*Article* **Analysis of Mechanical Properties and Mechanism of Natural Rubber Waterstop after Aging in Low-Temperature Environment**

**Lin Yu 1,\*, Shiman Liu 2, Weiwei Yang 1 and Mengying Liu 1**

**Abstract:** In order to elucidate the aging performance and aging mechanism of a rubber waterstop in low-temperature environments, the rubber waterstops were placed in the freezing test chamber to accelerate aging, and then we tested its tensile strength, elongation, tear strength, compression permanent deformation and hardness at different times. Additionally, the damaged specimens were tested by scanning electron microscope, Fourier transform infrared spectroscopy and energy dispersive spectrometry. The results showed that with the growth of aging time, the mechanical properties of the rubber waterstop are reduced. At the same time, many protrusions appeared on the surface of the rubber waterstop, the C element gradually decreased, and the O element gradually increased. During the period of 72–90 days, the content of the C element in the low-temperature air environment significantly decreased compared with that in low-temperature water, while the content of O element increased significantly.

**Keywords:** rubber waterstop; low temperature; aging performance; microscopic examination; mechanism analysis


**Influence of Pickling Process on** *Allium cepa* **and** *Citrus limon* **Metabolome as Determined** *via* **Mass Spectrometry-Based Metabolomics**

**Mohamed A. Farag 1,2, \*, Ahmed F. Tawfike 3,4 , Marwa S. Donia 5 , Anja Ehrlich 6 and Ludger A. Wessjohann 6, \***

Academic Editors: Lillian Barros and Isabel C.F.R. Ferreira Received: 4 January 2019; Accepted: 17 February 2019; Published: 7 March 2019

**Abstract:** Brine, the historically known food additive salt solution, has been widely used as a pickling media to preserve flavor or enhance food aroma, appearance, or other qualities. The influence of pickling, using brine, on the aroma compounds and the primary and secondary metabolite profile in onion bulb *Allium cepa* red cv. and lemon fruit *Citrus limon* was evaluated using multiplex metabolomics technologies. In lemon, pickling negatively affected its key odor compound "citral", whereas monoterpene hydrocarbons limonene and γ-terpinene increased in the pickled product. Meanwhile, in onion sulphur rearrangement products appeared upon storage, i.e., 3,5-diethyl-1,2,4-trithiolane. Profiling of the polar secondary metabolites in lemon fruit via ultra-performance liquid chromatography coupled to MS annotated 37 metabolites including 18 flavonoids, nine coumarins, five limonoids, and two organic acids. With regard to pickling impact, notable and clear separation among specimens was observed with an orthogonal projections to least squares-discriminant analysis (OPLS-DA) score plot for the lemon fruit model showing an enrichment of limonoids and organic acids and that for fresh onion bulb showing an abundance of flavonols and saponins. In general, the pickling process appeared to negatively impact the abundance of secondary metabolites in both onion and lemon, suggesting a decrease in their food health benefits.

**Keywords:** *Allium cepa* red cv.; *Citrus limon*; pickling; volatiles; SPME; chemometrics

#### **1. Introduction**

Pickling—using food additives, i.e., a highly concentrated salt solution (brine)—is a well-known method for preserving foods including vegetables that has been used for thousands of years and remains in use today. Undoubtedly, the most unambiguous role of pickling for human nutrition is to make the nutrients naturally present in the original food materials more palatable while also preserving their quality. Nevertheless, pickling processes can have several effects on food nutritional qualities [1]. The effect of the pickling preservation method and storage time on vitamins and amino acid composition in garlic was reported by Montano et al., 2004 [2]. In addition, the influence of pickling with and without fermentation was revealed, with fermented products showing higher α-tocopherol, riboflavin, and total amino acid levels except for thiamine and arginine. Another study on Chinese cabbage reported that the nitrogenous content, viz. nitrate and nitrite, in vegetables was dramatically affected by fermentation [3]. Other studies [4,5] demonstrated a decrease in the level of nitrates during the natural fermentation of cabbage and radish. The risk of the reduction of nitrates to nitrite lies in the possible induction of methemoglobinemia [6]. The metabolic changes associated with pickling may thus develop some distinctive properties related to its organoleptic characters, shelf life, and/or safety [7,8]. In terms of human health benefits, pickled foods produced by fermentation have been recognized as protective for the gut [9] via the microbial and enzymatic processing of food ingredients. Fermentation can improve protein and fiber digestibility by improving micronutrient bioavailability and decaying anti-nutritional factors [10]. Fermentation processes can also reduce toxic compounds such as aflatoxins concurrent with the production of antimicrobial factors such lactic acid, bacteriocins, carbon dioxide, and ethanol, which prevent the growth of food-borne pathogens [11,12].

*Citrus* fruits are enriched in polyphenols which mainly include flavanones and, to a lesser extent, flavones, flavonols, coumarins, and phenolic acids, viz. ferulic, *p*-coumaric, sinapic, and caffeic acids [13]. Phenolic compounds are well known for their myriad health benefits, as they exhibit antioxidant, anticancer, and anti-inflammatory properties, mostly attributed to their remarkable free radical scavenging activities [14]. A study on four Tunisian *Citrus* varieties revealed the abundance of phenolic acids (73.13–86.40%) [15] among their secondary metabolite profiles, whereas camphene was found to be a major component in *C. limon*. *Citrus* fruit is also abundant in coumarins, limonoids, sterols, and flavonoids, which all exhibit various bioactivities [16].

Onion bulbs (*Allium cepa*) encompass a myriad of bioactive natural product classes which are linked to its health benefits, i.e., anticancer or chemo-preventive agents [17]; antimicrobial [18], antiviral [19], and antioxidant activities [20]; protective activities against cardiovascular diseases [21], diabetes [22], neurodegenerative disorders, and cataract formation [23,24]. Among the secondary metabolites found in onion, flavonoids, fructans, and organosulphur compounds were mainly found to mediate its health benefits [25–27]. We have previously reported on the flavor makeup of *A. cepa* red cv. grown in the Siwa Oasis, Egypt, revealing its enrichment in sulphur compounds [28]. Solid-phase microextraction (SPME) is regarded as a powerful analytical tool for volatiles extraction without solvent consumption and with no heat application, which aids in maintaining the original food aroma without the formation of artifacts as compared to steam distillation [29]. Further, confined direct MS analysis with real-time ion source and its applications in the analysis of volatile organic compounds of *Citrus limon* (lemon) and *Allium cepa* (onion) was reported [30]. In terms the secondary non-volatile metabolite composition of *A. cepa*, flavonols and acylated amino acids were the major forms as analyzed via UPLC-QTOFMS [28]. Metabolomics provides a holistic overview for the chemical profile of an organism (set of metabolites) exposed to different conditions. It can provide a shorter and more accessible route for visualizing metabolic difference in food matrices [31]. Significant strides have been made in the analysis of plant foods, mostly using different metabolomics platforms data [32]. The application of mass spectrometry (MS) coupled to an array of separation techniques [33,34] helps to simultaneously analyze a relatively large number of metabolites in a high-throughput, reproducible, and sensitive manner [35]. This study aims to explore the impact of pickling as a preservation method on the metabolite profile. Onion and lemon were employed as two different models considering their different compositional profiles, as these represent major food crops preserved using pickling. The effect of pickling, with and without fermentation, in terms of processing and storage time on organosulphur compounds of garlic has been previously reported [36]. This study reported the drawbacks of fermentation on the bioactive sulphur compounds, namely γ-glutamyl peptides and *S*-alk(en)yl-L-cysteine sulfoxides. For the comprehensive analysis of metabolites, solid-phase microextraction (SPME) coupled with GC-MS was employed for volatiles profiling, whereas UPLC-QTOFMS was used to capture the polar non-volatile secondary metabolites. Results

from the current study reveal for the apparent negative effect of pickling on the bioactive and flavor chemical composition in both lemon and onion.

#### **2. Results and Discussion**

#### *2.1. Profiling of Onion and Lemon Volatiles Using SPME/GC-MS and Multivariate Data Analysis*

Three independent biological replicates representing each specimen including fresh and pickled samples were extracted and analyzed under identical conditions. The volatile analysis of lemon samples (Figure 1) revealed for the presence of 31 volatile components, with monoterpene hydrocarbons representing the major class at ca. 96.6% and 97.5% in the fresh and pickled lemon, respectively (Table 1). The fresh lemon monoterepenes pool was characterized by a relatively high β-pinene level (33%) versus an enrichment of limonene and δ-terpinene in pickled lemon. With regard to oxygenated monoterpenes, α/β-citral (odor key marker) was remarkably reduced in pickled lemon and likely accounted for the lower aroma strength of pickled lemon. Furthermore, total sesquiterpene hydrocarbons were found to be slightly higher in fresh lemon with (*E*)-α-bergamotene as major component compared with a relative increase of (*E*/*Z*)-α-farnesene and β-bisabolene in pickled lemon. SPME/GC-MS volatiles analysis of fresh and pickled *A. cepa* onion bulbs detected the presence of 20 volatile components belonging to both sulphur and non-sulphur compounds (Figure 1). Sulphur volatiles were dominant with 96.6% and 98.1% in pickled and fresh samples, respectively. Several of the volatile components either disappeared or were reduced in pickled onion, as shown in Table 2. Moreover, significant increases in the levels of allyl methyl trisulfide, 3,5-diethyl-1,2,4-trithiolane, and 2-hexyl-5-methyl-3(2*H*)-furanone were detected in pickled onion. Such chemical change in volatiles makeup due to pickling is likely to affect its organoleptic properties such as taste and aroma. β δ α β α α β

**Figure 1.** Solid-phase microextraction (SPME)/GC-MS chromatogram of headspace volatiles collected from fresh and pickled onion bulb and lemon fruit.

**Table 1.** Relative percentiles of volatile components to total peak areas detected in fresh and pickled lemon fruit using SPME/GC-MS measurements (*n* = 3).

a denotes volatiles confirmed using the authentic standard in addition to RI and MS spectral matching.

