.05. (\*) and (\*\*) indicate, respectively, *p* < 0.05 and 0.01 between non-depleted and cholesterol-depleted group (panels **A**–**D**).

Compared to non-depleted cells, the ability of the BUD:HPβCD complex (Figure 6C) and HPβCD (Figure 6D) to protect against H2O2 + LPS-induced ROS production was preserved. Moreover, when the difference between H2O2 + LPS-induced ROS production in cholesterol-depleted and non-depleted cells was considered, a concentration-dependent increase in this protective effect was observed (Figure 6E,F), although this was non-significant. Again, no matter the cholesterol status of the cells, budesonide did not show any protective effects (Figure 6B). Thus, cholesterol content might influence the antioxidant effect of the BUD:HPβCD complex and HPβCD. difference was considered significant for a *p*-value < 0.05. (\*) and (\*\*) indicate, respectively, *p* < 0.05 and 0.01 between non-depleted and cholesterol-depleted group (panels **A**–**D**).

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In contrast with cholesterol, sphingomyelin, another major component from raft and also interacting with HPβCD did not play a critical role on neither the oxidant generation induced by H2O2 + LPS nor on the ability of the BUD:HPβCD complex and HPβCD to protect against H2O2 + LPS-induced oxidant generation (Figure S2). In contrast with cholesterol, sphingomyelin, another major component from raft and also interacting with HPβCD did not play a critical role on neither the oxidant generation induced by H2O2 + LPS nor on the ability of the BUD:HPβCD complex and HPβCD to protect against H2O2 + LPSinduced oxidant generation (Figure S2).

2.4.2. Cholesterol Limits the Effects of the BUD:HPβCD Complex and HPβCD in PI3K/Akt Signaling Induced by H2O2 + LPS 2.4.2. Cholesterol limits the effects of the BUD:HPβCD complex and HPβCD in PI3K/Akt signaling induced by H2O2 + LPS

Since cholesterol-enriched plasma membrane domains may also play a critical role in the activation of PI3K/Akt signaling [23,25,26], which could be modulated by oxidative stress, the effect of cholesterol depletion on the protective effects of the BUD:HPβCD complex and HPβCD on the phosphorylation of Akt was studied. A decrease in Akt phosphorylation was preserved (Figure 7), without difference in cholesterol-depleted or not depleted cells. Since cholesterol-enriched plasma membrane domains may also play a critical role in the activation of PI3K/Akt signaling [23,25,26], which could be modulated by oxidative stress, the effect of cholesterol depletion on the protective effects of the BUD:HPβCD complex and HPβCD on the phosphorylation of Akt was studied. A decrease in Akt phosphorylation was preserved (Figure 7), without difference in cholesterol-depleted or not depleted cells.

**Figure 7.** Effect of the BUD:HPβCD complex versus HPβCD on H2O2 + LPS-induced Akt phosphorylation (p-Akt) in cholesterol-depleted and non-depleted A549 cells after 2 h of incubation with representative blot (cholesterol-depleted cells); each bar represents the mean of 3 independent **Figure 7.** Effect of the BUD:HPβCD complex versus HPβCD on H2O2 + LPS-induced Akt phosphorylation (p-Akt) in cholesterol-depleted and non-depleted A549 cells after 2 h of incubation with representative blot (cholesterol-depleted cells); each bar represents the mean of 3 independent measures.

#### measures. *2.5. BUD:HPβCD Complex and HPβCD Protect against H2O2 + LPS-Induced Increase in HDAC2 2.5. BUD:HP*β*CD Complex and HP*β*CD Protect against H2O2* + *LPS-Induced Increase in HDAC2 Phosphorylation in A549 Cells*

*Phosphorylation in A549 cells*  The increase in PI3K/Akt signaling induced by oxidative stress results in the phosphorylation of HDAC2, a critical step in oxidative stress-related glucocorticoid insensitivity [38,39]. The relationship between oxidative stress and HDAC2 phosphorylation as well as the relationship between the increase in PI3K/Akt signaling and HDAC2 phosphorylation was investigated by using NAC and LY294002, respectively (Figure 8A,C). The treatment of A549 cells with H2O2 + LPS for 2 h was associated with an increase in phosphorylated HDAC2. Concomitant incubation with NAC or LY294002 was associated with a lower phosphorylation of HDAC2 of approximately 62% (NAC) and The increase in PI3K/Akt signaling induced by oxidative stress results in the phosphorylation of HDAC2, a critical step in oxidative stress-related glucocorticoid insensitivity [38,39]. The relationship between oxidative stress and HDAC2 phosphorylation as well as the relationship between the increase in PI3K/Akt signaling and HDAC2 phosphorylation was investigated by using NAC and LY294002, respectively (Figure 8A,C). The treatment of A549 cells with H2O2 + LPS for 2 h was associated with an increase in phosphorylated HDAC2. Concomitant incubation with NAC or LY294002 was associated with a lower phosphorylation of HDAC2 of approximately 62% (NAC) and 40% (LY294002) (Figure 8A,C). This confirms that H2O2 + LPS increases HDAC2 phosphorylation through a mechanism involving oxidative stress and PI3K/Akt signaling in A549 cells.

40% (LY294002) (Figure 8A,C). This confirms that H2O2 + LPS increases HDAC2 phosphorylation through a mechanism involving oxidative stress and PI3K/Akt signaling in A549 cells. A concomitant incubation with the BUD:HPβCD complex or HPβCD with H2O2 + LPS was A concomitant incubation with the BUD:HPβCD complex or HPβCD with H2O2 + LPS was associated with a lower phosphorylation of HDAC2 of approximately 53% (BUD:HPβCD) and 74%

associated with a lower phosphorylation of HDAC2 of approximately 53% (BUD:HPβCD) and 74% (HPβCD) (Figure 8B,D). Thus, the BUD:HPβCD complex and HPβCD inhibited the decrease in

*Molecules* **2020**, *25*, x 10 of 21

**Figure 8.** HDAC2 phosphorylation induced by H2O2 + LPS in A549 cells. Effect of NAC and LY294002 (**A**) and the BUD:HPβCD complex versus HPβCD (**B**) after 2 h of incubation. Data are expressed in absolute values (**A**/**B**; with representative blots) or in relative values (in comparison with the pHDAC2/HDAC2 ration of cells incubated with H2O2 + LPS; **C**/**D**). HDAC2 phosphorylation was quantified after a Western blot by measuring the proportion of phosphorylated-HDAC2 (p-HDAC2) blot luminescence intensity/total HDAC2 (HDAC2) blot luminescence intensity. Each bar represents the mean of 3 ± SEM or 2 independent measures. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group with the mean of the control group (H2O2 + LPS-treated group). The difference was considered significant for a *p*-value < 0.05. (\*) indicate *p* < 0.05 versus **Figure 8.** HDAC2 phosphorylation induced by H2O2 + LPS in A549 cells. Effect of NAC and LY294002 (**A**) and the BUD:HPβCD complex versus HPβCD (**B**) after 2 h of incubation. Data are expressed in absolute values (**A**/**B**; with representative blots) or in relative values (in comparison with the pHDAC2/HDAC2 ration of cells incubated with H2O2 + LPS; **C**/**D**). HDAC2 phosphorylation was quantified after a Western blot by measuring the proportion of phosphorylated-HDAC2 (p-HDAC2) blot luminescence intensity/total HDAC2 (HDAC2) blot luminescence intensity. Each bar represents the mean of 3 ± SEM or 2 independent measures. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group with the mean of the control group (H2O2 + LPS-treated group). The difference was considered significant for a *p*-value < 0.05. (\*) indicate *p* < 0.05 versus control group.

