*2.1. Expression of the ICAM-1 and PECAM-1 Proteins in the Cremaster Muscle*

The microcirculation of the cremaster muscle in animals injected with the toxins Jar, Jar-C, and BnP1 presented positive labeling for both adhesion molecules compared to the microcirculation of the control group. When the levels of these proteins were quantified using ELISA, these three toxins induced a similar pattern of protein expression based on the level of fluorescence and time course of appearance (Figure 1A–E).

Toxins induced an increase ICAM-1 expression in the early stages (2 h and 4 h) compared with the control group (Figure 1A,B); however, at 24 h postinjection, the group that received BnP1 did not exhibit a morphological difference from the control group (Figure 1C). Quantification using the immunoassay confirmed the increase in the expression of ICAM-1 in groups injected with the toxins 2 and 4 h after the injection compared to the control group. A statistically significant difference was observed in animals injected with Jar between 2 and 4 h, and this pattern was exclusively induced by Jar (Figure 1D). Twenty-four hours after the injection of those three toxins, the concentration of ICAM-1 returned to a value similar to its initial level and did not differ from the control group (Figure 1D).

PECAM-1 expression in the microvasculature of cremaster muscle was significantly increased 4 h and 24 h after the injection of the three toxins when compared to the control group, as evidenced by the results of immunofluorescence assays (Figure 1B,C). The quantification of PECAM-1 levels using ELISA revealed constitutive expression in the control group, and an evident increase in the expression of this molecule was induced by the three toxins over time. This difference was greater at 24 h after toxin injection (Figure 1E). Notably, no nonspecific immunofluorescence labeling for the primary antibody was observed, since staining was also conducted using samples from in naive animals (data not shown).

**Figure 1.** Expression of ICAM-1 and PECAM-1 in the cremaster muscle at different time points. The panels present photomicrographs of immunofluorescence labeling analyzed using confocal microscopy at2h(**A**), 4 h (**B**) and 24 h (**C**) after the subcutaneous injection of PBS, Jar, Jar-C or BnP1 (0.5 μg/100 μL) in the mouse scrotum. Bar, 50 μm. Quantification of the protein levels of ICAM-1 (**D**) or PECAM-1 (**E**) in homogenates of cremaster muscle determined using ELISA. Absorbance was measured at 492 nm. The results are presented as the means ± S.E.M. (*n* = 5). \* *p* < 0.05 compared to the PBS group at any time point. Different letters (a, b, c) in the same group represent significant differences (\* *p* < 0.05).


**4. Conclusions**

Using a well-known methodology, it is concluded that the actions actually attacked the root causes that promoted plugging in the biomass system, especially in position M710. The great gain of the work was the low cost and agility in carrying out the proposed actions, surpassing expectations regarding the return that was thought to be possible to achieve. Therefore, the work reached the proposed objective of reducing the occurrences in the power boiler through simple and easy-to-apply solutions, showing that, in general, there are opportunities for solving problems that involve low cost and high return.


**9. The importance and uses of Schiff bases**

Today, with the development of spectral methods, the mechanisms of biochemical reactions can be explained. It has been determined that some reactions in living organisms proceed on Schiff bases, Schiff bases eliminate the toxic effects of aldehyde and amine components and bind free metal ions. The importance of Schiff bases increases day by day as they can be used in biological systems [79], chemical catalysis [80], medicine and pharmacy [81], chemical analysis, and new technologies [82, 83]

**Figure 21.** *Examples of biologically active Schiff bases.*

due to their properties. If we briefly summarize the reasons why Schiff bases have such a wide working area [84]:

In addition, due to their photochromism feature, they can be used in different fields, such as controlling and measuring radiation intensity, image systems, and optical computers [85]. Since the metal complexes of these compounds are colored substances, they are used as pigment dyestuffs in the dye industry, especially in textile dyeing [86, 87]. Moreover, they are widely used in the perfume and pharmaceutical industries. These compounds also have properties, such as synthetic oxygen carrier and intermediate in enzymatic reactions. They are also used as spectrophotometric reagents in analytical chemistry, as they react selectively and specifically to some metal ions. They can be used in aircraft construction, television and computer screens, and digital clock displays by taking advantage of the liquid crystal feature that occurs in some metal complexes [88].