**Table 2.** Relative percentiles of volatile components to total peak areas detected in fresh and pickled onion bulb using SPME/GC-MS measurements (*n* = 3).

a denotes volatiles confirmed using the authentic standard in addition to RI and MS spectral matching.

Multivariate data analysis was further applied to the volatiles abundance GC-MS dataset to visually demonstrate similarities and differences among specimens. Principal component analysis (PCA) was used as an unsupervised clustering model to highlight the variation based on volatiles abundance peak data. The PCA score plot (Figure S1) modeling fresh and pickled lemon showed no tight clustering of replicates, especially for pickled lemon. Consequently, supervised multivariate data analysis, i.e., OPLS, was employed for samples classification. OPLS-DA outscores PCA in the separation of the predictive variation from orthogonal variation and enhances data interpretation [37]. The OPLS-DA score plot (Figure 2A) showed better discrimination between the sample groups with the pickled group clustering separately from the fresh group. The S-loading plot derived from the OPLS-DA model is represented in Figure 2C. The figure highlights limonene and δ-terpinene as the most discriminatory aroma compounds for the pickled lemon, whereas β-pinene and α-citral were found distinctive for fresh lemon. Citral is a key flavor compound that accounts for lemon aroma [38]. Similarly, the OPLS-DA score plot of the pickled onion model (Figure 2C) discriminated between both sample groups, with 2-hexyl-5-methyl-3-(2*H*)-furanone and 3,5-diethyl-1,2,4-trithiolane (identified as markers for pickled onion) being highly correlated to the variation of the pickled onion. 2-Hexyl-5-methyl-3(2*H*)-furanone has previously been reported in "shallot" onion [39] as a decomposition fatty acid product derived from the onion lachrymatory factor [40], suggesting that sulphur compounds also undergo such degradation during pickling. Similarly, 3,5-diethyl-1,2,4-trithiolane may occur due to the thermal decomposition of cysteine [41], as reported in heat-prepared *Allium* essential oil [39].

limonene and δ whereas β pinene and α

"shallot"

**Figure 2.** OPLS-DA score plot derived from modeling volatile metabolites. The metabolites were analyzed via SPME/GC-MS, and were derived fresh and pickled lemon fruit (**A**) and onion bulb (**C**), each modeled one at a time (*n* = 3). The respective *S*-plots, (**B**) and (**D**), show the covariance p[1] against the correlation p(cor)[1] of the variables of the discriminating component of the OPLS-DA model. Cut-off values of *p* < 0.05 were used; selected variables are highlighted in the *S*-plot and identifications are discussed in the text.

#### *2.2. Profiling of Onion and Lemon Secondary Metabolites via UPLC-QTOFMS and Multivariate Data Analysis*

To assess changes in secondary metabolite compositions of brine-preserved lemon and onion, non-targeted profiling was conducted using ultra-performance liquid chromatography (UPLC) coupled to a photodiode array and high resolution QTOF-MS operated in the negative- and positive-ionization modes (Figure S2). It should be noted that extracts were analyzed in both positive and negative-ion electrospray ionization (ESI) MS modes (Supplementary Figure S2) as changes in ESI polarity can often circumvent or significantly alter competitive ionization and suppression effects, revealing otherwise suppressed metabolite signals. We have previously reported on the UPLC-MS characterization of onion bulb, as published elsewhere [28], and we now present an annotation of metabolites for lemon fruit. Compared to the positive-ion ESI mode, the negative-ion MS spectra revealed better sensitivity and more observable peaks in the case of lemon. Nevertheless, it did not yield as much fragmentation information as in the positive-ion mode. Thus, the positive-ion mode provided more structural context and the negative-ion mode greater sensitivity. In total, 14 peaks from lemon fruit were annotated based on their negative-ionization mass spectral data versus 32 in the positive-ion mode, see Table 3. This is the first profile of *C. limon* fruit methanol extract from Egypt obtained via a UPLC-QTOFMS platform and it is presented herein as part of this study towards the composition of fresh *C. limon*. LC-MS and NMR were reported for the metabolite profiling of citrus oil derived from Italy [42]. A representative UPLC-MS base peak chromatogram (BPC) of *C. limon* is shown in (Figure S2A). The identities, retention times (rt), UV characteristics, and observed molecular and fragment ions for individual secondary metabolites are presented in Table 3. A total of 49 metabolites were detected, of which 36 were annotated. Metabolites belonged to several natural product classes including flavonoids, limonoids, coumarins, and phenolic/organic acids.

#### 2.2.1. Phenolic Acids

As precursors for most phenolic metabolites, phenolic acids are commonly reported in metabolite profiling studies of functional foods, often conjugated with sugars as in the case of *C. limon*. Phenolic acids are also known to contribute, among others, to the flavor/taste of foods. In this study, two phenolic acid glycosides were found to be predominant in lemon fruit extracts, namely 6-*O*-Feruloyl-hexoside (peak 6, *m*/*z* 341.087 [M − H]− and citrusin E (peak 24, *m*/*z* 353.0872 [M − H]−) preferentially ionized in negative-ionization mode.

#### 2.2.2. Flavonoids

Flavonoids were detected as the most abundant class, represented by 18 peaks belonging to flavanone, flavone, and flavonols subclasses, principally as *O*-glycosides. In MS analysis, the nature of the sugars could be revealed by the elimination of the sugar residue, which would have a mass of 162 amu (hexose; glucose or galactose), 146 amu (rhamnose), or 132 amu (pentose; xylose or arabinose). The MS spectrum interpretation allowed for the annotation of hesperitin signals (*m*/*z* 301.27, C16H13O6 −) in peaks 37 and 39, luteolin (*m*/*z* 285.21, C15H9O6 −) in peaks 7 and 23, apigenin (*m*/*z* 269.21, C15H9O−) in peak 13, diosmetin (*m*/*z* 299.26, C16H11O6 −) in peak 14, and limocitirin (*m*/*z* 345.21, C17H13O8 −) in peaks 17, 18, and 26. The readily cleaved sugar moieties from aglycone yielded a fragment mass in these respective peaks. In contrast, several flavonoid peaks (8–12) showed intense molecular ion peaks, with [M − 90 − H]− and [M − 120 − H]− fragments exclusively in flavone peaks of the MSn spectra indicative of sugar cleavage in *C*-glycoside peaks 8–12. The fragmentation pathways most characteristic of *C*-glycosyl flavonoids include dehydration (−18 amu) and cross-ring cleavage (0,2 and 0,3) of the sugar moiety, i.e., −120 amu and −90 amu for the *C*-hexosides; −90 amu and −60 amu for the *C*-pentosides. Citrus fruits are rich dietary sources of flavonoids [43] and thus exhibit a wide range of pharmaceutical properties including anti-atherogenic, anti-inflammatory, antitumor, and antioxidant activities [44].

#### 2.2.3. Limonoids/Coumarins

Limonoids (abundant in lemon) belonging to tetranortriterpenes were annotated in peaks 48, 49, and 54 as glycosidic conjugates and in peak 65 as the aglycone "limonin", eluting much later at a relatively less polar eluent composition. This the first report of methyllimonexic acid in *C. limon*. Aside from their bitterness, imparting their taste to lemon, limonoids are regarded as an important constituent in food diets including *Citrus* fruit owing to their anti-obesity and anti-hyperglycemic effects [45]. Several coumarins (furano-type) were also detected, associated with peaks 56 (*m*/*z* 201.0186 [M − H]−), 62 (*m*/*z* 371.1488 [M − H]−), and 75 (*m*/*z* 297.1519 [M − H]−) and annotated as bergaptol, 6 ′ ,7′ -dihydroxybergamottin, and geranyloxycoumarin, respectively. Lipophilic coumarins acylated with a fatty acid group and eluting in the fatty acid region were also assigned in peaks 44, 45, and 47. Except for bergapten and dihydrobergamotin octanal acetal, these coumarins are annotated for the first time in *C. limon* and might also account for the food properties or health effects observed in grapefruit.

The UPLC-QTOFMS dataset was further subjected to multivariate data analysis to help determine which analytical platform provides a better prediction of pickling impact on *Allium* and *Citrus* metabolism. PCA was initially constructed to reveal for the metabolites variation among fresh and pickled specimens based on the abundance of peaks. The PCA score plots (Figure S3a,b) demonstrated a clear segregation between the fresh and pickled product in both lemon and onion with a total covered variance of 86% and 94%, respectively. The OPLS-DA analysis was further employed to identify metabolites that were highly correlated with the sample type. Compared to GC-MS, the UPLC-QTOFMS-derived OPLS model was found to be more predictive of the assessment of pickling, as revealed from the prediction power of their respective models. However, it should be noted that in contrast to the GC-MS-based model, the identified variant masses in case of UPLC-QTOFMS were based on MS spectral interpretation and not confirmed with authentic standards. A clear separation was detected from the OPLS-DA score plot (Figure 3A,C) for lemon and onion. The S-loading plot of lemon (Figure 3B) revealed the presence of xyloccensin, citric acid, and its methyl ester as the most distinctive markers for fresh lemon. In contrast, onion fresh bulb was discriminated from the pickled one by the abundance of steroidal saponins in addition to quercetin glycosidic conjugates (Figure 3D). Xyloccensin exhibits an anti-hyperglycemic activity [46] and a decrease in its levels could ultimately affect lemon benefits. Moreover, the benefits of *Allium's* polyphenols, i.e., quercetin glycoside and diglycoside, are well recognized [47] and a decrease in their levels was also observed in the case of *A. cepa* red cv. examined herein. Whether these metabolites get solubilized in the brine solution surrounding the bulb or get degraded has yet to be determined. *'s*

**Figure 3.** OPLS-DA score plot derived from modeling primary and secondary metabolites analyzed using UPLC-QTOFMS. Metabolites were derived fresh and pickled lemon fruit (**A**) and onion bulb (**C**), each modeled one at a time. The respective *S*-plots, (**B**) and (**D**), show the covariance p[1] against the correlation p(cor)[1] of the variables of the discriminating component of the OPLS-DA model. Cut-off values of *p* < 0.05 were used; selected variables are highlighted in the *S*-plot and identifications are discussed in the text.