#### control group. *2.6. BUD:HP*β*CD Complex and HP*β*CD Attenuate H2O2* + *LPS-Induced Inflammatory Response in THP-1 Cells*

*2.6. BUD:HPβCD Complex and HPβCD Attenuate H2O2 + LPS-Induced Inflammatory Response in THP-1 Cells*  Since persistent inflammatory response in the lung is a major feature of smoking-induced COPD [31], the anti-inflammatory potential of the BUD:HPβCD complex in comparison with BUD or HPβCD was evaluated. Thus, the effect of the BUD:HPβCD complex, BUD or HPβCD on H2O2 + LPSinduced IL-8 release in A549 cells and TH-P1 cells was determined. Because A549 cells appeared not sensitive to LPS [40], phorbol myristate acetate-activated THP-1 (A-THP-1) cells [41], a widely used Since persistent inflammatory response in the lung is a major feature of smoking-induced COPD [31], the anti-inflammatory potential of the BUD:HPβCD complex in comparison with BUD or HPβCD was evaluated. Thus, the effect of the BUD:HPβCD complex, BUD or HPβCD on H2O2 + LPS-induced IL-8 release in A549 cells and TH-P1 cells was determined. Because A549 cells appeared not sensitive to LPS [40], phorbol myristate acetate-activated THP-1 (A-THP-1) cells [41], a widely used model for human monocytes, which are highly sensitive to LPS treatment, were used. For the sake of comparison, we also treated A549 cells with TNF-α for inflammatory stress.

model for human monocytes, which are highly sensitive to LPS treatment, were used. For the sake of

comparison, we also treated A549 cells with TNF-α for inflammatory stress.

10).

First, the incubation of A-THP-1 cells with H2O2 + LPS for 2 h was significantly associated with an 8.6-fold increase in IL-8 release (Figure 9A). Treatment with LPS alone induced a significant 6.6-fold increase, whereas H2O2 alone did not induce any effects on IL-8 expression [41]. First, the incubation of A-THP-1 cells with H2O2 + LPS for 2 h was significantly associated with an 8.6-fold increase in IL-8 release (Figure 9A). Treatment with LPS alone induced a significant 6.6 fold increase, whereas H2O2 alone did not induce any effects on IL-8 expression [41]. Concomitant incubation of the BUD:HPβCD complex with H2O2 + LPS was associated with a

Concomitant incubation of the BUD:HPβCD complex with H2O2 + LPS was associated with a lower release of IL-8 of approximately 45% no matter the concentration of the BUD:HPβCD complex used (Figure 9D). In the presence of BUD, a decrease in of IL-8 release was also observed. The effect was similar with that induced by the BUD:HPβCD complex (budesonide 1 and 10 µM), but higher at higher budesonide concentration (100 µM) (67%) (Figure 9B). The presence of HPβCD was also associated with a non-dependent dose-type decrease in IL-8 release. The effect was slightly lower as compared to BUD and the BUD:HPβCD complex (approximately 34%) (Figure 9C). These results suggest that the BUD:HPβCD complex and BUD have similar anti-inflammatory properties, except at high concentrations at which budesonide was more efficient. lower release of IL-8 of approximately 45% no matter the concentration of the BUD:HPβCD complex used (Figure 9D). In the presence of BUD, a decrease in of IL-8 release was also observed. The effect was similar with that induced by the BUD:HPβCD complex (budesonide 1 and 10 µM), but higher at higher budesonide concentration (100 µM) (67%) (Figure 9B). The presence of HPβCD was also associated with a non-dependent dose-type decrease in IL-8 release. The effect was slightly lower as compared to BUD and the BUD:HPβCD complex (approximately 34%) (Figure 9C). These results suggest that the BUD:HPβCD complex and BUD have similar anti-inflammatory properties, except at high concentrations at which budesonide was more efficient.

**Figure 9.** IL-8 release by A-THP-1 cells after treatment with H2O2, LPS or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced IL-8 release. IL-8 release was measured in the extracellular medium by sandwich ELISA. Each bar represents the mean ± SEM of 3 independent means of triplicated measures. A one-way ANOVA with Dunett posttest was used to compare the mean of each test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05; (aaa), indicate *p* < **Figure 9.** IL-8 release by A-THP-1 cells after treatment with H2O2 , LPS or H2O2 + LPS for 2 h (**A**) and effect of BUD (**B**), HPβCD (**C**), and BUD:HPβCD complex (**D**) on H2O2 + LPS-induced IL-8 release. IL-8 release was measured in the extracellular medium by sandwich ELISA. Each bar represents the mean ± SEM of 3 independent means of triplicated measures. A one-way ANOVA with Dunett post-test was used to compare the mean of each test group with the mean of untreated group or H2O2 + LPS-treated group. The difference was considered significant for a *p*-value < 0.05; (aaa), indicate *p* < 0.001 versus untreated group; (\*), (\*\*), and (\*\*\*) correspond to *p* < 0.05, 0.01 and 0.001 versus H2O2 + LPS-treated group, respectively.

LPS-treated group, respectively. A similar effect on IL-8 release was reported when comparing the effect of TNFα on A549 cells A similar effect on IL-8 release was reported when comparing the effect of TNFα on A549 cells with the effect LPS on A-THP1. An anti-inflammatory potential of BUD (1 µM) and the BUD:HPβCD complex (1:25 µM) was observed with a lower potential of HPβCD to decrease IL-8 release (Figure 10).

0.001 versus untreated group; (\*), (\*\*), and (\*\*\*) correspond to *p* < 0.05, 0.01 and 0.001 versus H2O2 +

with the effect LPS on A-THP1. An anti-inflammatory potential of BUD (1 µM) and the BUD:HPβCD complex (1:25 µM) was observed with a lower potential of HPβCD to decrease IL-8 release (Figure

*Molecules* **2020**, *25*, x 12 of 21

**Figure 10.** IL-8 release by A549 cells after treatment with H2O2 + TNF-α for 2 h (**A**) and effect of the BUD:HPβCD complex versus BUD and HPβCD on H2O2 + TNF-α-induced IL-8 release (**B**). IL-8 release was measured in the extracellular medium by sandwich ELISA. Results on panel B were normalized relative to untreated cells (0%) and H2O2 + TNF-α-treated cells (100%). Each bar represents the mean ± SEM of 3 independent means of triplicated measures. (\*), (\*\*), and (\*\*\*), indicate, **Figure 10.** IL-8 release by A549 cells after treatment with H2O2 + TNF-α for 2 h (**A**) and effect of the BUD:HPβCD complex versus BUD and HPβCD on H2O2 + TNF-α-induced IL-8 release (**B**). IL-8 release was measured in the extracellular medium by sandwich ELISA. Results on panel B were normalized relative to untreated cells (0%) and H2O2 + TNF-α-treated cells (100%). Each bar represents the mean ± SEM of 3 independent means of triplicated measures. (\*), (\*\*), and (\*\*\*), indicate, respectively, *p* < 0.05, 0.01, and 0.001 versus non-treated cells (**A**) or H2O2+LPS-treated cells (**B**). BUD:HPβCD complex versus BUD and HPβCD on H2O2 + TNF-α-induced IL-8 release (**B**). IL-8 release was measured in the extracellular medium by sandwich ELISA. Results on panel B were normalized relative to untreated cells (0%) and H2O2 + TNF-α-treated cells (100%). Each bar represents the mean ± SEM of 3 independent means of triplicated measures. (\*), (\*\*), and (\*\*\*), indicate, respectively, *p* < 0.05, 0.01, and 0.001 versus non-treated cells (**A**) or H2O2+LPS-treated cells (**B**).

As HDAC2 is recruited by the activated glucocorticoid receptor to repress the transcription of

respectively, *p* < 0.05, 0.01, and 0.001 versus non-treated cells (**A**) or H2O2+LPS-treated cells (**B**). As HDAC2 is recruited by the activated glucocorticoid receptor to repress the transcription of proinflammatory genes [42] and to study the potential role of HDAC2 in the protection afforded by the BUD:HPβCD complex in comparison with BUD or HPβCD on IL-8 release, IL-8 release induced by TNF-α in conditions where cells were preincubated with or without trichostatin, a pharmacological HDAC2 inhibitor [43], was measured. We pretreated for 30 min A549 cells with increasing concentrations of trichostatin (0–250 nM) and determined IL-8 release after incubation for As HDAC2 is recruited by the activated glucocorticoid receptor to repress the transcription of proinflammatory genes [42] and to study the potential role of HDAC2 in the protection afforded by the BUD:HPβCD complex in comparison with BUD or HPβCD on IL-8 release, IL-8 release induced by TNF-α in conditions where cells were preincubated with or without trichostatin, a pharmacological HDAC2 inhibitor [43], was measured. We pretreated for 30 min A549 cells with increasing concentrations of trichostatin (0–250 nM) and determined IL-8 release after incubation for 2 h of cells with TNF-α (20 ng/mL) and BUD:HPβCD complex or BUD or HPβCD (Figure 11). proinflammatory genes [42] and to study the potential role of HDAC2 in the protection afforded by the BUD:HPβCD complex in comparison with BUD or HPβCD on IL-8 release, IL-8 release induced by TNF-α in conditions where cells were preincubated with or without trichostatin, a pharmacological HDAC2 inhibitor [43], was measured. We pretreated for 30 min A549 cells with increasing concentrations of trichostatin (0–250 nM) and determined IL-8 release after incubation for 2 h of cells with TNF-α (20 ng/mL) and BUD:HPβCD complex or BUD or HPβCD (Figure 11).