*2.12. Total Phenolic Content*

The phenolic compound was measured according to [25]. In brief, 0.5 mL of extract was placed in a test tube, and 1 mL of Folin Ciocalteau reagent was added. The mixture was vortexed and stored for 5 min. After that, 2 mL of 2.5% Na2CO3 and 4 mL of distilled water were added to the mixture, immediately vortexed, and stored in a dark place for 30 min. The absorbance of the mixture was measured at 760 nm. The result of absorbance was plotted in a gallic acid standard curve. The result was expressed as mg gallic acid equivalent/100 g sample.

### *2.13. Total Flavonoid Content*

The flavonoid content was examined based on a previous report by [26]. An amount of 0.5 mL of extract was mixed with 0.3, 0.3, and 2 mL of 5% NaNO2, 10% AlCl3, and 1 M NaOH, respectively, in a 10 mL volumetric flask. After that, the distilled water was added to the volume. The mixture was then homogenized. The absorbance of the mixture was measured at 510 nm. The catechin and distilled water were used as standard and blank, respectively, and the result was expressed as mg catechin equivalent/g sample.


**2. Antioxidants**

The decreased antioxidant level is found in the diabetic patient. In a previous study, the total antioxidant capacity in the plasma of type 1 DM was shown to be 16% lower than that of normal subjects. Antioxidants counter the action of free radicals via several mechanisms such as degradation of free radicals, regulating the metals that stimulate the production free radicals, and scavenging the free radical. Lately, researchers found out the beneficial use of antioxidants from natural resources to replace synthetic ones.

Among the natural resources, data from laboratory studies showed that plants contain a large amount of antioxidant properties. Antioxidants occur in all parts of any higher plants (wood, bark, stems, pods, leaves, fruit, roots, flowers, pollen, and seeds). Plants with high levels of antioxidant have a significant role in improving oxidative stress disorders like DM. A number of findings showed the protective effect of the antioxidant ingredients against DM and achieved good results [10]. Hence, classical antioxidant could regulate the process and progress of DM and its complications. The good impact antioxidant activity toward DM and its associated complications has highly gained attention in the recent therapeutic society. Plenty of plants are rich in antioxidant property. To name it few, the plant or natural herbs such as *Piper sarmentosum* [11], *Momordica charantia* (bitter gourd) [12], and *Piper betel* [6], the common herbs used in improving the diabetic status enriched with antioxidant compounds. Noticeable active compounds like naringenin and quercetin are also important in managing hyperglycemic condition as well as regulating the oxidative stress–induced complication in DM. Vitamin C and E are well-known antioxidant agents for DM [13]. The antioxidant-enriched herbs not only increase the antioxidant level but also reduce the serum glucose level as well as improve the deteriorative changes in DM.


**5. Upper envelope**

8 Stochastic Control

*Xdhs* = 1

The unconditional upper prevision is obtained as a particular case when the conditioning

Coherent upper conditional probabilities are obtained when only 0-1 valued random variables

**Theorem 2.** *Let* (Ω, *d*) *be a metric space and let B be a Borel-measurable partition of* Ω*. For every B* ∈ *B denote by s the Hausdorff dimension of the conditioning event B and by hs the Hausdorff s-dimensional outer measure. Let m be a 0-1 valued finitely additive, but not countably additive, probability on* ℘(*B*) *such that a different m is chosen for each B. Thus, for each B* ∈ *B, the function*

*hs*(*B*) if 0 < hs

Let *B* be a set with positive and finite Hausdorff outer measure in its Hausdorff dimension *s*. Denote by *hs* the *s*-dimensional Hausdorff outer measure and for every *A* ∈ ℘(*B*) by *μ*∗

have that the upper conditional prevision *P*(·|*B*) is a functional defined on **L**(*B*) with values

**Example 1** Let *B* = [0, 1]. The Hausdorff dimension of *B* is 1 and the Hausdorff 1-dimensional measure *h*1 is the Lebesgue measure. Moreover *h*1[0, 1] = 1 then the coherent upper