To assess the validity of the UPLC-MS based models, Q2 and R2 values of all calculated models were found to be larger than 0.5 and close to 1. The permutation diagnostic analysis of 20 iterations provided a reference distribution of R2/Q2 values and hence indicated the statistical significance of these parameters, with most models showing a regression line crossing zero, with negative Q2 and R2 values close to 1, which signifies the model validation. Also, the *p*-value for each OPLS-DA model was calculated using CV-ANOVA and all *p*-value were below 0.005 in the pickled models of lemon and onion (Supplementary Figures S4 and S5). Nevertheless, the models derived from the volatiles GC-MS dataset exhibited lower model validation, showing smaller R2 and Q2 values and with *p*-values higher than 0.05, suggesting that the UPLC-MS-derived models provided a better assessment of the pickling impact on both foods

#### *2.3. Onion and Lemon Primary Metabolite Profiling Using GC-MS*

Although UPLC-QTOFMS revealed the variation in organic acids, viz. citric acid and its methyl derivative, as a major contributor to the segregation of pickled lemon from fresh ones, such a platform is not optimized for primary metabolite profiling [48]. To provide a more sensitive analysis of primary metabolites, viz. sugars and amino acids, compared to reversed-phase UPLC-QTOFMS, GC-MS was adopted for primary metabolite profiling in extracts prepared from fresh and pickled tissues. GC-MS analysis detected 52 primary metabolites belonging to organic acids, amino acids, fatty acids, sugars, and inorganic and nitrogenous compounds (Figure 4, Table S1). Primary metabolite analysis revealed a remarkable decrease in the total amount of organic acids, amino acids, and inorganic and nitrogenous compounds in the pickled tissue of both onion and lemon. In contrast, sugars and fatty acids were the major primary metabolites in pickled samples. Particularly in onion, fresh tissue was rich in malic acid (12.6%), proline (7%), fructofuranose (27%), and mannopyranose (11.6%). On the other hand, pickled onion showed dominancy in sugars, viz. maltose (16.3%) and sucrose (38%). In lemon, fresh tissue was also predominated by organic acids, viz. citric acid (37%), and sugar, viz. sucrose (28%), accounting for the sour taste of lemon concurrent with an abundance of sugar alcohol, viz. myo-inositol (21.9%) and fructofuranose (47%). A decrease in citric acid and its methyl ester levels in pickling can explain the less sour taste observed in pickled lemon and is in agreement with the UPLC-QTOFMS results. However, citric acid is considered a natural preservative that aids in smooth digestion and helps dissolve kidney stones [49]. Also of interest is the different sugar profile in the pickled product being more dominated by sugar alcohols, viz. myo-inositol, and monosaccharides, viz. fructose, compared to disaccharides in the fresh product, viz. sucrose. A decrease in disaccharide levels upon pickling in lemon could be attributed to the chemical hydrolysis of sucrose upon storage and especially due to the acidic nature of lemon, as an such effect was not observed in case of pickling *Allium* bulb. Sugar alcohols exhibit higher thermal stability and do not undergo any Milliard reaction compared to sugars [50].

**Figure 4.** GC-MS chromatogram of silylated primary metabolites analyzed from fresh and pickled onion bulb and lemon fruit.

#### **3. Materials and Methods**

#### *3.1. Plant Material*

*Allium sativum* and *A. cepa* red cv. bulbs were collected fresh from the field at Siwa Oasis, Egypt during the month of May 2016. Lemon fruit was collected at the ripe stage from trees grown in Behira governorate, Egypt during the month of May 2016.

#### *3.2. Pickling Protocol*

Preparing pickled lemon and onion was made by packing directly with acidified brine after blanching. Before processing, defective fruits or bulbs were discarded. Lemon fruit and pealed onion bulbs were blanched separately in water at 90 ◦C for 5 min and immediately packed in dark glass jars that were closed tight, containing acidified brine solution using 5% acetic acid. Brine was prepared by dissolving NaCl in water at a concentration of 15%. Both pickled products were stored in a dark place away of light at room temperature for four weeks.

#### *3.3. Chemicals and Fibers*

SPME fiber of stableflex coated with divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS, 50/30 µm) was purchased from Supelco (Oakville, ON, Canada). All chemicals and standards were purchased from Sigma Aldrich (St. Louis, MO, USA). Acetonitrile and formic acid (LC–MS grade) were obtained from J.T. Baker (Avantor, Netherlands). MilliQ water was used for UPLC-PDA-ESI-TOF-MS analysis.

#### *3.4. Headspace Volatiles Analysis of C. limon and A. cepa Bulbs*

The headspace-solid phase microextraction (HS-SPME) volatile analysis was carried out as mentioned previously [28]. (*Z*)-3-hexneyl acetate, dissolved in water to make a final concentration of 2 µg per 1.5-mL SPME screw cap vial, was used to spike 100 mg of dried, finely ground peeled bulbs of onion and lemon fruit placed in 1.5-mL glass vials. The SPME fiber was soaked in a vial containing plant material and placed in an oven of 50 ◦C for 30 min. The fiber was successively withdrawn into the needle and then injected into the injection port of the gas chromatography-mass spectrometer (GC-MS). A system blank containing no plant material was run as a control. SPME fibers were desorbed at 210 ◦C for 1 min in the injection port of a Shimadzu Model GC-17A gas chromatograph interfaced with a Shimadzu model QP-5000 mass spectrometer (Kyoto, Japan). Volatiles were separated on a DB5-MS column (30 m length, 0.25 mm inner diameter, and 0.25 µm film) (J & W Scientific, Santa Clara, CA, USA). Injections were made in the splitless mode for 30 s. The gas chromatograph was operated under the following conditions: injector 220 ◦C, column oven 38 ◦C for 3 min, then programmed at a rate of 12 ◦C/min to 180 ◦C, maintained at 180 ◦C for 5 min, and finally ramped at a rate of 40 ◦C min−1 to 220 ◦C and maintained for 2 min. He was used as the carrier gas at 1 mL/min−1 . The transfer line and ion-source temperatures were adjusted to be 230 and 180 ◦C, respectively. The HP quadrupole mass spectrometer was operated in the electron ionization mode at 70 eV. The scan range was set at *m*/*z* 40–500. Peaks were deconvoluted using AMDIS software (Gaithersburg, MD, USA www.amdis.net). Volatile components were identified by matching their retention indices (RI) relative to n-alkanes (C6–C20), as well as mass comparison to NIST and WILEY library databases and with standards.

#### *3.5. GC-MS Analysis of Silylated Primary Metabolites in Fruit Pulp and Skin*

Freeze-dried fruit or bulb powders (100 mg) were extracted by adding 5 mL 50% MeOH. Then, 100 µL of this 50% aqueous extract was evaporated under nitrogen until dryness was reached. Next, 150 µL of *N*-methyl-*N*-(trimethylsilyl)-trifluoroacetamide (MSTFA) was added and incubated at 60 ◦C for 45 min for derivatization. The primary metabolites were analyzed using GC-MS. Silylated products were purified on an Rtx-5MS (30 m length, 0.25 mm inner diameter, and 0.25 µm film) column. Injections were made in a (1:15) split mode with the following conditions: injector 280 ◦C, column oven 80 ◦C for 2 min, rate 5 ◦C/min to 315 ◦C, maintained at 315 ◦C for 12 min. He was used as the carrier gas at 1 mL/min−1 . The transfer line and ion-source temperatures were set to 280 and 180 ◦C, respectively. Compounds were identified as described in [51].

#### *3.6. Extraction Procedure and Sample Preparation for UPLC-PDA-MS Analysis*

Dried lyophilized food material was grounded separately in a mortar with liquid nitrogen. A powdered aliquot (ca. 30 mg) was then homogenized with 2.5 mL 70% MeOH containing 5 mg/mL umbelliferone (internal standard) with sonication for 30 min. Extracts were vortexed, centrifuged at 3000× *g* for 30 min to remove debris, and stored. Chromatographic separation was performed on an Acquity UPLC system (Waters Corp., Milford, MA, USA) equipped with an HSS T3 column (100 × 1.0 mm, particle size 1.8 mm; Waters Corp.) applying the following binary gradient at a flow rate of 150 mL/min: 0 to 1 min, isocratic 95% A (water:formic acid, 99.9:0.1, *v*/*v*), 5% B (acetonitrile:formic acid, 99.9:0.1, *v*/*v*); 1 to 16 min, linear from 5 to 95% B; 16 to 18 min, isocratic 95% B; 18 to 20 min, isocratic 5% B.

#### *3.7. GC-MS and UPLC-QTOFMS Data Processing for Multivariate Analysis*

MS peak abundance of volatiles and secondary metabolites were extracted using MET-IDEA software with default parameter settings for GC-MS and LC-MS files [52]. The aligned peak abundance data table was normalized to a spiked internal standard and further exported to principal component analysis (PCA) and partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P version 13.0 software package (Umetrics, Umeå, Sweden). All variables were mean-centered and scaled to Pareto variance.

#### **4. Conclusions**

Pickling using brine, an old traditional process used to preserve food products, was investigated for the first time using an MS-based metabolomics approach in two food materials—lemon and onion. Metabolomics was effectively implemented to highlight the similarities and differences between fresh and pickled products. Chemical analysis revealed a decline in lemon sensory volatiles, i.e., α,β-citral, as well as the degradation and rearrangement of sulphur compounds in onion to generate 2-hexyl-5-methyl-3(2*H*)-furanone and 3,5-diethyl-1,2,4-trithiolane, which are sulphur rearrangement products. A marked decrease in citric acid levels in lemon is likely to account for the less sour taste of its fruit. Nevertheless, it should be noted that the chemical changes observed in this study need to be further complemented with a sensory analysis to prove whether they are ultimately reflected in changes in aroma or taste. The impact of pickling on the non-volatile polar bioactive metabolites was revealed via UPLC-QTOFMS analysis and suggested for a lower health value of pickled product relative to the fresh specimens. The effect of blanching as part of the pickling was also not separately assessed, as samples were only analyzed after the pickling step.