2 h of cells with TNF-α (20 ng/mL) and BUD:HPβCD complex or BUD or HPβCD (Figure 11).

**0 50 100 150 200 250 300 Trichostatin [nM] Figure 11.** Percentage of IL-8 released after A549 cells pretreatment for 30 min with trichostatin (TSA) and incubation for 2 h with TNF-α in presence of BUD:HPβCD complex, BUD or HPβCD. Results are **Figure 11.** Percentage of IL-8 released after A549 cells pretreatment for 30 min with trichostatin (TSA) and incubation for 2 h with TNF-α in presence of BUD:HPβCD complex, BUD or HPβCD. Results are expressed in percentage of IL-8 released. 100% corresponds to cells preincubated for 30 min with TSA and incubated for 2 h with TNF-α only. IL-8 release was measured in the extracellular medium by sandwich ELISA. Data are from 3 independent experiments in triplicates. ▼HPβCD; ♦ **Figure 11.** Percentage of IL-8 released after A549 cells pretreatment for 30 min with trichostatin (TSA) and incubation for 2 h with TNF-α in presence of BUD:HPβCD complex, BUD or HPβCD. Results are expressed in percentage of IL-8 released. 100% corresponds to cells preincubated for 30 min with TSA and incubated for 2 h with TNF-α only. IL-8 release was measured in the extracellular medium by sandwich ELISA. Data are from 3 independent experiments in triplicates. HHPβCD; BUD:HPβCD; BUD.

expressed in percentage of IL-8 released. 100% corresponds to cells preincubated for 30 min with TSA

and incubated for 2 h with TNF-α only. IL-8 release was measured in the extracellular medium by sandwich ELISA. Data are from 3 independent experiments in triplicates. ▼HPβCD; ♦ BUD:HPβCD; ■ BUD. IL-8 release induced by TNFα was markedly reduced (around 70%) by BUD and BUD:HPβCD whereas HPβCD alone did not shown any effect or a very slight effect. When trichostatin was used BUD:HPβCD; ■ BUD. IL-8 release induced by TNFα was markedly reduced (around 70%) by BUD and BUD:HPβCD whereas HPβCD alone did not shown any effect or a very slight effect. When trichostatin was used in preincubation to inhibit the HDAC2 activity, the IL-8 release was increased, in a dose-dependent fashion in the presence of BUD or BUD:HPβCD. BUD:HPβCD failed to improve the response of IL-8 release induced by TNFα was markedly reduced (around 70%) by BUD and BUD:HPβCD whereas HPβCD alone did not shown any effect or a very slight effect. When trichostatin was used in preincubation to inhibit the HDAC2 activity, the IL-8 release was increased, in a dose-dependent fashion in the presence of BUD or BUD:HPβCD. BUD:HPβCD failed to improve the response of glucocorticoids in the condition of HDAC2 inhibition. Again, no or a very slight effect was observed with HPβCD (Figure 11).

in preincubation to inhibit the HDAC2 activity, the IL-8 release was increased, in a dose-dependent fashion in the presence of BUD or BUD:HPβCD. BUD:HPβCD failed to improve the response of


**2. Materials and Methods**

#### *2.1. Power Plants Description*

The production of electricity from geothermal exploitation in Italy is concentrated in the Tuscany region. Currently, all the geothermal power plants have been built and operated by EGP, which manages 37 productive units, allowing for the production of about 5.8 TWh/y.

The geothermal area in Tuscany is divided in four districts: Larderello, Lago and Radicondoli (halfway from the province of Siena, Grosseto and Pisa) and, in the south Tuscany, the area of Mount Amiata (between Grosseto and Siena) [37]. The area of Monte Amiata is composed by two productive geothermal fields, namely Bagnore and Piancastagnaio. The Bagnore field is characterized by the presence of 2 power plants: Bagnore 3 and Bagnore 4, entirely constructed and operated by EGP. Bagnore 3 is a flash plant with 20 MWe of installed power producing 170 GWh/y of electric energy. Additionally, the plant is powered by a 1 MWe Organic Rankine Cycle (ORC) unit, which provides 6.8 GWh/y of additional electric energy. Bagnore 4 is powered by two 20 MWe groups, which can input 367 GWh/y to the electric grid. Thus, the electricity production from the Bagnore field is about 544 GWh/y. In addition to electric generation, heat delivery is also achieved by exploiting residual heat after turbine expansion. The total heat delivered to the final users is about 32 GWh/y.

The two power plants are connected to each other to enhance the performance of the whole system. Such an enhancement is reached in both power production and environmental compatibility of the geothermal power plants [38]. A shared steam network powering the two power plants, allows the optimization of the available steam flow, thus, maximizing the power output. The shared steam network also improves the environmental footprint: in case of maintenance operations to one of the three productive units, it is possible to reroute the overflowing steam towards the operating units, thus avoiding free release into atmosphere. The operator also equipped the power plants with oversized AMIS system, able to treat 150% of the entering fluid for each turbine. Such oversizing allows the system to also abate the emissions during flow rerouting for maintenance operations.


**4. Results and Discussion**

#### *4.1. Wheat Bran Characterization*

The micrographs of wheat bran fibers (Figure 2a) show that bran particles have various dimension. Mainly the bran powder consists of platelets having low aspect ratio that forms agglomerates having an average size around 250–500 micrometers. However smaller size fraction in large quantity can also be observed. In the SEM micrographs the wheat bran fibers showed a low aspect ratio and their morphology is similar to flakes.

Consequently, for the fibers aspect ratio distribution a flake geometry was assumed where the filler aspect ratio, *ar*, can be defined as the ratio between the average fiber diameter (*d*) (calculated on the larger platelets surface) and the mean thickness of the platelets (*h*) according to Equation (12) [54]

$$a\_{r\prime} \, plate \, lets = \frac{d}{h} \tag{12}$$

In Figure 2b-c a sharp peak can be observed in the range of 0–200 μm and 0–40 μm for the mean fiber diameter and fiber thickness distributions, respectively. Thanks to the fibers distribution the mean weighted fibers lengths for the calculation of the mean fibers aspect ratio was carried out. In particular, a mean weighted fiber diameter of 219.76 μm and a mean weighted fiber thickness of 51.40 μm were obtained that correspond to a mean fiber aspect ratio of 4.27. Consequently, the composites obtained belong to the family of very short fiber composites [27].

**Figure 2.** (**a**) SEM images at 200× of wheat bran fibers (**b**) average diameter distribution and (**c**) average thickness distribution.

In the infrared spectra (reported in Figure 3) the hydrophilicity of the wheat fibers is highlighted by the very sharp –OH groups stretching in the region of 3650–3000 cm−1. The peak at 3294 cm−1 corresponding to –OH stretching was attributed to specific intramolecular hydrogen bonds of cellulose II [65,66]. The infrared spectra displayed a small adsorption band at 2925 cm−1, typical of the stretching vibrations of the C–H bonds in hemicelluloses and cellulose. The bands at 1639 cm−1 and 1540 cm−1, attributable to amide I and amide II vibrations, can be ascribed at the presence of the protein fraction in bran. Moreover, the shoulder at 1639 cm−1 is attributable to the acetyl and uronic ester groups of hemicelluloses or to the ester linkage of carboxylic group of the ferulic and p-coumaric acids of lignin [67]. Adsorption bands can also be observed near 1639 cm−1 and they are attributed to deformation of the C=O groups of xylan [68] that is the main component of hemicellulose.

**Figure 3.** ATR spectrum of wheat bran fibers.


2.6. Experiments

The two pilot-scale columns were followed for 6 months under continuous flow conditions. The liquid flow rate was maintained at 3 Ld−1 . Woodwaste leachate percolated filters with a hydraulic load of 0.169 m3 m−2 d−1 . Air was applied upward at a flow rate of 5 m3 m−2 h−1 . Columns were fed with real woodwaste leachate, which presented a pH between 4.5 and 4.7 spiked to 1 μg mL−1 with eight phenolic compounds and operated at room temperature (20–25°C). A flow sheet of the pilot scale unit is described in Figure 2.