We recall the definition of the Cantor set. Let *E*0 = [0,1], *E*1 = [0,1/3] ∪ [2/3,1], *E*2 = [0,1/9] ∪ [2/9, 1/3] ∪ [2/3,7/9] ∪ [8/9,1], etc., where *En* is obtained by removing the open middle third

**Example 2** Let *B* be the Cantor set. The Hausdorff dimension of the Cantor set is *s* = *ln*2

*hs*(*B*)

*hs*(*B*) = 1. Then the coherent upper conditional prevision is defined for every *X* ∈ **K**(*B*) by

*hs*(*B*) the upper conditional probability defined on ℘(*B*). From Theorem 1 we

*hs*(*B*) is a normalizing constant.

*B Xdhs* =

*B Xdhs* =

*B Xdh*1

*B Xdh ln*2 *ln*3

(B) < +∞

*B* integral represents *P*(*X*|*B*) since *P*(*X*|*B*) =

*B*(*A*) =

3*n* . The Cantor's set

*ln*3 and

(B) = 0, +∞

*hs*(*B*)

 *B Xdhs*.

1 *hs*(*B*)

*P*(*A*|*B*) = *hs*(*AB*)

*P*(*A*|*B*) = *m*(*AB*) if hs

event is Ω, that is *P*(*A*) = *P*(*A*|Ω) and *P*(*A*) = *P*(*A*|Ω).

are considered; they have been defined in [6] :

*is a coherent upper conditional probability.*

in � and the upper conditional probability *μ*∗

*Xdhs*. The number 1

conditional prevision is defined for every *X* ∈ **K**(*B*) by

*n*=0 *En*.

*P*(*X*|*B*) = 1

of each interval in *En*−1, so *En* is the union of 2*n* intervals, each of length 1

*P*(*X*|*B*) = 1

*hs*(*B*)

*defined on* ℘(*B*) *by*

*P*(*A*|*B*) = *hs*(*AB*)

*B* = 1 *hs*(*B*)

is the perfect set *E* = ∞

**4. Examples**

*and by*

*Xdμ*∗

 *B*

The last equality holds since each *B* is *hs*-measurable, that is *hs*(*B*) = *hs*(*B*).

A necessary and sufficient condition for an upper prevision *P* to be coherent is to be the *upper envelope* of linear previsions, i.e. there is a class *M* of linear previsions such that *P* =sup{*P*(*X*) : *P* ∈ *M*} [19, 3.3.3].

Given a coherent upper prevision *P* defined on a domain **K** the maximal coherent extension of *P* to the class of all bounded random variables is called [19, 3.1.1] *natural extension* of *P*.

The linear extension theorem [19, 3.4.2] assures that the class of all linear extensions to the class of all bounded random variables of a linear prevision *P* defined on a linear space **K** is the class *M*(*P*) of all linear previsions that are dominated by *P* on **K**. Moreover the upper and lower envelopes of *M*(*P*) are the natural extensions of *P* [19, Corollary 3.4.3].

Let *P*(·|*B*) be the coherent upper conditional prevision on the the class of all bounded Borel-measurable random variables defined on *B* defined in Theorem 1.

In Doria [9, Theorem 5] it is proven that, for every conditioning event *B*, the given upper conditional prevision is the upper envelope of all linear extensions of *P*(·|*B*) to the class of all bounded random variables on *B*.

**Theorem 3.** *Let* (Ω, *d*) *be a metric space and let B be a Borel-measurable partition of* Ω*. For every conditioning event B* ∈ *B let L*(*B*) *be the class of all bounded random variables defined on B and let P*(·|*B*) *be the coherent upper conditional previsionon the class of all bounded Borel-measurable random variables defined in Theorem 1. Then the coherent upper conditional prevision defined on L*(*B*) *as in Theorem 1 is the upper envelope of all linear extensions of P*(·|*B*) *to the class L*(*B*)*.*

In the same way it can be proven that the conjugate of the coherent upper conditional prevision *P*(·|*B*) is the *lower envelope* of *M*(*P*), the class of all linear extension of *P*(·|*B*) dominating *P*(·|*B*).