**Supplementary Materials:** The followings are available online, Table S1: Relative percentiles of silylated primary metabolites detected in fresh and pickled onion bulb and lemon fruit using GC-MS measurements; Figure S1: SPME/GC-MS-based PCA score plot derived from modeling the pickling effect on lemon fruit to assess the effect of pickling on metabolite composition; Figure S2. UPLC-QTOFMS chromatogram of metabolites analyzed from fresh and pickled lemon fruit (A) and onion bulb (B) in negative- and positive-ionization modes, showing qualitative differences upon pickling in each examined food; Figure S3: UPLC-QTOFMS-based PCA score plot derived from modeling the pickling effect on lemon fruit (A) and onion bulb red cv. (B) separately to assess the effect of pickling on metabolite composition.

**Author Contributions:** M.A.F. and L.A.W. conceived and designed the experiments; M.A.F. and A.E. performed the experiments and the measurements; A.F.T. wrote the manuscript, M.S.D. performed the data analysis; M.A.F. revised the paper.

**Funding:** Mohamed A. Farag wishes to thank the Alexander von Humboldt foundation, Germany for the financial support and the American University of Cairo Internal Research Support Grant (RSG1-18).

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

#### **References**

**Sample Availability:** Samples of the compounds are not available from the authors.

© 2019 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/).

*Article*


**Association between Nutrient-Based Dietary Patterns and Bladder Cancer in Italy**

**Valeria Edefonti 1 , Carlo La Vecchia 1 , Matteo Di Maso 1 , Anna Crispo 2 , Jerry Polesel 3 , Massimo Libra 4 , Maria Parpinel 5 , Diego Serraino 3 , Monica Ferraroni 1,**† **and Francesca Bravi 1,\* ,**†

Received: 14 April 2020; Accepted: 25 May 2020; Published: 28 May 2020

**Abstract:** Limited knowledge is available on dietary patterns and bladder cancer risk. We analyzed data from an Italian case-control study carried out between 2003 and 2014, including 690 incident bladder cancer cases and 665 hospital-controls. We derived nutrient-based dietary patterns applying principal component factor analysis on 28 selected nutrients. We categorized factor scores according to quartiles, and estimated the odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) through logistic regression models, adjusted for major confounding factors. We identified four dietary patterns named "Animal products", "Vitamins and fiber", "Starch-rich", and "Animal unsaturated fatty acids". We found an inverse association between the "Vitamins and fiber" pattern and bladder cancer (OR = 0.70, 95% CI: 0.48–0.99, IV versus I quartile category). Inverse relationships of borderline significance were also found for the "Animal products" and the "Animal unsaturated fatty acids" dietary patterns. No significant association was evident for the "Starch-rich" pattern. The current study allowed us to identify major dietary patterns in this Italian population. Our study confirms available evidence and shows that scoring high on a fruit-and-vegetables pattern provides beneficial effects on bladder cancer risk.

**Keywords:** bladder cancer; case-control study; dietary patterns; diet; factor analysis

### **1. Introduction**

Bladder cancer accounted for about 550,000 new cases worldwide in 2018 and ranked 15th among the causes of cancer mortality [1]. Tobacco smoking is the major recognized risk factor for this neoplasm, accounting for 28% of male cases and 18% of female cases in Europe, and 21% and 16%, respectively, in the USA [2]. Other well-known risk factors are past occupational exposures to aromatic amines, high level of arsenic in drinking water, and *Schistosoma haematobium* and other urinary tract infections, whereas the role of other lifestyle factors needs to be clarified [3–5]. Diet has been involved in the development of bladder cancer because the metabolites of the ingested foods have direct contact with bladder mucosa [6]. However, the role of specific foods and nutrients is still unclear, and the World

Cancer Research Fund updated report indicates that only limited/suggestive evidence has been reached for a favorable role of vegetables and fruit consumption and tea drinking, while limited/non-conclusive evidence was available for the other dietary items [7].

Most studies have investigated single foods or nutrients, while only a few studies have used *a priori* [8–11] or *a posteriori* dietary patterns [12,13] to describe dietary habits as a complex behavior and to assess their relationship with bladder cancer risk. Previous analyses of selected aspects of diet in the present Italian population showed an unfavorable role of meat consumption (particularly stewed and roasted meat) [14], carbohydrates and glycaemic load [15], and an inverse relationship with vegetables, milk/yogurt [14], and flavones and isoflavones [16]. Considering dietary habits as a whole in the same population, bladder cancer was positively associated with a pro-inflammatory diet [17] and inversely related to a Mediterranean diet [18].

A national food consumption survey conducted in Italy in early 2000 showed that cereals represented the primary source of energy (providing ~38% of energy), followed by oils and fats (~17%, mainly from oils), and milk products (~13%); meats and fish provided a limited contribution (~9% and 2% of energy, respectively) [19]. Cereals were the primary source of fiber, providing a fiber intake comparable to the one given by the sum of fruit and vegetables [19]. However, the mean daily intake of vegetables, legumes, and fruit was below the recommendations provided by the World Cancer Research Fund [20].

To further investigate the role of overall dietary habits on bladder cancer risk, we derived *a posteriori* dietary patterns—using an exploratory principal component factor analysis—in an Italian case-control study.

### **2. Materials and Methods**

### *2.1. Design and Participants*

A hospital-based case-control study was carried out between 2003 and 2014 in four Italian areas —i.e., Milan, Pordenone, Naples, and Catania. The study design and inclusion criteria have been described in detail elsewhere [21]. Briefly, cases were 690 patients (including 595 men and 95 women) younger than 85 (age range: 25–84, median: 67) years with incident urothelial carcinoma of the bladder, recruited in major teaching and general hospitals of the study areas, and with no previous history of other neoplasms. Almost all cancer cases (*n* = 645, 93%) were confirmed by histology or cytology. Cases were classified on the basis of the 2016 World Health Organization (WHO) grading system [22]: 268 cases (38.8%) were non-muscle invasive (i.e., TNM pTis/pTa), 192 (27.8%) were pT1, 159 (23.0%) were muscle-invasive (i.e., pT2–pT4); as to the grading, 307 cases (44.5%) were moderately or well-differentiated (i.e., G1–G2), and 312 (45.2%) were undifferentiated or poorly differentiated (i.e., G3–G4). Controls were 665 patients (including 561 men and 104 women), selected among subjects admitted to the same hospital networks of cases for acute non-neoplastic diseases unrelated to alcohol drinking or tobacco smoking, and not associated with long-term dietary modifications. The median age of controls was 66, range 27–84 years. Among controls, 39.9% were admitted to hospital for acute surgery, 28.9% for traumas, 22.1% for nontraumatic orthopedic conditions, and 9.8% for other miscellaneous diseases. Less than 5% of cases and controls approached did not participate. The study protocol was submitted to the Board of Ethics of the participating hospitals and received the approval required at the time of data collection. The Ethics Committee of the National Cancer Institute "Centro di Riferimento Oncologico, IRCCS", Aviano, updated the study approval on 14 December 2012 with the protocol number IRB-15-2012. The Ethics Committee of the Hospital "Niguarda Ca' Granda", Milan, provided the study approval on 23 March 2012, with register number 99\_03/2012.

Details on selected characteristics of the study participants are provided in Table S1.

### *2.2. Data Collection*

Participants' data were collected during their hospital stay by centrally trained interviewers through a structured questionnaire assessing information on sociodemographic characteristics, anthropometric factors, tobacco smoking, a personal medical history of selected diseases, and occupational exposures. Dietary habits in the two years before cancer diagnosis (or before interview for controls) were also assessed with a food frequency questionnaire (FFQ), including 80 foods and recipes, and a list of different beverages. The FFQ included the following sections: (I) milk and sweeteners, (II) bread, cereals, and first courses, (III) second courses, (IV) side dishes (i.e., raw and cooked vegetables), (V) fruit, and (VI) sweets and desserts. Additional sections concerned lifetime consumption of beverages, including (a) alcoholic beverages, (b) hot beverages, (c) soft drinks, and (d) tap and bottled water [14,23]. Participants were asked to recall their usual frequency of consumption per week for each dietary item. Occasional consumption (defined as frequency >1 per month and <1 per week) was coded as 0.5 per week. For each participant, we estimated total energy, selected nutrient intakes, and the amount of condiments (e.g., butter and different types of oil) used in the recipes, through an Italian food composition database [24,25]. The validity and reproducibility of the FFQ were tested using a 7-day dietary record repeated twice [26,27].

### *2.3. Statistical Analysis*

### 2.3.1. Factorability of the Original Matrix

The analyses were carried out on a comprehensive list of 28 macronutrients, micronutrients, and minerals. We examined the potential relationships among nutrients to avoid over-representing any single nutrient or specific profiles of consumption, thus resulting in artificially higher correlation coefficients. We evaluated the factorability of the correlation matrix of the original nutrients (including both cases and controls) by visual examination of the matrix and through statistical procedures, namely Bartlett's test of sphericity, overall (Kaiser–Meyer–Olkin) and individual measures of sampling adequacy [28]. Since we obtained satisfactory results (see Table 1), we used an exploratory principal component factor analysis to derive the *a posteriori* dietary patterns.

1 Overall and individual measures of sampling adequacy range between 0 and 1, with values > 0.60 indicating a satisfactory size.

### 2.3.2. Dietary Pattern Identification

We carried out a principal component factor analysis [29] on the correlation matrix of the 28 selected nutrients (including cases and controls together) to describe the variance–covariance structure of these variables in terms of a smaller number of underlying unobservable and randomly varying factors, which can be interpreted as dietary patterns. We selected the number of factors to retain, taking into account the following criteria: factor eigenvalue >1, scree-plot visual inspection, and factor interpretability [29]. We applied a varimax rotation to obtain a simpler and more interpretable loading structure. Each factor's interpretation and labeling were based on nutrients with rotated factor loadings

≥0.63 in absolute value. We set this cut-off because it implies a minimum contribution of any factor to any nutrient's total variance of approximately 40% (i.e., 0.632 ) [30]. Nutrients with such factor loadings are called "dominant nutrients" hereafter. Factor scores, as continuous measures, were calculated for each participant and each pattern, and quantify the degree of adherence of each subject's diet to the identified pattern. Factor scores were computed using the weighted least squares method [31].