### 2.6.1. Pilot 1 (with mercuric chloride)

The bacterial activity was inhibited in this column using mercuric chloride (HgCl2) at 0.5 g L−1 in the fed leachate. Only physicochemical retention by sorption and volatilization are in operation and responsible for phenolic compounds removal in this column. Liquid influent and effluent were sampled each day for 6 months to establish the parameters variation profiles. pH and COD were determined daily for the first 3 months and each 2 days from the 4th month. Phenolic compounds were quantified each 2 days in the liquid influent and effluent and twice a week in the collected steam during all the operation period. Parameters profile variations are presented in Figures 4 and 5.

Figure 4. Physicochemical parameters variation in the effluent of column 1 (without bacterial activity).

Figure 5. Phenolic compounds profiles variation in the column 1 (without biological activity).

### <IP_ADDRESS>. Media without biological activity characterization

of the eight studied phenolic compounds was given as substrate when the biomass was acclimated and then the real woodwaste leachate was used for the biomass growth before use in the biofilter. The biomass growth and substrates utilization were followed by respirometric

Acclimation steps

1 2 345

V added (mL) 3 3 2 1 0

(% C) 100.00 96.63 90.54 76.13 0.00 ppm 0 2 4 6 8

V added (mL) 0 5 10 15 20 mg C 0 3.83 7.66 11.49 15.32 % (C) 0 3.37 9.46 23.87 100

AGV mg C 109.92 109.92 73.28 36.64 0.00

Phenol mg phenol 0 5 10 15 20

Total mg C 109.92 113.75 80.94 48.13 15.32

VFAs: 80 g L−1 (36.64 g-C/L); phenol: 1 g L−1 (0.766 g-C/L); nutrients: 65.86 g L−1 (0.052 g-N/L); volume of reactor: 2.5 L.

The two pilot-scale columns were followed for 6 months under continuous flow conditions.

Columns were fed with real woodwaste leachate, which presented a pH between 4.5 and 4.7 spiked to 1 μg mL−1 with eight phenolic compounds and operated at room temperature

The bacterial activity was inhibited in this column using mercuric chloride (HgCl2) at 0.5 g L−1 in the fed leachate. Only physicochemical retention by sorption and volatilization are in operation and responsible for phenolic compounds removal in this column. Liquid influent and effluent were sampled each day for 6 months to establish the parameters variation profiles. pH and COD were determined daily for the first 3 months and each 2 days from the 4th month. Phenolic compounds were quantified each 2 days in the liquid influent and effluent and twice a week in the collected steam during all the operation period. Parameters profile

(20–25°C). A flow sheet of the pilot scale unit is described in Figure 2.

. Woodwaste leachate percolated filters with a

.

. Air was applied upward at a flow rate of 5 m3 m−2 h−1

measurements during all the acclimation process.

378 Phenolic Compounds - Natural Sources, Importance and Applications

The liquid flow rate was maintained at 3 Ld−1

hydraulic load of 0.169 m3 m−2 d−1

Table 2. Acclimation of biomass steps.

2.6.1. Pilot 1 (with mercuric chloride)

variations are presented in Figures 4 and 5.

2.6. Experiments

Both conventional scanning electron microscopy (SEM) and environmental scanning electron microscopy (ESEM) characterized media of pilot 1, with mercuric chloride. The environmental SEM offers all of the performance advantages of a conventional SEM, but allows high resolution and the analysis of wet and environmental samples in their current state without preliminary manipulations. Analysis was performed on JEOL 840-A (MEB) instrument for conventional SEM and on JSM-6360 instrument at low voltage (30 V of acceleration voltage) and with different vacuum values for ESEM.


But what about the consistency of the sentence "**D**1*m* ∈ **D**2*m* holds for all *m* ≥ 1 "? Perhaps a method developed in [50] can be useful to solve this problem.

4. It would be interesting to define a generic extension of **L** in which, for instance, **D**1*m* ∈ **D**2*m* holds for all even *m* ≥ 1 but fails for all odd *m* ≥ 1, or vice versa.

Lemma 2 on page 8 presents a possible difficulty: If we have **D**1*n* ∈ **D**2*n* for some *n* ≥ 1 by means of the equality **D**1*n* = P(*ω*) ∩ **L**, then **D**1*m* ∈ **D**2*m* definitely *fails* for all *m* < *n*.

5. Another question considered by Tarski in [18] is related to the sets **D***k* = - *m* **D***km* (all elements of order *k* , definable by a formula of any order). Tarski proves that **D***k* ∈/ **D***k*+1 for all *k* ≥ 2, and leaves open the question whether **D**1 ∈ **D**2 . Similarly to the problem **D**1*m* ∈ **D**2*m* in Section 1.1, the *negative* answer **D**1 ∈/ **D**2 follows from the axiom of constructibility **V** = **L**, and hence is consistent with **ZFC**.

Prove the consistency of the sentences **D**1 ∈ **D**2 and **D**1 = P(*ω*) ∩ **L**.

#### **Supplementary Materials:** The following are available online at http://www.mdpi.com/2227-7390/8/12/2214/ s1 .

**Author Contributions:** Conceptualization, V.K. and V.L.; methodology, V.K. and V.L.; validation, V.K. and V.L.; formal analysis, V.K. and V.L.; investigation, V.K. and V.L.; writing original draft preparation, V.K.; writing review and editing, V.K.; project administration, V.L.; funding acquisition, V.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Russian Foundation for Basic Research RFBR grant number 18-29-13037.

**Acknowledgments:** We thank the anonymous reviewers for their thorough review and highly appreciate the comments and suggestions, which significantly contributed to improving the quality of the publication.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**

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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


**Process–Structure–Properties in Polymer Additive Manufacturing II**

Editors

**Swee Leong Sing Wai Yee Yeong**

MDPI Basel Beijing Wuhan Barcelona Belgrade Manchester Tokyo Cluj Tianjin

*Editors* Swee Leong Sing Department of Mechanical Engineering National University of Singapore Singapore Singapore

Wai Yee Yeong Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore

*Editorial Office* MDPI St. Alban-Anlage 66 4052 Basel, Switzerland

This is a reprint of articles from the Special Issue published online in the open access journal *Polymers* (ISSN 2073-4360) (available at: www.mdpi.com/journal/polymers/special issues/process structure polym additive manufacturing II).

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**1.1 Multiferroic BaTiO3**

The magnetoelectric (ME) effect—the induction of magnetization by an electric field and the induction of electric polarization by a magnetic field [1]. Multiferroic nanostructures have given recent advances in new type of memory devices including multistate data storage and spintronics [2]. BaTiO3 (BTO) is a rare single-phase multiferroic. In multiferroics, the magnetic order is due to exchange interactions between magnetic dipoles, which themselves originate from unfilled shells of electron orbitals. Similarly, the electric order is due to the ordering of local electric dipoles, elastic order is due to the ordering of atomic displacements due to strain. The three crystallographic phases of BTO are ferroelectric: rhombohedral <190 K, orthorhombic for 190 K< T < 278 K and tetragonal for 278 K < T < 395 K. At higher temperatures, BTO is a paraelectric. For tetragonal BTO (**Figure 1(b)**) having lattice constants: *a*(Å) = *b*(Å) = 3.99; *c*(Å) = 4.03; space group = P4*mm*, the displacement of Ti4+ ion along *c*-axis might be induced electrical polarization (ferroelectricity). It involved hybridization of charge among Ti cation (3d states) with O anions (2p states). In cubic phase, the Ba2+ is located at the centre of the cube with coordination number 12.

Since to the formation of ME random access memories (MERAMs), the main thing that required ME coupling via interfacial exchange coupling among a multiferroic and a ferromagnet, which can change the magnetization of the ferromagnetic coating with respect to a voltage (**Figure 1(a)**) [3]. For such MERAMs, an electric field is enabled by ME coupling could control the exchange coupling between multiferroic and ferromagnetic at the interface. This exchange coupling at the interface reins the magnetization of the ferromagnetic layer, and therefore the magnetization might be change with multiferroic electrical polarization. Therefore, for perovskite (ABO3) BTO, Ba2+ (A-site cation) induce the required distortion for ferroelectricity, while magnetism can be achieved by the doping such as TM = Cr, Mn, Fe, Co, Ni, Cu along B-site cation [4, 5].

