The Reactivity and Reaction Pathway of Fenton Reactions Driven by Substituted 1,2-Dihydroxybenzenes

Fenton systems are interesting alternatives to advanced oxidation processes (AOPs) applied in soil or water remediation. 1,2-Dihydroxybenzenes (1,2-DHBs) are able to amplify the reactivity of Fenton systems and have been extensively studied in biological systems and for AOP applications. To develop efficient AOPs based on Fenton systems driven by 1,2-DHBs, the change in reactivity mediated by different 1,2-DHBs must be understood. For this, a systematic study of the reactivity of Fenton-like systems driven by 1,2-DHBs with different substituents at position 4 was performed. The substituent effect was analyzed using the Hammett constant (σ), which has positive values for electron-withdrawing groups (EWGs) and negative values for electron-donating groups (EDGs). The reactivity of each system was determined from the degradation of a recalcitrant azo dye and hydroxyl radical (HO·) production. The relationship between these reactivities and the ability of each 1,2-DHB to reduce Fe­(III) was determined. From these results, we propose two pathways for HO· production. The pathway for Fenton-like systems driven by 1,2-DHBs with EDGs depends only on the Fe­(III) reduction mediated by 1,2-DHB. In Fenton-like reactions driven by 1,2-DHBs with EWGs, the Fe­(III) reduction is not primarily responsible for increasing the HO· production by this system in the early stages

Summary of the parameter values (dependent variables) obtained from fitting the data on <i>A</i>. <i>ostenfeldii</i> growth to Eqs (1) and (2).

<p><i>X₁</i>: salinity and <i>X₂</i>: temperature (°C). The natural values of the experimental conditions are shown in brackets.</p

Second-order equations describing the effects of <i>T</i> and <i>S</i> on net toxin productions (PSP toxin and GYM-A analogue) by <i>A</i>. <i>ostenfeldii</i>.

<p>The coefficient of adjusted determination (<i>R</i>^<i>2</i>_<i>adj</i>) and the <i>F</i>-values (<i>F</i>_<i>1</i>, <i>F</i>_<i>2</i>, <i>F</i>_<i>3</i>, and <i>F</i>_<i>4</i>) are also shown. S: significant; NS: non-significant.</p

Experimental domain and codification of the independent variables in the factorial rotatable design.

<p>Experimental domain and codification of the independent variables in the factorial rotatable design.</p

Combined effects of temperature and salinity on toxin production by RSA.

<p>Theoretical response surfaces describing the combined effects of temperature and salinity on the specific (A) PSP toxin and (B) GYM-A analogue net production rates (<i>r</i>), and on the net production of (C) PSP toxins (pg cell^-1) and (D) GYM-A analogue (pg GYM-A eq. cell^-1) at the end of the <i>A</i>. <i>ostenfeldii</i> culture period.</p

Toxin-production kinetic profiles.

<p>Kinetics of net toxin production by strain AOTV-B4A cultivated under the environmental conditions defined by the factorial design summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143021#pone.0143021.t001" target="_blank">Table 1</a>. ○: PSP toxins (pg cell^-1), ●: GYM-A analogue (pg GYM-A eq cell^-1). Experimental data (symbols) were fitted to Eq (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143021#pone.0143021.e003" target="_blank">3</a>) (lines).</p

Optimal values of salinity and temperature (<i>S</i>_<i>opt</i> and <i>T</i>_<i>opt</i>) needed to obtain the maximum values (<i>Y</i>_<i>max</i>) using the equations shown in Table 5 and for the different dependent variables studied (toxin productions).

<p>Optimal values of salinity and temperature (<i>S</i>_<i>opt</i> and <i>T</i>_<i>opt</i>) needed to obtain the maximum values (<i>Y</i>_<i>max</i>) using the equations shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143021#pone.0143021.t005" target="_blank">Table 5</a> and for the different dependent variables studied (toxin productions).</p

Growth kinetic profiles.

<p>Growth kinetics of <i>Alexandrium ostenfeldii</i> strain AOTV-B4A cultivated under the environmental conditions defined by the factorial design summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143021#pone.0143021.t001" target="_blank">Table 1</a>. Experimental data (symbols) were fitted to Eq (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143021#pone.0143021.e001" target="_blank">1</a>) (lines).</p

Second-order equations describing the effects of <i>S</i> and <i>T</i> on the growth parameters of <i>A</i>. <i>ostenfeldii</i> AOTV-B4A (used in coded values according to the criteria defined in Table 1).

<p>The coefficient of adjusted determination (<i>R</i>^<i>2</i>_<i>adj</i>) and the <i>F</i>-values (<i>F</i>_<i>1</i>, <i>F</i>_<i>2</i>, <i>F</i>_<i>3</i> and <i>F</i>_<i>4</i>) are also shown. S: significant; NS: non-significant.</p

Population differences and the effect of vaginal progesterone on preterm birth in women with threatened preterm labor^*

<p><i>Objective</i>: Threatened preterm labor (tPTL) is a complication of pregnancy. Identification of women and clinical definition differs between countries. This study investigated differences in tPTL and effectiveness of vaginal progesterone to prevent preterm birth (PTB) between two countries.</p> <p><i>Methods</i>: Secondary analysis of a randomized controlled trial (RCT) from Argentina and Switzerland comparing vaginal progesterone to placebo in women with tPTL (<i>n</i> = 379). Cox proportional hazards analysis was performed to compare placebo groups of both countries and to compare progesterone to placebo within each country. We adjusted for baseline differences. Iatrogenic onset of labor or pregnancy beyond gestational age of interest was censored.</p> <p><i>Results</i>: Swiss and Argentinian women were different on baseline. Risks for delivery <14 days and PTB < 34 and < 37 weeks were increased in Argentina compared to Switzerland, HR 3.3 (95% CI 0.62–18), 54 (95% CI 5.1–569) and 3.1 (95% CI 1.1–8.4). In Switzerland, progesterone increased the risk for delivery <14 days [HR 4.4 (95% CI 1.3–15.7)] and PTB <37 weeks [HR 2.5 (95% CI 1.4–4.8)], in Argentina there was no such effect.</p> <p><i>Conclusion</i>: In women with tPTL, the effect of progesterone may vary due to population differences. Differences in populations should be considered in multicenter RCTs.</p