### 2.3.3. Reproducibility, Reliability, and Validity of Dietary Patterns

To evaluate the internal reproducibility of the identified dietary patterns, we performed additional analyses using a different procedure for estimating factor scores (namely, multiple regression method), and different estimation methods (namely, principal axis factor analysis with generalized least squares estimation method, and maximum likelihood factor analysis, after logarithmic transformation of the original nutrients) [29]. Moreover, following a split-half approach, we split the original dataset into 2 randomly selected subsamples (with cases and controls equally distributed), and carried out the principal component factor analysis procedure separately in each subsample; this procedure was repeated several times using different starting seeds for the random assignment, in order to verify the stability of the identified patterns [31]. As a sensitivity analysis, the principal component factor analysis procedure was also carried out among controls only.

Since all these checks were satisfactory, we performed all the subsequent analyses on factor scores obtained from the main analysis based on principal component factor analysis performed on cases and controls together, with varimax rotation and weighted least squares method.

To evaluate factor reliability and refine the identified dietary patterns, we calculated the standardized Cronbach's coefficient alpha for those nutrients with a factor loading ≥0.40 in absolute value on any factor [32]. For each factor, we computed an overall coefficient alpha and several nutrient-specific coefficient alphas when-item-deleted, which assessed the importance of each nutrient within the corresponding pattern.

To further describe and interpret the identified dietary patterns, we calculated the Spearman rank correlation coefficients between the continuous factor scores derived from principal component factor analysis and the weekly intake of selected food groups and condiments, defined on the same data and derived from the original 80 food items [31].

### 2.3.4. Risk Estimates

For each dietary pattern, we categorized participants into 4 groups according to the quartiles of the distribution of factor scores among cases and controls combined. We estimated the odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) for quartile categories of factor scores compared to the reference category (i.e., the lowest quartile category for patterns characterized by positive factor loadings, and the highest quartile for patterns characterized by negative factors loadings), using unconditional multiple logistic regression models. We fitted both separate models for each factor and a composite model, including all the factors simultaneously. We included in each model the following potential confounding variables: age (<55, 55–59, 60–64, 65–69, 70–74, 75–79, ≥80 years), sex, center of recruitment, education (<7, 7–11, ≥12 years), cigarette smoking status and intensity (never, former, current <15, current 15–25, current ≥25 cigarettes/day), alcohol drinking intensity (<1, 1–<2, 2–<4, ≥4 drinks/day), history of occupational exposure (yes vs. no) in selected sectors relevant for bladder cancer risk, history of diabetes, history of cystitis, family history of bladder cancer, year of interview, and body mass index (BMI, <20, 20–24, 25–29, ≥30 kg/m2 ). The tests for linear trends were computed for all these models, scoring the quartile categories as numbers from 1 to 4. Moreover, we fitted a composite model including the factor scores of the identified dietary patterns in continuum (with measurement unit equal to 1 standard deviation), which estimates the mean variation in bladder cancer risk per 1 standard deviation increment of factor scores, accounting for the aforementioned confounding variables.

Calculations were performed using the open-source statistical computing environment R (Ihaka and Gentleman, 1996; R Core Team, 2019), with its libraries psych [33] and GPArotation [34].

### **3. Results**

Visual inspection of the correlation matrix of the original nutrient variables (among cases and controls) indicated that it was adequate to carry out a factor analysis. Table 1 shows the results from statistical procedures for checking matrix factorability. In particular, the Bartlett's test of sphericity was statistically significant (*p*-value < 0.001), allowing to reject the null hypothesis that the correlation matrix is the identity matrix. The overall measure of sampling adequacy (Keiser–Meyer–Olkin statistic) was 0.86, thus indicating that the sample size was adequate compared to the number of nutrients included in the analysis. In addition, the individual measures of sampling adequacy were satisfactory for all considered variables, since 9 nutrients had measures ≥0.90, 12 had measures between 0.80 and 0.89, 5 had measures between 0.70 and 0.79, and only 2 nutrients had measures between 0.60 and 0.69.

Table 2 gives the factor loading matrix of the four selected dietary patterns and the corresponding communalities. The retained dietary patterns explained about 78% of the variance of the original nutrient variables. All the examined nutrients had one or more factor loadings ≥0.30, thus indicating that all the selected nutrients were relevant in this analysis. The greater (in absolute value) was the loading of a given nutrient to a factor, the higher was the contribution of that nutrient to the factor. The first dietary pattern was named "Animal products" and was characterized by high positive factor loadings on calcium, saturated fatty acids, riboflavin, animal protein, cholesterol, phosphorus, and zinc. The second one, labeled "Vitamins and fiber", was characterized by high negative factor loadings on vitamin C, total fiber, beta-carotene equivalents, vitamin E, potassium, and total folate. The third dietary pattern, named "Starch-rich", had high negative factor loadings on starch, vegetable protein, and sodium. The fourth one was labeled as "Animal unsaturated fatty acids" and showed high positive factor loadings on other polyunsaturated fatty acids and vitamin D.

**Table 2.** Factor loading matrix 1 , communalities, and explained variances for the four major dietary patterns identified by principal component factor analysis.

**Table 2.** *Cont.*

1 Estimates from a principal component factor analysis carried out on 28 nutrients, as measured among cases and controls together. For each factor, loadings greater or equal to 0.63 (in absolute value) indicated important or "dominant nutrients" in the current paper and were shown in bold typeface; loadings smaller than 0.1 in absolute value were suppressed.

The factor loading matrix derived from the sensitivity analysis on controls only is presented in Table S2. Visual inspection of the two-factor loading matrices provided reassuring results, with all the dominant nutrients highlighted in Table 2 being confirmed in Table S2. In addition, the single component and overall explained variances were comparable across the two solutions.

Standardized Cronbach's coefficient alphas were high (at least 0.93) for all the factors, and most standardized coefficient alphas when-item-deleted were smaller than the corresponding coefficient alpha for the same factor, which supported the presence of internal consistency of the nutrients on each identified factor (data not shown).

Table 3 gives the Spearman correlation coefficients between the identified dietary patterns and selected food groups and condiments. The "Animal products" pattern score was positively correlated with the consumption of cheese, milk, liver, red meat, desserts, eggs, bread, and processed meat. The "Vitamins and fiber" pattern score had positive correlation coefficients with citrus fruit, other fruits, olive oil, fruiting vegetables, leafy vegetables, root vegetables, other vegetables, and pasta and rice. The "Starch-rich" pattern showed a week positive correlation with pasta and rice. The "Animal unsaturated fatty acids" pattern was positively correlated with the consumption of fish, unspecified seed oils, and red meat.

198

**Table 3.** *Cont.*

1 Correlations greater or equal to 0.25 (in absolute value) were shown in bold typeface; correlations smaller than 0.1 (in absolute value) were suppressed.

Table 4 shows the ORs and the corresponding 95% CIs for bladder cancer, according to quartile categories of the dietary patterns, and in continuum (per 1 standard deviation). Results refer to the composite models, including all the dietary patterns simultaneously. The "Vitamins and fiber" dietary pattern was inversely related to bladder cancer risk (OR = 0.70, 95% CI: 0.49–0.98, for the highest versus the lowest quartile category of consumption). Inverse relationships of borderline significance were also found for the "Animal products" dietary pattern (OR = 0.70, 95% CI: 0.48–1.01) and possibly for the "Animal unsaturated fatty acids" dietary pattern (OR = 0.81, 95% CI: 0.58–1.15). The remaining dietary pattern named "Starch-rich" was unrelated to bladder cancer risk (OR = 1.28, 95% CI: 0.90–1.81). Risk estimates in continuum were consistent with those in categories, indicating a mean risk reduction of 11% for the "Vitamins and fiber" pattern, and of 8% for the "Animal products" and "Animal unsaturated fatty acids" patterns. Risk estimates obtained from models fitted separately for each dietary pattern were comparable to those from the composite model (data not shown).

**Table 4.** Odds ratios (ORs) 1 of bladder cancer and corresponding 95% confidence intervals (CIs) on quartiles of factor scores from a principal component factor analysis.

1 Estimates from an unconditional logistic regression model adjusted for age, sex, center of recruitment, education, tobacco smoking, alcohol drinking, occupational exposure, history of diabetes, history of cystitis, family history of bladder cancer, year of interview, body mass index. Results refer to the composite model, including all the four factors simultaneously. 2 Reference category. 3 *p*-value for linear trend. 4 SD: standard deviation.

### **4. Discussion**

In this case-control study on bladder cancer, we identified four major dietary patterns that explained almost 80% of the nutritional variability in this population. Among these, the "Vitamins and fiber" and possibly the "Animal products" and "Animal unsaturated fatty acids" patterns were associated with a decreased risk of bladder cancer, after mutual adjustment for all the remaining patterns. These patterns allowed to recover the main characteristics of the Italian diet at the time of the present study, in agreement with the findings of a national food consumption survey conducted in Italy in the same period [19].

Correlation coefficients between the identified patterns and selected food groups confirmed the labeling of dietary patterns and provided further insight into their composition. The "Animal products" pattern was primarily characterized by consumption of cheese and milk—which had the highest correlation coefficients—while minor, dominant components were different types of meat, eggs, and desserts (mainly bakery products and ice cream). The dairy products correlating with this pattern, especially milk, may have driven its inverse association with bladder cancer [14]. Moreover, in Italy, in contrast to Northern Europe and North America, poorer diets are largely based on bread, pasta, and carbohydrate-rich foods, instead of meat products, and meat consumption tends to be less unfavorable than elsewhere [35]. The "Vitamins and fiber" pattern correlated highly with different types of fruit and vegetables, as well as with olive oil; these dietary components are major sources of fiber, carotenoids, vitamin C, and vitamin E, and flavonoids, which have antioxidant and anti-inflammatory properties against cancer development [36]. Moreover, this is in line with findings supporting a favorable role of fruit and vegetables on bladder cancer, as indicated in the World Cancer Research Fund updated report [7]. The "Animal unsaturated fatty acids" pattern was mainly characterized by consumption of fish, and, to a lesser extent, by seed oils and red meat.