#### **1.2 Spinel ferrites**

The spinel structure typically represented as AB2O4, where 'A' indicates fourfold coordinated tetrahedral sub-lattice sites and 'B' indicates six-fold coordinated octahedral sub-lattice (**Figure 1(c)**). There are 8 A-sites in which the metal cations are tetrahedrally coordinated with oxygen, and 16 B-sites, which possess octahedral coordination. Normal ferrites have divalent cations residing solely as the central ion on the tetrahedral sub-lattice with only trivalent Fe cations occupying octahedral sub-lattice sites. Harrisa and Sepelak [6] suggested superexchange interaction, the JBB is strong and negative indicating antiferromagnetic coupling between Fe3+–O2−–Fe3+ with octahedral sub-lattice cation spins largely canceling out. When

**95**

state is singlet 6

**Figure 1.**

**1.3 Diluted magnetic semiconductors**

*Ferromagnetism in Multiferroic BaTiO3, Spinel MFe2O4 (M = Mn, Co, Ni, Zn) Ferrite…*

the divalent cation resides on the [B] site and A and B ions share the balance of [B] and the totality of (A), the spinel is inverse: (A1-δBδ)[AδB2-δ]O4, where δ is the inversion degree, *i.e.*, NiFe2O4. Ferrite of the type NiFe2O4 (NFO), CoFe2O4 (CFO) and MnFe2O4 (MFO) with the spinel structure are magnetic ceramics which have potential in electronic and magnetic components [7]. The NFO has an inverse spinel structure for which Fe3+ ions occupied tetrahedral A-sites; whereas Fe3+ and Ni2+ ions are sit on octahedral B-sites. This NFO is ferrimagnetic material has magnetization originated by antiparallel spins on A- and B-sites. However, for normal spinel structure of CFO, Co is a divalent atom, occupying tetrahedral A-sites, while Fe is a trivalent atom, sitting on the octahedral B-sites. For MFO, the inverted spinel structure is partial for which the Mn2+ and Fe3+ ions with half-filled 3d shell (ground

*moments and their antiparallel alignment. Adopted from Harrisa and Sepelak [6].*

*(a) Schematic MERAM device in which the binary information is stored by the magnetization direction of the ferromagnetic layer (I & II), read by the resistance, Rp of the magnetic trilayer, and written by applying a voltage across the multiferroic ferroelectric-antiferromagnetic layer (FE-AFM). (b) Tetragonal crystalline structure of BTO, with a lattice ferroelectric distortion. (c) Spinel unit cell. Arrows represent magnetic*

S with spin = 5/2 with zero orbital momentum) and the crystal field

is not sufficient to split it [8]. The magnetic moment of MFO agrees well with Neel's

Recently, the realization of spin in DMS, semiconductor with substituted magnetic impurities (Fe, Co, Ni, Cu) has attracted great interest in design of spintronics devices like spin field-effect transistors, non-volatile memory devices, and programmable logic gates [10–13]. Among various DMS, ZnO is a promising spin

coupling scheme and has lower resistivity than CFO and NFO ferrites [9].

*DOI: http://dx.doi.org/10.5772/intechopen.82437*

*Ferromagnetism in Multiferroic BaTiO3, Spinel MFe2O4 (M = Mn, Co, Ni, Zn) Ferrite… DOI: http://dx.doi.org/10.5772/intechopen.82437*

#### **Figure 1.**

*Electromagnetic Materials and Devices*

**1.1 Multiferroic BaTiO3**

at localized magnetic impurities and electron–electron interactions. To use DMSs for practical spintronic devices, a relatively high concentration of magnetic elements needed in the semiconductor host, and a large ferromagnetism is required with a Curie temperature (Tc) above room temperature. The transition metal (TM) ferrites with a spinel structure (MFe2O4; M = Co2+, Ni2+, Cu2+, Zn2+, etc.) are used in a wide variety of technological applications such as magnetic memory devices and biomedicine. However, these spinel ferrites are the candidate materials for multiferroic heterostructure due to their excellent magnetic response. For such multiferroic heterostructures, the perovskite (BaTiO3, PbTiO3, BiFeO3, etc.) has an opportunity of higher piezoelectric coefficient that may pool with magnetostrictive materials

The magnetoelectric (ME) effect—the induction of magnetization by an electric field and the induction of electric polarization by a magnetic field [1]. Multiferroic nanostructures have given recent advances in new type of memory devices including multistate data storage and spintronics [2]. BaTiO3 (BTO) is a rare single-phase multiferroic. In multiferroics, the magnetic order is due to exchange interactions between magnetic dipoles, which themselves originate from unfilled shells of electron orbitals. Similarly, the electric order is due to the ordering of local electric dipoles, elastic order is due to the ordering of atomic displacements due to strain. The three crystallographic phases of BTO are ferroelectric: rhombohedral <190 K, orthorhombic for 190 K< T < 278 K and tetragonal for 278 K < T < 395 K. At higher temperatures, BTO is a paraelectric. For tetragonal BTO (**Figure 1(b)**) having lattice constants: *a*(Å) = *b*(Å) = 3.99; *c*(Å) = 4.03; space group = P4*mm*, the displacement of Ti4+ ion along *c*-axis might be induced electrical polarization (ferroelectricity). It involved hybridization of charge among Ti cation (3d states) with O anions (2p states). In cubic phase, the Ba2+ is located at the centre of the cube with coordination number 12. Since to the formation of ME random access memories (MERAMs), the main

thing that required ME coupling via interfacial exchange coupling among a multiferroic and a ferromagnet, which can change the magnetization of the ferromagnetic coating with respect to a voltage (**Figure 1(a)**) [3]. For such MERAMs, an electric field is enabled by ME coupling could control the exchange coupling between multiferroic and ferromagnetic at the interface. This exchange coupling at the interface reins the magnetization of the ferromagnetic layer, and therefore the magnetization might be change with multiferroic electrical polarization. Therefore, for perovskite (ABO3) BTO, Ba2+ (A-site cation) induce the required distortion for ferroelectricity, while magnetism can be achieved by the doping such as TM = Cr,

The spinel structure typically represented as AB2O4, where 'A' indicates fourfold coordinated tetrahedral sub-lattice sites and 'B' indicates six-fold coordinated octahedral sub-lattice (**Figure 1(c)**). There are 8 A-sites in which the metal cations are tetrahedrally coordinated with oxygen, and 16 B-sites, which possess octahedral coordination. Normal ferrites have divalent cations residing solely as the central ion on the tetrahedral sub-lattice with only trivalent Fe cations occupying octahedral sub-lattice sites. Harrisa and Sepelak [6] suggested superexchange interaction, the JBB is strong and negative indicating antiferromagnetic coupling between Fe3+–O2−–Fe3+ with octahedral sub-lattice cation spins largely canceling out. When

Mn, Fe, Co, Ni, Cu along B-site cation [4, 5].

**1.2 Spinel ferrites**

(CoFe2O4, NiFe2O4, ZnFe2O4, etc.) via lattice strain effect.

**94**

*(a) Schematic MERAM device in which the binary information is stored by the magnetization direction of the ferromagnetic layer (I & II), read by the resistance, Rp of the magnetic trilayer, and written by applying a voltage across the multiferroic ferroelectric-antiferromagnetic layer (FE-AFM). (b) Tetragonal crystalline structure of BTO, with a lattice ferroelectric distortion. (c) Spinel unit cell. Arrows represent magnetic moments and their antiparallel alignment. Adopted from Harrisa and Sepelak [6].*

the divalent cation resides on the [B] site and A and B ions share the balance of [B] and the totality of (A), the spinel is inverse: (A1-δBδ)[AδB2-δ]O4, where δ is the inversion degree, *i.e.*, NiFe2O4. Ferrite of the type NiFe2O4 (NFO), CoFe2O4 (CFO) and MnFe2O4 (MFO) with the spinel structure are magnetic ceramics which have potential in electronic and magnetic components [7]. The NFO has an inverse spinel structure for which Fe3+ ions occupied tetrahedral A-sites; whereas Fe3+ and Ni2+ ions are sit on octahedral B-sites. This NFO is ferrimagnetic material has magnetization originated by antiparallel spins on A- and B-sites. However, for normal spinel structure of CFO, Co is a divalent atom, occupying tetrahedral A-sites, while Fe is a trivalent atom, sitting on the octahedral B-sites. For MFO, the inverted spinel structure is partial for which the Mn2+ and Fe3+ ions with half-filled 3d shell (ground state is singlet 6 S with spin = 5/2 with zero orbital momentum) and the crystal field is not sufficient to split it [8]. The magnetic moment of MFO agrees well with Neel's coupling scheme and has lower resistivity than CFO and NFO ferrites [9].

#### **1.3 Diluted magnetic semiconductors**

Recently, the realization of spin in DMS, semiconductor with substituted magnetic impurities (Fe, Co, Ni, Cu) has attracted great interest in design of spintronics devices like spin field-effect transistors, non-volatile memory devices, and programmable logic gates [10–13]. Among various DMS, ZnO is a promising spin

source, since it epitomizes DMS with Tc well above room temperature. The DMS ZnO is a wide band gap that gained recent research in spintronics, due to an ability to change its optical and magnetic behavior with doping of TM = Fe, Co, Mn, Ni, Cu, Cr, or V ions and/or by intrinsic defects, such as oxygen vacancy (VO) and zinc vacancy (VZn). The DMS ZnO has wide applications included:

#### *1.3.1 Magnetic recording*

For read heads in magnetic disk recorders (computer components), read head senses the magnetic bits that are stored on the media, which is stored as magnetized regions of the media, called magnetic domains, along tracks (**Figure 2(a)**) [13]. Magnetization is stored as a "0" in one direction and as a "1" in the other. Although, there is no magnetic field emanating from the interior of a magnetized domain itself, uncompensated magnetic poles in the vicinity of the domain walls generate magnetic fields (sensed by the GMR element) that extend out of the media.

### *1.3.2 Nonvolatile memories*

The "Nonvolatile" refers to information storage that does not "evaporate" when power is removed from a system, *i.e.*, magnetic disks and tapes. Prinz [13] has recently demonstrated that GMR elements can be fabricate in arrays with standard lithographic processes to obtain memory that has speed and density approaching that of semiconductor memory, but is nonvolatile. A schematic representation of RAM that is constructed of GMR elements is shown in **Figure 2(b)**. The spindependent scattering of the carriers (electrons & holes) is minimized for parallel magnetic moment of the ferromagnetic layer, to induce lowest value of resistance. However, the highest resistance is the result of maximized spin-dependent scattering carriers via anti-aligned ferromagnetic layers. An external magnetic field could give the direction of magnetic moments, applied to the materials. The spin-valve structures of GMR set into series using lithographic (wires) termed as a sense line. This sense line has information storage due to resistance (resistance of elements). The sense line runs the current which is detected at the end by amplifiers because resistance changes in the elements.

#### **Figure 2.**

*A schematic representation of (a) GMR read head (I) that passes over recording media containing magnetized regions, (b) RAM that is constructed of GMR elements. Adopted from Prinz [13], (c) bound magnetic polaron (BMP), VZn, Oi trapped carriers couple with the 3d shell spins of TM ions within its hydrogenic orbit.*

**97**

tization, Ms (emu g−1

coupling constant, αME (mV cm−1

14.6, χ2

*Ferromagnetism in Multiferroic BaTiO3, Spinel MFe2O4 (M = Mn, Co, Ni, Zn) Ferrite…*

because of bound magnetic polaron (BMP) model [14]. The localized spins of the dopant ion interact with the charge carriers that are bound to a small number of defects such as oxygen vacancies, resulting into a magnetic polarization of the surrounding local moments. Since the magnetism in TM ions doped ZnO nanoparticles relates with exchange interactions between unpaired electron spins, that arising from the lattice imperfections such as oxygen vacancies, VO at the surface of the nanoparticles. Pal et al*.* [15] described BMP formation in Co doped ZnO and shown in **Figure 2(c)**. The electrons trapped in the defect vacancies undergo orbital coupling with the *d* shells of the adjacent divalent dopant ion and form BMP. In BMP model, the bound electrons (holes) hold in defect states that coupled through TM ions to overlap ferromagnetic regions, which responsible into high TC (due to formation of long-range ferromagnetic ordering) [16]. When the dopant ions are donors or acceptors, the exchange interactions are sp-d that would lead BMPs formation.

Generally, the room temperature ferromagnetism (RTFM) in DMS ZnO is given

The multiferroic, DMS and ferrites materials might be synthesized by methods

such as a sol-gel [17], chemical combustion [18], hydrothermal [19], metalloorganic decomposition (MOD) [20], conventional solid-state reaction [21], sol-gel

The sol-gel method is used to prepare pure BaTiO3 and BaTM0.01Ti0.99O [TM = Cr (BTO:Cr), Mn (BTO:Mn), Fe (BTO:Fe), Co (BTO:Co), Ni (BTO:Ni), Cu (BTO:Cu)] nanoparticles [4]. The TM ions in perovskite BTO structure highly influenced lattice constants to induce lattice strain and unit cell expansion, which responsible into defects vacancies formation. **Figure 3** shows the Rietveld refinement (Full-Prof program) of X-ray diffraction (XRD) patterns for pure and BaTM0.01Ti0.99O nanoparticles measured at room temperature. A polycrystalline with tetragonal BTO phase (space group:P4*mm*) is detected. The fitting parameters, Rp(%) = 6.7, 7.1, 6.7, 4.9, 9.1, 8.2 and 9.8, Rwp(%) = 3.2, 9.9, 9.2, 10.0, 12.5, 1.2 and

 = 1.1, 1.4, 0.81, 1.4, 3.3, 3.3 and 0.9 and distortion ratio, (*c*/*a*) = 1.00959, 1.00932, 1.00688, 1.00909, 1.00776, 1.00625 and 1.00508, respectively, refined for pure BTO and BTO with Cr, Mn, Fe, Co, Ni, Cu doping. Also, **Figure 3(a)** shows the tetragonal splitting of (200) diffraction peak at 2θ = 44.3–45.7°. The diffraction peak of pure BTO has shifted towards a lower diffraction angle with TM doping which supports the lattice strain in BTO. Such splitting of (200) peak might be confirmed the tetragonal phase formation. It is due to electrostatic repulsions between 3d electrons of Ti4+ ions and 2p electrons of O2− ions, the structure becomes distorted. It is also reported in Ref. [4] that the average particles size, from TEM, DTEM (nm) = 20 ± 3, 13 ± 1, 33 ± 5, 35 ± 3, 17 ± 1 and 47 ± 7, the value of saturation magne-

Oe−1

respectively, measured with Cr, Mn, Fe, Co, Ni, Cu doping into BTO.

) = 0.056, 0.042, 0.066, 0.035, 0.013 and 0.021, and the ME

) = 25.91, 11.27, 31.15, 16.58, 11.61 and 16.48,

*3.1.1 X-ray diffraction for BaTiO3 and BaTM0.01Ti0.99O3 nanoparticles*

*1.3.3 Ferromagnetism in DMS ZnO due to bound magnetic polarons*

*DOI: http://dx.doi.org/10.5772/intechopen.82437*

**2. Experimental methods**

**3. Result and discussion**

**3.1 Multiferroic systems of BaTiO3**

precipitation [22], thermal evaporation [23], etc.

*Ferromagnetism in Multiferroic BaTiO3, Spinel MFe2O4 (M = Mn, Co, Ni, Zn) Ferrite… DOI: http://dx.doi.org/10.5772/intechopen.82437*

*1.3.3 Ferromagnetism in DMS ZnO due to bound magnetic polarons*

Generally, the room temperature ferromagnetism (RTFM) in DMS ZnO is given because of bound magnetic polaron (BMP) model [14]. The localized spins of the dopant ion interact with the charge carriers that are bound to a small number of defects such as oxygen vacancies, resulting into a magnetic polarization of the surrounding local moments. Since the magnetism in TM ions doped ZnO nanoparticles relates with exchange interactions between unpaired electron spins, that arising from the lattice imperfections such as oxygen vacancies, VO at the surface of the nanoparticles. Pal et al*.* [15] described BMP formation in Co doped ZnO and shown in **Figure 2(c)**. The electrons trapped in the defect vacancies undergo orbital coupling with the *d* shells of the adjacent divalent dopant ion and form BMP. In BMP model, the bound electrons (holes) hold in defect states that coupled through TM ions to overlap ferromagnetic regions, which responsible into high TC (due to formation of long-range ferromagnetic ordering) [16]. When the dopant ions are donors or acceptors, the exchange interactions are sp-d that would lead BMPs formation.