Evidence on dietary habits and bladder cancer risk is mainly based on single nutrients, foods, or food groups [7]. In the Danish Diet, Cancer and Health Study prospective cohort, no association was found between vitamin C, E, or folate and urothelial carcinoma, and a protective effect of dietary, but not supplemental, total beta-carotene was found [37]. Likewise, the Melbourne Collaborative Cohort Study found no association between dietary intake of B-group vitamins and urothelial cell carcinoma [38]. In the European Prospective Investigation into Cancer and Nutrition, no association was found between dietary folate, vitamin B2, B6, and B12 and urothelial cell carcinoma [39]. A population-based case-control study reported no association for fruits or vegetables, but an inverse association for vitamin B12 [40]. In our study, vitamin C, E, B-group, folate, and beta-carotene equivalents are all part of the same pattern named "Vitamins and fiber", which was inversely related to bladder cancer risk.

The aforementioned case-control study also showed a positive association for processed meat intake [40]. A positive relationship between processed meat, and possibly red meat, and the risk of bladder cancer has also been reported in a meta-analysis, where, however, the association was evident in case-control but not prospective studies [41].

These findings confirm the difficulties of identifying a favorable or detrimental role of specific foods or nutrients on bladder cancer risk and the opportunity to consider diet as an overall exposure using the dietary pattern approach.

Only two papers from the same research group have reported on the role of food-based dietary patterns and bladder cancer risk [12,13]. In the first paper, the authors reported results of a case-control study, including 255 bladder cancer cases and 501 matched hospital controls from Uruguay [12]. They used factor analysis and identified 3 food-based dietary patterns, named "Sweet beverages", "Western", and "Prudent" patterns. The first one was characterized by high loadings on coffee, added sugar, and boiled eggs and was associated with an increased bladder cancer risk. In our study, we did not observe a pattern similar to that one. The "Western" pattern was characterized by positive loadings on red meat and wine and negative loadings on poultry and fish, and it was associated with an increased risk of bladder cancer. Given the common animal orientation, this pattern appears to have similarities with our "Animal products" and "Animal unsaturated fatty acids" patterns. However, unlike the Uruguayan pattern, ours were positively correlated with fish, and white and red meat; the presence of white meat and fish may explain the identified different results in terms of risk. The Uruguayan "Prudent" pattern was characterized by positive loadings on cooked and raw vegetables, citrus and other fruits, and desserts, and by negative loadings on French bread; this pattern was not related to bladder cancer risk. However, when the authors analyzed the separate effects on risk of the dominant food groups from the "Prudent" pattern, citrus fruit was inversely associated, whereas cooked vegetables were positively associated with bladder cancer; thus, the identified null association for that pattern appears to be the consequence of opposite effects on bladder cancer risk of its dominant food groups; an additional effect of condiments in cooked vegetables is likely to explain the positive association of this food group with bladder cancer risk. Another study was carried out by the same authors within a multi-site case-control design, including the aforementioned data on bladder cancer [13].  Four sex-specific and

food-based dietary patterns called "Prudent", "Traditional", "Western", and "Drinker" were identified. While the "Western" and "Prudent" patterns showed associations in the same direction observed in the previous study, the "Traditional" and "Drinker" patterns were unrelated to bladder cancer risk; however, CIs were, in general, very wide. To our knowledge, no studies have been published considering *a posteriori* dietary patterns derived on nutrients.

A few other studies have investigated the role of *a priori* dietary patterns on bladder cancer. In a previous analysis within our case-control study, we found an inverse association between adherence to the Mediterranean diet, as assessed through the Mediterranean Diet Score (MDS) and bladder cancer risk [18]. In a pooled analysis of 13 prospective studies from the BLadder cancer Epidemiology and Nutritional Determinants (BLEND) consortium, a higher MDS was associated with a reduction in bladder cancer risk [11]. In the Melbourne Collaborative Cohort Study (MCCS), the MDS and the Healthy Eating Index (HEI) showed borderline inverse associations with invasive, but not superficial, bladder cancers [9]; no relationship was found in the same study with the Dietary Inflammatory Index, representing a pro-inflammatory diet [9]. Similarly, in the Nurses' Health Study (NHS) and in the Health Professionals Follow Up Study (HPFS), no association with bladder cancer was evident for the Empirical Dietary Inflammatory Pattern measuring the pro-inflammatory potential in diet [8]. A study within the Breast Cancer Detection Demonstration Project follow-up cohort reported an inverse association between the Recommended Food Score—a global measure of diet quality—and overall cancer risk, but no association was detected with bladder cancer [10].

Though these mixed results do not allow to draw firm conclusions, the role of diet in bladder carcinogenesis remains plausible; the biological argument targets those many compounds in foods and their metabolites that are excreted through the urinary tract [6].

Associations between dietary factors and disease may be influenced by selection and information bias, as well as confounding [42]. Hospital controls may not be fully representative of the general population. In our study, however, the low refusal rate and the comparable catchment areas of cases and controls avoided major selection biases. Furthermore, cases and controls were interviewed by the same trained personnel in the same hospital setting [43], and the FFQ was satisfactorily reproducible and valid [26,27], thus reducing the possibility of information bias. The FFQ aimed at assessing dietary habits two years before the enrolment in the study. While this time frame may be insufficient for the development of bladder cancer, it is implicitly assumed that most people do not appreciably change their dietary habits through their adult age; a bias may have occurred if this assumption did not hold. As for potential confounding, we were able to adjust for socioeconomic indicators, tobacco, and a number of other factors.

Further issues are related to the use of factor analysis to derive *a posteriori* dietary patterns [44–46]. This technique [47] requires subjective decisions at various levels of the analysis, including the type and number of dietary components to analyze, the number of factors to retain, the choice of applying a rotation method or not (and which method to use), and the interpretation of the identified factors [48]. For this reason, we performed several complementary analyses, which were reassuring and supported the (internal) reproducibility of the identified dietary patterns, as well as their interpretation.

### **5. Conclusions**

The present work provides a comprehensive description of dietary habits in the Italian population considered, with the identification of four major dietary patterns explaining most of the variability in nutrient intakes. In line with the available evidence on dietary patterns and bladder cancer risk, the additional modeling effort required by dietary patterns has not ended up in stronger risk estimates for this cancer site, as compared to those observed for single dietary components. Our study confirms that scoring high on a fruit-and-vegetables pattern provides beneficial effects on bladder cancer risk.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2072-6643/12/6/1584/ s1, Table S1: Distribution of 690 bladder cancer cases and 665 controls according to selected characteristics. Italy 2003–2014, Table S2: Factor loading matrix and explained variances for the four major dietary patterns identified by principal component factor analysis.

**Author Contributions:** Conceptualization, V.E., C.L.V., M.F. and F.B.; methodology, V.E., M.F. and F.B.; data interpretation, V.E., C.L.V., M.D.M., M.P., M.F. and F.B.; formal analysis, V.E., M.D.M., M.F. and F.B.; investigation, C.L.V., A.C., J.P., M.L. and D.S.; data curation, C.L.V., A.C., J.P., M.L. and D.S.; writing—original draft preparation, V.E., M.F. and F.B.; writing—review and editing, V.E., C.L.V., M.D.M., A.C., J.P., M.L., M.P., D.S., M.F. and F.B.; funding acquisition, C.L.V., J.P. and M.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Italian League Against Cancer and by Ministero della Salute Ricerca Corrente. Matteo Di Maso was partially supported by a grant from Fondazione Umberto Veronesi at the time the study was conducted. The APC was funded by funds from Ferraroni.

**Acknowledgments:** The authors wish to thank A. Tavani and R. Talamini for coordination of the data collection, and Vincenzo Tortora, who contributed to the analyses of the present work as part of his specialty thesis.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**

© 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/).


**6.3 Impact of COVID-19 on the schools' fundraising efforts**

To keep the spaces safe from infections, schools had to be fumigated every day when the learners left the premises [2]. Subsequently, renting out of school spaces to the public to use for various functions could no longer happen as explained in KZN Circular 41 of 2020. This resulted in the loss of revenue that schools generated from these fundraising efforts. Mostly, the under-resourced schools were negatively affected by this arrangement. *Othandweni* Primary Principal lamented that this 'had a huge negative impact; the school has a tuck shop which it uses for income. A lot of fundraising activities were compromised'. *Thethani* Combined Principal regretted that the new arrangement affected the school 'negatively because the school hall was used as a wedding venue previously'. *Umthetho* Primary Principal complained that the new arrangement 'has affected us negatively since there was a church that was using a classroom on Sundays. They have now stopped paying rent'. *Inhlanhla* Primary Principal bemoaned the fact that the 'income received from rental of classrooms is now nil'. Lethiwe Principal even stipulated the amount lost when she said that there has been 'no income for rental from March – loss of R12000'.

### **6.4 Challenges of curriculum delivery and management during the pandemic**

The presented data show how difficult it was for principals to cope in managing the delivery of the school curriculum during the COVID-19 pandemic. Teaching and learning were disrupted due to COVID-19 infections. **Table 1** depicts the combined statistics of cases of infection to both teachers and learners, with the quarantine of teachers and the closing of schools from June when the schools reopened to October when this study was conducted. This depiction is necessary as it reveals the amount of teaching and learning time lost to the pandemic within a short time.