**Author details**

Dragana Stanic-Vucinic1,2, Simeon Minic1,2, Milan R. Nikolic1,2 and Tanja Cirkovic Velickovic1,2,3,4\*

\*Address all correspondence to<EMAIL_ADDRESS>
1 University of Belgrade - Faculty of Chemistry, Center of Excellence for Molecular Food Sciences, Belgrade, Serbia

2 University of Belgrade - Faculty of Chemistry, Department of Biochemistry, Belgrade, Serbia

3 Ghent University Global Campus, Incheon, South Korea

4 Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium


**3. Formation mechanism of micro-size spherical AlN fillers**

In the above section, we summarized the influence of synthetic parameters on the morphology of final AlN products. It can be concluded that high N2 pressure, suitable additives, and appropriate reaction temperature were essential to synthesize the micro-sized spherical AlN fillers. Compared with the traditional CRN method, the as-synthesized AlN fillers exhibited two main obvious morphological changes: the growth of the particle size and the sphericity of the particle shape. In this section, we will discuss the formation mechanism of the two morphological changes based on the experimental results.


*4.1. Dataset*

The primary product of Pléiades satellite images were used for performing experimental analysis of the proposed method. The Pléiades program, which was launched by CNES (the French space agency), is the optical Earth imaging component of French–Italian ORFEO (Optical and Radar Federated Earth Observation). The Pléiades constellation consists of two satellites with VHR optical sensors. The Pléiades 1A launched on 17.12.2011 and Pléiades 1B launched on 2.12.2012. Both of the satellites provide 0.5 m spatial resolution for the Pan sensor and 2 m for MS sensor with 20 km swath width and 12 bit radiometric resolution [44].

The dataset used in this research consists of three Pleiades image scenes, which cover different landscape characteristics (Table 3). The locations of scenes are provided in Figure 3. Ten different sub frames were selected from these image scenes, in order to evaluate the performance of Pan sharpening methods for varying landscape characteristics and seasonal conditions (Table 4).

**Figure 3.** The locations of the Pléiades image scenes overlaid on Google Earth©.

**Table 3.** The description of three datasets.

Four sub frames cover rural areas that contain forests with different types of trees with varying heights and barren roads between them, and mountains and agricultural fields. Three sub frames cover urban areas that include complex buildings, roads and highways. Finally, three sub frames cover sub-urban areas that include all the complex buildings, factories, vegetation, roads, trees and bare soil parts to perform a precise survey on effects of the proposed method in Pan sharpening of vegetation, impervious and soil surfaces simultaneously.


*3.2. Imbalance Measurement*

In multi-label learning, a commonly used measure that evaluates the global imbalance of a particular label is *IRLbl*. Let |*Ci*| be the number of instances whose *i*-th label value is 1; *IRLbl* is then defined as follows:

$$IRLbl\_{j} = \frac{\max\{|c\_1|, |c\_2|, \dots, |c\_m|\}}{c\_i} \,. \tag{1}$$

Therefore, the larger the value of *IRLbl* for a label, the more minority class it is. For a node *vi*, its GMD is defined as follows:

$$GMD\_i = \frac{IRLbl\_j \cdot \left[B\_{i\bar{j}} = 1\right]}{\sum\_{j=1}^{m} \left[B\_{i\bar{j}} = 1\right]},\tag{2}$$

where [*Bij* = 1] means *vi* has the *j*-th label, and ∑*mj*=1 [*Bij* = 1] counts the number of labels that *vi* has.

The LMD of a node can be measured by the proportion of opposite class values in its local neighborhood. For *vi*, let *Nki* denote its k-hop neighbor nodes. Then, for label *cj*, the proportion of neighbors having an opposite class to the class of *vi* is computed as

$$S\_{ij} = \frac{\sum\_{\upsilon\_m \in N\_i^k} [B\_{ij} \neq B\_{mj}]}{|N\_i^k|} \,\,\,\,\tag{3}$$

where *S* ∈ R*n*×*m* is a matrix defined to store the local imbalance of all nodes for each label. Given *S*, a straightforward way to compute the LMD for *vi* is to average its *Sij* for all labels as follows:

$$LMD\_i = \frac{\sum\_{j=1}^{m} S\_{ij}[B\_{ij} = g\_j]}{m} \,. \tag{4}$$

where *gj* ∈ {0, 1} denotes the minority class of the *j*-th label. Namely, if |*cj*| ≥ 0.5 · *n*, *gj* = 1; otherwise, *gj* = 0. Here, *n* is the total number of vertices. Further, we group the global minority nodes into different types based on the LMD, and each type is identified correctly by the classifier with different difficulties. Following [50,51], we discretize the range [0, 1] of *LMDi* to define four types of nodes, namely safe (SF), borderline (BD), rare (RR), and outlier (OT), according to their local imbalance:

Based on the above categories, we are confident about generating new virtual samples for the global minority samples belonging to SF by imitating their features and labels to balance the distorted class distribution. The global minority samples belonging to BD are located in the decision boundary; hence, it is challenging to determine the label for virtual samples similar to them. Therefore, we keep the new samples unlabeled and use them to weaken the over-propagation of majority class features by taking advantage of the feature smoothing mechanism on the graph. The global minority samples belonging to RR/OT are more likely to be outliers and should not be selected as seeds to generate new samples.

Furthermore, for *vi*, we define two metrics: labeled seed probability (LSP) and unlabeled seed probability (USP) to describe the probability of being selected as a seed example to generate labeled synthetic nodes and unlabeled synthetic nodes, respectively. The seed probabilities (LSP/USP) are calculated as follows:

$$SP\_i = GMD\_i \cdot LMD\_i = \begin{cases} \displaystyle LSP\_{i\prime} & \text{if } v\_i \in \text{SF} \\ \displaystyle LSP\_{i\prime} & \text{if } v\_i \in \text{BD} \end{cases} \tag{5}$$

We compute the LSP and USP scores for all nodes and sort them in descending order. The top-ranked nodes (controlled by the hyper-parameter seed example rate *ρ*) will be selected as seed examples. A min-max normalization processes all the GMD and LMD scores to improve the computation stability.


**6.2 Care support**

Medical staff should use protective equipment when in contact with patients to avoid oral and respiratory infections. It is important to avoid holding or pulling the patient strongly and to limit injury to the epidermis (blood pressure measuring tape, electrocardiogram) [73]. Bacteria, viruses, and Candida fungi from three skin lesions should be cultured. Herpes infection should be excluded, especially in the case of severe mucous membrane lesions. Systemic antibiotics should be used if there is evidence of infection. In patients who have diarrhea or are unable to move, avoid getting dirty stools into skin lesions. Pay attention to using pain relievers if the pain is severe [1, 74].

Skin lesions should be washed with sterile warm water or physiological saline or with an antiseptic solution such as chlorhexidine (1/5000). A moisturizer with fatty properties such as vaseline, paraffin all over the skin, including the area that is growing granules should be applied. Scaly skin could be improved with topical antimicrobial drugs. Peeled epidermal fragments should be kept as a bio-bandage. The blisters should be aspirated and drained. Areas of skin that have lost the epidermis should be covered with non-stick gauze. Necrotic and infected epidermal fragments should be removed.

Eye mucosa is often damaged in SJS/TEN, if not detected, timely treatment can leave complications such as corneal ulceration, eye corner adhesions, pterygium adhesions, blindness [68]. Patients with SJS/TEN should be examined, treated, and monitored by an ophthalmologist from the acute stage of the disease until the disease has recovered. The mucous membrane of the vulva, vagina needs to be regular checkups and cleaning with antiseptic solutions, moist gauze. Topical corticosteroids can reduce inflammation [75]. Oral mucosa needs to be cleaned with antiseptic solutions such as chlorhexidine. Lips and mouth should be covered with moist gauze, corticosteroid solution can be applied to rinse the mouth, oral hemorrhages need to be controlled [76].

Peripheral and central lines should be placed in preserved areas. The fluid balance will be monitored by a catheter. The amount of fluid to compensate could be calculated by referring to the formula of Shiga and Cartotto [77]:2 ml kg−1 body weight/% of epidermal area detachment, necrotic.

If the patient can drink, oral rehydration should be maintained. Patients with SJS/ TEN need more nutrition than usual. If the mouth is severely damaged, eating is difficult, a nasogastric tube should be placed or parenteral nutrition. In the acute phase, the required calorie intake is 20–25 kcal kg−1 per day. During the recovery phase, the calorie requirement is 25–30 kcal kg−1 per day [1].

Patients with SJS/TEN have pain in the skin, especially at epidermal detachment sites. There are no studies on analgesic regimens in SJS/TEN. Therefore, analgesics according to the World Health Organization tiers can be used. Paracetamol or

synthetic opiate pain relievers (tramadol) should be used, but not non-steroidal antiinflammatory analgesics because of the risk of kidney and stomach damage. Some care procedures such as bathing and changing clothes require the use of analgesics.

Other treatments including proton pump inhibitors, anticoagulants, and drugs to treat leukopenia, anemia (granulocyte colony-stimulating factor, G-CSF) should be used appropriately.

#### **6.3 Specific medicines**

## *6.3.1 Intravenous immunoglobulin*

The basis for the use of IVIG in SJS/TEN are studies that show the role of Fas-FasL interaction in the mechanism of apoptosis of squamous cells [78]. FasL is a transmembrane protein of the TNF family that is expressed on the surface of cytotoxic T cells and natural killer cells. When cytotoxic T cells are activated, FasL is expressed, binds to its receptor on the target cell, activates the intracellular caspase, leading to uncontrolled destruction of the target cell. In addition, Fas can be separated from the cell membrane by metalloproteinase enzymes, producing soluble Fas from FasL, still maintaining the ability to bind to Fas receptors, causing apoptosis [6, 79]. High concentrations of normal immunoglobulin inhibit Fas-Fas ligand and apoptosis interactions through activation of anti-Fas antibodies.

In a systematic review and meta-analysis published by Huang in 2012 (all studies included at least 8 IVIG-treated SJS/TEN patients), cumulative estimates of risk mortality were determined, comparing IVIG and supportive care alone in patients with TEN and overlapping SJS/TEN. Statistical analysis was performed on the raw data to compare the clinical differences between high- and low-dose treatment in adult patients, and between pediatric and adult patients receiving IVIG. The mortality rate in the group of TEN and overlapping SJS/TEN patients treated with IVIG was 19.9%. Pediatric patients treated with IVIG had a lower mortality rate than adults (0% vs. 21.6%, p = 0.01). Adult patients treated with high dose IVIG had a lower mortality rate than those treated with low dose (18.9% vs. 50%, p = 0.02). However, the multivariable logistic regression model showed that IVIG dose was not correlated with mortality. But these results should be interpreted with caution due to limitations in the study design [79]. Following Huang's publication, a further study performed by Firoz et al. including 23 TEN patients treated with IVIG, demonstrated that IVIG did not improve survival compared with supportive care simply [80]. In 2013, Lee et al. published a retrospective analysis of 64 patients with overlapping SJS/TEN and TEN receiving IVIG. Based on the actual mortality compared with the SCORTEN estimated mortality, IVIG therapy showed no benefit. In addition, there was no difference between the high dose (>3 g/kg) and the low dose (<3 g/kg) [81].

#### *6.3.2 Systemic corticosteroid therapy*

Corticosteroids have been used to treat SJS/TEN for many years. Advocates emphasize the anti-inflammatory role of high doses of corticosteroids in the early stages of the disease. Opponents argue that systemic corticosteroids increase the risk of infection. Retrospective analysis of EuroSCAR data showed a lower mortality rate in the German group of patients receiving corticosteroids than in the supportive care group alone. To limit the side effects of long-term corticosteroid use, some authors use very high doses for a short time (pulse therapy) [82]. In the study by Kardaun and Jonkman, 12 patients treated with intravenous dexamethasone 100 mg or 1.5 mg/kg for 3 days had a lower mortality rate compared with the estimated mortality according to the SCORTEN [83]. Hirahara et al. had 8 patients with SJS/TEN treated with intravenous methylprednisolone 1000 mg for three consecutive days, followed by dose reduction with oral prednisolone or 2 days of methylprednisolone at half the initial dose. No patient died although the SCORTEN estimated mortality was 1.6. Serum biomarkers IFN-γ, TNF-α, IL-6, and IL-10 were measured in 5/8 patients. On the fourth day post-treatment, the mean concentrations of these cytokines decreased compared with pre-treatment, but only significantly changed for interferon-gamma (IFN-γ) and IL-6. On day 19, there was a significant reduction in both IFN-γ, TNF-α, and IL-6, whereas IL-10 levels were higher than before treatment [84].

#### *6.3.3 Cyclosporine*

Cyclosporine is an immunosuppressive drug, indicated in many diseases such as rheumatoid arthritis, psoriasis, Crohn's disease, nephrotic syndrome, anti-rejection in organ transplantation. The mechanism of action of the drug is to reduce the function of lymphocytes by forming a complex with cyclophilin to inhibit the activation of calcium channel phosphatase, thereby reducing the production of cytokines by T lymphocytes.

Its inhibitory effect on lymphocytes defines cyclosporine as the theoretical standard drug of action in SJS/TEN [1]. A study by Valeyrie-Allanore showed that in 29 SJS/TEN patients treated with cyclosporine (1.5 mg/kg/day in 2 divided doses for the first 10 days, then reduced to 1 mg/kg/day days for the next 10 days, the last 10 days is 0.5 mg/kg/day) is effective. No patient died, although the SCORTEN estimated number of deaths was 2.75/29 [85]. Singh reported 11 patients with SJS/ TEN who were treated with cyclosporine 3 mg/kg/day for 7 days, followed by dose reduction. This group was compared with 6 corticosteroid-treated SJS/TEN patients. In the cyclosporine group with a shorter hospital stay, the epithelialization rate was faster. Cyclosporine was more effective than corticosteroids when comparing SCORTEN estimated mortality. Kirchhof retrospectively studied 64 SJS/TEN patients treated with cyclosporine or IVIG (dose varied from patient to patient). Comparison of SCORTEN estimated mortality with actual mortality suggests a benefit of cyclosporine over IVIG [86]. Cyclosporine is well-tolerated, despite treatment in patients prone to hemodynamic instability and prerenal hypovolemia. It contributed to improved patient survival. Disease progression was slow and halting in the majority of patients [85, 87].

#### *6.3.4 Other methods of treatment*

Other therapies were used in SJS/TEN but in small sample sizes, no comparisons were made. Plasmapheresis is used in difficult-to-treat cases, and some reports have shown it to be effective [88, 89]. The immunoregulatory and regenerative role of G-CSF is used in the treatment of SJS/TEN (helps to stop hypersensitivity, stimulate epithelialization, control neutropenia) [90]. Biologics such as TNF-alpha antagonists have been conducted to improve the prognosis of SJS/TEN [23, 52]. Paradisi reported 10 patients with SJS/TEN treated with etanercept with a single dose of 50 mg subcutaneously. The study did not have a control group. All patients responded with a mean time of epithelialization of 8.5 days. Although the SCORTEN estimated mortality rate was 50%, no patient died [91].


**6. Conclusion**

HT screening is a comprehensive process to discover new drug targets using siRNA and drug candidates from small molecule libraries. Statistical evaluation of the assay perform‐ ance is a very critical step in HT screening data analysis. A number of data analysis methods have been developed to correct for plate-to-plate assay variability and systematic errors, and assess assay quality. Statistical analysis is also pivotal in the "hit" selection process from pri‐ mary screens and in the evaluation during confirmatory screens. While some of these meth‐ ods may be intuitively applied using spreadsheet programs (e.g., Microsoft Excel), others may require the development of computer programs using more advanced programming environments (e.g., R, Perl, C++, Java, MATLAB). Besides commercially available compre‐ hensive analysis tools, there are also numerous open-access software packages designed for HT screening data management and analysis for scientist with little or no programming knowledge. A short compilation of freely available analysis tools is listed in Table 3. The growing number of statistical methods will accelerate the discovery of drug candidates with higher confidence.

**Table 3.** Examples of open-access software packages for library management and statistical analysis of HT screening data.