**Table 1** highlights that whilst the principals adhered to policy guidelines of screening people, sending them to quarantine and closing schools for decontamination, they were being robbed of important assets for curriculum delivery: time and personnel in the form of teachers, learners and days lost [2, 17]. In total, 17 teachers from 12 schools went into isolation and/or quarantine for a period of about 10 days. This was not the only dilemma that principals faced as there were other cases of absenteeism, like family responsibility leave, that added to the challenges. The most serious challenge came from the absence of teachers who had to be away from school as per the Education Labour Relations Council (ELRC) Agreement 1 of 2020. Under this agreement, the concession was made for teachers with high-risk comorbidities and those who are over 60 years of age to work from home while the country was on Alert Levels 3 and 2 of the state of disaster [18].

The principals complained that the teachers who remained at home on concession were not substituted. *Thandokuhle* Primary Principal moaned that 'for three months, since June, the teacher who applied for comorbidity has been absent and her

**Table 1.** *COVID-19 cases and teaching time lost.* *Principalship Educational Policy Challenges in the Management of a Turbulent School… DOI: http://dx.doi.org/10.5772/intechopen.108504*

#### **Table 2.**

*Levels of confidence in curriculum recovery programmes.*

subjects have not been taught due to shortage of staff'. Othandweni Primary principal stressed that the 'absence of educators has a huge negative impact on subjects being taught as learners lost learning time'. Zwelonke Primary Principal revealed that 'teachers who attend school regularly are being burdened with relief [duties]' which makes 'frustration levels high amongst staff due to continuous changing of subjects to teach'. To recover the lost time some schools, like Lethiwe, arranged Saturday and morning classes with teachers for higher grades. Others like Bongisizwe, arranged for afternoon classes. For Esethu Primary, the impact left by the absence of teachers was 'addressed by requesting teachers to draft a catch-up plan upon return to school'. Goodness Primary applied a similar strategy.

**Table 2** shows the varying levels of confidence amongst the schools in the completion of assigned tasks, and their comparison with the implementation of curriculum recovery programmes and completion of assessment tasks. The findings show the negative impact of the turbulent schooling year that principals had to contend with. The Policy Guidelines made efforts at trimming the tasks, yet the situation looked bleak as schools lost days due to sudden outbreaks of the virus and the subsequent enforced quarantine periods.

Furthermore, **Table 2** shows 17 principals who were unsure of their stand as far as their capacity to manage the completion of the assigned tasks, curriculum recovery programmes and assessments tasks. What can be read from the above is the level of hopelessness that prevailed as principals were only capable of managing what was within their reach.

### **6.5 Areas of achievements in policy implementation**

This section looks at the duties that were performed by the allocated staff and the manner in which the principals managed these duties. Principals showed an element of success in managing the daily routine tasks through the allocated personnel. Principals had to provide immediate task-oriented leadership to prepare and make schools ready to prevent the spread of infection by applying the policy guidelines [2, 11] The first priority was to set up COVID-19 Committees comprising staff members and to provide relevant training for them. This would then be followed by delegating duties as prescribed by the policy guidelines. Most of the tasks were, however, performed by personnel other than teachers. These were employed and trained specially to execute these special tasks. Nonetheless, it was the duty of the principal to monitor the performance of these duties. The table below indicates the levels of performance as observed by principals.

#### **Table 3.**

*Level of confidence with performance on COVID-19 activities.*

**Table 3** indicates that the principals observed very high or high levels of performance in the execution of duties allocated to various personnel except for a few schools whose performance was low or very low.

Procedures that needed to be followed with great accuracy included how to isolate individuals suspected of infection, notification of relevant authorities and closing down of schools for decontamination. Out of the 12 schools that had to deal with reported positive cases, principals seemed to have followed protocol and handled cases in the best way that protected the schooling community.

*Lethiwe* Primary had a case with a learner and later a teacher. The learner was 'placed in [an] isolation room' while the principal called the parent—'fetched by a parent'. The teacher was 'asked to get immediate medical help'. The principal contacted the Circuit Manager and 'phoned the nurse'. The school 'followed directives from [the] Health Department' and the school closed for 3 days to decontaminate. *Bongisizwe* also had multiple cases from learners at different times. The principal 'contacted [the] parent to collect [the child] immediately' and 'phoned the Circuit Manager, [and] health [officials]' and notified 'school staff'. 'The school closed for 3 days'. With a case in Grade 12, only the affected grade was closed. All other schools that experienced cases followed similar procedures.

That protocol was followed by principals may also be supported by data in **Tables 1** and **3**. **Table 1** depicts the number of cases the schools experienced, the number of learners sent home and the number of teachers quarantined. **Table 3** illustrates the principals' levels of confidence related to the performance of the activities used as barriers to prevent the virus from infecting many individuals.

### **7. Discussion of the findings**

The findings point to the difficulties that were faced by principals to ensure continuous teaching and learning despite the spatial arrangement to try to equitably

#### *Principalship Educational Policy Challenges in the Management of a Turbulent School… DOI: http://dx.doi.org/10.5772/intechopen.108504*

share the classrooms through alternate attendance models. Principals had to make these compromises as a way of trying to balance the phasing in of the Grade R to Grade 6 learners in primary and Grades 8–11 learners in secondary level respectively. The other key finding from the data is that the limited infrastructure in underresourced schools posed a risk of spreading the virus. These are contextual factors beyond the control of the principals. The policy guidelines compelled schools to have an isolation room or sick room for individuals with suspected infections. Of the schools participating in the study, it was only the well-resourced schools that had functional isolation rooms or sick rooms. Most under-resourced schools improvised by using available spaces for this purpose. Such adaptation is nevertheless in line with the argument that spaces may change depending on need, which means that certain activities and human conceptions determine the meanings and use of space [19, 20].

It is clear from the findings that teaching was negatively affected by the absence of teachers. Absent teachers leave behind gaps that may not be instantly or suitably filled by the principal. Added to that is the number of days in which some of the schools were closed for decontamination. Twelve schools closed for a combined total of 31 days ranging from 2 to 9 days for some of the schools. To respond to these challenges, some principals had mitigation strategies to make up for the lost time. The findings indicate the complexity of implementing the policy and the gaps that exist between the policy and the reality at the school level. The turbulent nature of the academic year indicated the level of challenges that principals faced in managing the implementation of the policy guidelines.

## **8. Conclusion**

In this section, we draw conclusions and highlight implications for practice and research. As researchers, we acknowledge the fact that 30 out of 487 public schools is not a sufficiently large enough figure from which to draw general conclusions on how uMgungundlovu District managed the COVID-19 crisis in schools. We nevertheless conclude that there was a disjuncture between policy and implementation. Policymakers seem to have assumed that schools had capacities to implement all the ideas contained in the guidelines. However, the contexts of the schools are never the same, as some lack the financial and other resources to fully implement COVID-19 safety protocols. A one-size-fits-all approach does not work in the educational context. Although principals may have been determined to implement all the guidelines, the complex, turbulent and unprecedented nature of the pandemic made it difficult to have fully functional schools.

Some principals managed to salvage teaching and learning despite the challenges of juggling different grades and classes to allow for the sharing of space. Some of the failures were beyond the principals' control, as teachers used their legal rights to apply for leave due to underlying comorbidities.

The added burden of managing the temporary closure of schools for decontamination negatively affected the number of days for teaching and learning. All the efforts that were made for curriculum recovery programmes could not be successful in a learning situation filled with fear and anxiety caused by the new infections. The recovery programmes were more of a sacrifice by the teachers putting in extra hours of work. We conclude that situational leadership was applied in areas where principals had a level of control. Where there was not much to be done principals allowed the situation to unfold and dealt with those areas within their control to ensure that the

academic year was not totally lost. While this study aimed to understand the principals' experiences, it also revealed the capabilities and readiness of schools as they maintained a delicate balance between providing education and fighting the virus. Evidence on various models of social distancing applied in schools has proved to be challenging as revealed by the findings. Research is thus required to develop methods of creating space to avoid close contact in schools without disruptions to curriculum delivery, especially in under-resourced schools within the South African context.


**Abstract**

The goal for collaborative forest management (CFM) is to attain sustainable management of forest resources for sustainable development. Securing rights and responsibilities of forest fringe communities is central to achieving effective and sustainable management of forest reserves. This article discusses the rights and responsibilities of the forest fringe communities under Ghana's collaborative Forest Management (CFM) in the Northern region and explores the levels of awareness of communities of these rights and responsibilities. The survey employed a mixed method research design with community members and forestry staff as key respondents. We found that although Forest fringe communities are entitled to some admitted rights including access to the reserves and the right to harvest nontimber forest products such as thatch, medicinal plants, dry wood for firewood and edible fruits mainly for domestic use; in reality, access to such rights is somehow restricted by the forestry staff. Fringe communities have limited knowledge about their rights and responsibilities to the forest reserve. For sustainability, educating fringe communities on their rights and responsibilities to forest reserves and involving them in management decisions is recommended as the surest ways of securing their interests in CFM.

**Keywords:** collaborative forest management, rights, responsibilities, sustainability, northern region


3.5.1. Potentiodynamic Polarization

The open circuit potential (EOC) evolution after 1 h of immersion and the potentiodynamic curves of the investigated systems are presented in Figure 4. During the immersion, the EOC of the TiCN and TiSiCN thin films showed a steady evolution, while the substrate slightly changed its value for half of the time, reaching a stable evolution at the end of the test. The TiSiCN coatings exhibited a positive EOC value (54 mV) compared with the TiCN coatings, indicating that the addition of Si had a positive effect on corrosion behavior.

**Figure 4.** (**a**) Open circuit potential evolution in time and (**b**) potentiodynamic curves of the investigated systems.

The main electrochemical parameters of the investigated specimens calculated based on the Tafel and potentiodynamic curves are presented in Table 4 (all the presented potentials are relative to the SCE value). Polarization resistance (*R*p) was determined from linear polarization measurements as the slope of the linear region of the Δ*E*–Δ*i* curve near *E*corr. Corrosion potential (*E*corr), anodic (β*a*) and cathodic (βc) slopes were estimated from Tafel plots. The corrosion current density was also calculated based on one form of the Stern–Geary equation (Equation (1)), based on previously determined parameters.

$$\frac{1}{R\_{\text{P}}} = \left(\frac{\Delta i}{\Delta E}\right)\_{E\_{\text{corr}}} = 2.3 \left(\frac{\beta\_{\text{a}} + \left|\beta\_{\text{c}}\right|}{\beta\_{\text{a}} \left|\beta\_{\text{c}}\right|}\right) i\_{\text{corr}} \tag{1}$$

considering the *E*corr parameter, the most electropositive value was demonstrated by the TiSiCN coating (*E*corr TiSiCN = −14 mV), as well as the smallest value of corrosion current density (*i*corr TiSiCN = 49.6 nA cm−2). Taking into account the polarization resistance, the highest value was observed in the case of the CoCr substrate, closely followed by the TiSiCN coating (*R*p TiSiCN = 425 kΩ·cm2).

**Table 4.** The main corrosion parameters of the investigated specimens.

3.5.2. Electrochemical Impedance Spectroscopy (EIS)

It was observed that the electrochemical performance of the investigated specimens was different as a function of their composition. For comparison, Nyquist and Bode plots for the investigated specimens are presented in Figure 5.

The electrochemical parameters were obtained by fitting the data with an equivalent circuit, which took into consideration the phenomenon at the interface of each investigated system with the testing electrolyte (inset Figure 5). *Rel* represents the electrolyte resistance, CPElayer represents the coating capacitance, Rpore represents the resistance associated with the current flow through the pores generated by the coatings' defects and CPEdl is a double layer capacitance in parallel with a charge transfer resistance - Rct. CPE was used instead of a capacitor due to the non-ideal character of the

working electrode. The physical interpretation of a circuit that has a constant phase element (for a better quality fit) depends on the value of α. If the α parameter is 1, then the CPE can be modeled as a capacitor. Since after the fitting, the α parameter showed values less than 1 in both cases (i.e., the α layer and αdl), a CPE was used. This can be due to possible deviations from the ideal dielectric behavior and it is usually related to the surface inhomogeneity [55]. According to Hirschorn et al. [56], these deviations arise either from different properties along the surface of an electrode (e.g., roughness), or properties normal for the surface (e.g., thickness).

**Figure 5.** (**a**) Nyquist plot (electrical circuit used for the fitting procedure included) and (**b**) Bode plot of the investigated specimens.

The electrochemical parameters of the investigated systems are presented in Table 5. It can be noticed the low value of the χ2 parameter, which is an indication of an excellent agreement between the experimental data and those simulated by the equivalent circuit.

**Table 5.** The fitting results of EIS curves for the investigated systems.

Taking into account the fitting results for the investigated systems, it can be noticed that the highest pore-associated resistance was obtained for TiSiCN, while the CoCr substrate showed low values. It was stated that CoCr alloys form a passive layer at the surface, which is mainly based on Cr(III), and smaller amounts of Cr(OH)3, Co and Mo oxides [57]. The fitted values associated to the CoCr specimen showed that the formed layer is not as compact and protective as the TiCN and TiSiCN coatings.

The *Qdl* parameter, which is representative of the substrate–electrolyte interface, indicated a better protection of the deposited/formed layer in the following order: TiSiCN > TiCN > CoCr. Thus, the best protection after immersion in 90 % DMEM + 10 % FBS was observed for the TiSiCN coatings, with the best capacitive character, indicated by the low value of Qlayer and the highest value of Rct.

Considering αlayer, it can be observed that for CoCr, the CPE used for fitting the obtained data were the closest to a capacitor, since in this case, αlayer = 0.96. This could be due to the low roughness measured before the corrosion as compared to the other investigated specimens (Table 3). Similar α layer values were obtained for the coatings and the time-constant dispersion is ascribed to the similar values of roughness. Going deeper, at the interface between the coating and the substrate, another double layer is formed. *Qdl* and αdl can give an indication of the compactness of the deposited/formed layer and the electrolyte ingress through the defects, which can create pathways for the electrolyte to

reach the substrate [58]. It can be observed that even though αdl was higher for TiCN, showing an almost defect-free structure, TiSiCN was the one showing better values of *Qdl* and *Rct.*

### *3.6. Morphology and Roughness after Corrosion*

SEM images after the corrosion tests are presented in Figure 6. It is worth noting that the uncoated substrate was more affected by the corrosion than the coated surfaces. The destruction of the protection layer can be seen on the coated samples, after performing the corrosion tests. Regarding the TiCN coatings, there were various corrosion products on the surface, indicating that this surface was affected by the corrosive solution. Moreover, the coating was partially destroyed in some areas, with the CoCr substrate being visible. The TiSiCN surface also had corrosion products, but there were less compared with the TiCN surface, indicating better anticorrosive properties. All surfaces were affected by the corrosive solution, but TiSiCN was less damaged.

**Figure 6.** SEM of the investigated (**a**) CoCr substrate and (**b**) TiCN and (**c**) TiSiCN coatings.

The main roughness parameters of the investigated surfaces are presented in Table 6. Comparing these results with the values obtained before the corrosion tests (Table 3), it can be said that all surfaces were significantly damaged after the corrosion tests. The Ra of the uncoated substrates increased from 46.9 ± 5.9 nm to 1342.9 ± 192.4 nm. A significant increase in Ra roughness was found for the TiCN coatings after corrosion (15584.3 ± 7462.8 nm), indicating a major deterioration of the coatings after the corrosion tests. The TiSiCN coatings were also affected by the corrosive process, but they have finer irregularities than TiCN, demonstrating that the addition of Si led to an enhancement of anticorrosive properties. All surfaces showed a negative value of Sk after the corrosion tests, signifying that the surfaces were characterized by many valleys formed during the corrosive processes. The TiSiCN surface had fewer valleys that the TiCN surface, as shown by the smaller absolute value of Sk.

**Table 6.** Main roughness parameters of the investigated specimens after corrosion tests.


*Edited by Jamila Tarhouni*

Groundwater is the largest natural resource in the world. The estimation of groundwater resources as well as their sustainable management are challenges for users, practitioners, managers, and decision-makers. These challenges can be solved based on the progress in three domains: (1) data modeling (2) data science, and (3) advanced systems of ground measurement and Earth data. This book contributes to the progress of groundwater characterization by addressing some challenges through applications and discussions of relevant case studies as well as new approaches. It contains six chapters that discuss various approaches and tools used to study and investigate the impacts of climate change and pollution risks. They also present techniques for accessing water that may contribute to sustainable exploitation and management of groundwater resources.

ISBN 978-1-80355-483-9

Groundwater - New Advances and Challenges

Published in London, UK © 2023 IntechOpen © Yata / iStock

## Groundwater New Advances and Challenges

*Edited by Jamila Tarhouni*


**Acknowledgements**

*Innovations in Cell Research and Therapy*

with age. It was also reported that BMMNCs isolated from patients with chronic ischemic heart disease have a significantly reduced migratory and colonyforming activity in vitro and a reduced neovascularization capacity in vivo, as compared to healthy controls [145]. Therefore, for the patients that are elderly and suffer from pathological insults, they may not benefit from treatment using their own cells. For allogeneic cells, the cell dose is less of an issue than autologous cells. As off-the-shelf products, they are presumably validated for safety and efficacy before being applied to patients. However, generation of cell lots with consistent potency and comparability has been recognized as a significant issue for clinical translation. Recently, two independent investigations reported that clinical-grade human neural stem cell product (HuCNS-SC; proprietary of StemCells, Inc.), in contrast to the research-grade NSCs provided by the same company, failed to demonstrate the efficacy in animal models of spinal cord injury and Alzheimer's disease, respectively [144, 146]. However, despite being informed of the negative impact of stem cell engraftment on functional outcome in the animal model, the company initiated a clinical trial testing this product in patients with cervical spinal cord injury (NCT02163876) in December 2014 and subsequently reported a small improvement in motor strength in 4/5 subjects in the 6-month interim report. However, the clinical trial was terminated in May 2016, due to a lack of significant improvements and the lack of a trend for improvements over time [146]. In this study, there were no details on how the clinical- and research-grade products were made differently that might contribute to the disparity on the efficacy of animal studies. HuCNS-SC was derived from donated fetal brain tissue based on fluorescence-activated cell sorting of

 cells and expanded as neurospheres. It is possible that the clinical- and research-grade products were from different donors with varying genetic background and/or developmental stage. It is also possible that the scale-up production of the cell products under good manufacturing practice (GMP) unfavorably changed the therapeutic function of the cells. Nevertheless, the lack of efficacy of the cell product in the animal model was consistent with the failure of the clinical trial. It has to be noted that in vivo preclinical testing of the final clinical product is not required by the FDA, because "human-derived cellular therapy products intended for clinical administration in animals may not be informative" [147]. As a result, stem cell products are increasingly entering clinical studies for various disease conditions without prior efficacy studies in animal models, outpacing our understanding on their potential mechanisms of action. Although it is true that not all the animal models recapitulate spectrum of human diseases and it is difficult to extrapolate the results from the animal study to human, the lesson learned from the failures of clinical studies including HuCNS-SC is the importance of robust and reliable potency assays to characterize the cells and to ensure the consistency between different manufacturing lots before applying to patients. Recently, the International Society of Stem Cell Research (ISSCR) released updated guidelines on stem cell research and clinical translation, recommending that the cells entering clinical trials are based on sound scientific rationales with robust manufacturing and animal efficacy data, in addition to a safety package to

We are at the end of the beginning in the field of stem cell research and stem

cell regenerative medicine. Particularly, the development of iPSCs and gene editing techniques have opened a new era of disease modeling and personalized

**114**

support clinical trials [148].

**4. Conclusion**

CD133<sup>+</sup>

The authors would like to thank Erin Morris, RN, for assistance in the preparation of this chapter. This work was supported by grants from the Pediatric Cancer Research Foundation to MSC, DEBRA International funding to MSC, and National Natural Science Foundation of China (81472141) to HZ.