*Article* **Gut Microbial Composition of Pacific Salmonids Differs across Oregon River Basins and Hatchery Ancestry**

**Nicole S. Kirchoff 1,\*, Trevan Cornwell 2 , Staci Stein 2 , Shaun Clements 2 and Thomas J. Sharpton 1,3**

**Abstract:** The gut microbiome may represent a relatively untapped resource in the effort to manage and conserve threatened or endangered fish populations, including wild and hatchery-reared Pacific salmonids. To clarify this potential, we defined how steelhead trout gut microbiome composition varies across watersheds and as a function of ancestry. First, we measured this variation across watersheds using wild steelhead trout sampled from nine locations spanning three river basins. While gut microbial composition differs across basins, there exist bacterial clades that are ubiquitous across all populations. Correlating the phylogenetic composition of clades with geographic distance reveals 395 clades of bacteria whose ecological distribution implicates their co-diversification with steelheads. Second, we quantified how microbiome composition varies between first generation hatchery-reared steelhead and traditional hatchery-reared steelhead. Despite being subject to the same hatchery management strategies, fish bred from wild parents carry distinct microbiomes from those bred from hatchery broodstock, implicating the role of genotype on microbiome composition. Finally, we integrated all data from both studies to reveal two distinct, yet robust clusters of community composition. Collectively, our study documents for the first time how the steelhead gut microbiome varies by geography or broodstock and uncovers microbial taxa that may indicate the watershed or hatchery from which an individual was sourced.

**Keywords:** steelhead trout; gut microbiome; hatcheries; aquaculture

#### **1. Introduction**

Steelhead trout (*Oncorhynchus mykiss)* is an economically, culturally, and ecologically important fish. However, climate change, overfishing, and habitat destruction threaten and endanger steelhead populations. Even efforts to preserve access to steelhead through the hatchery production of fish are met with rising challenges, as fewer hatchery-reared adults return to spawn compared to their wild counterparts. Simply put, the management and conservation of Pacific salmonids faces grave challenges and may benefit from new tools that aid outcomes.

The gut microbiome is an increasingly considered but relatively untapped resource in the management and conservation of wildlife, including fisheries. Ample evidence shows that anthropogenic-caused land-use changes, climate change, environmental contamination, as well as captivity disrupts gut microbial communities [1]. This disruption is known to involve the elimination or reduction of microorganisms that are important to host health and fitness. For example, red colobus monkeys living in fragmented forests have fewer bacteria that can degrade tannins, a toxic xenobiotic present in many of their food sources [2]. The loss of these bacteria may impact their ability to digest their preferred diet and thus impact their survival. The augmentation or supplementation of microbes important to host survival and health may mitigate anthropogenic disturbances and aid conservation efforts.

**Citation:** Kirchoff, N.S.; Cornwell, T.; Stein, S.; Clements, S.; Sharpton, T.J. Gut Microbial Composition of Pacific Salmonids Differs across Oregon River Basins and Hatchery Ancestry. *Microorganisms* **2022**, *10*, 933. https://doi.org/10.3390/ microorganisms10050933

Academic Editor: Konstantinos Ar. Kormas

Received: 4 March 2022 Accepted: 23 April 2022 Published: 29 April 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 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 (https:// creativecommons.org/licenses/by/ 4.0/).

Therefore, learning more about the gut microbiome of vulnerable animals will embolden potential microbial related mitigation efforts with the mission of aiding threatened hosts and their microbial consortia. Knowledge of the steelhead gut microbiome is critical if we wish to use gut microbial manipulation to improve the conservation efforts related to these fish.

Despite the importance of the fish gut microbiome to their host, little is known about the steelhead gut microbiome, especially with respect to the diversity of the microbiome across distinct watersheds, wild populations, and hatchery broodstocks [3]. This paucity of knowledge challenges efforts to link the gut microbiome to management and conservation practices. Previous studies have focused on characterizing the non-anadromous member of the *O. mykiss* species, rainbow trout [4–6]. Additionally, previous rainbow trout gut microbiome studies have mostly been conducted in laboratory or aquaculture facilities and not in wild or hatchery populations. Thus, we were interested in characterizing the wild and hatchery steelhead gut microbiome as well as determining how the gut microbiome varies across river systems, thus informing conservation efforts regarding the necessity of location-based gut microbial interventions.

In order to characterize the steelhead gut microbiome and evaluate the gut microbial composition based on location and broodstock ancestry we conducted two studies. The first study investigated the differences between the gut microbiome of steelhead from several different locations in western Oregon. The second study investigated differences in the gut microbiome between traditional hatchery broodstock and hatchery steelhead with wild parents. We found that the steelhead gut microbiome presents geographical effects and varies based on a wild broodstock or hatchery broodstock host background, which suggests that host genotype contributes to gut microbial differences. Additionally, we reveal bacterial clades that demonstrate a phylogenetic composition in the steelhead gut that is associated with geography and that the steelhead gut microbiome has two predominant microbiome types.

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

#### *2.1. Sample Locations*

For the comparison of fish across river basins, we sampled ten wild-born, juvenile steelhead from each of nine freshwater systems within three Oregon river basins (Figure 1). We sampled Gravel Creek, Sunshine Creek, and Cedar Creek in the Siletz Basin; Fall Creek, Tobe Creek, and East Fork Lobster Creek in the Alsea Basin; and Alder Creek, East Fork Beaver Creek, and Elk Creek in the Nestucca River Basin.

For the comparison of wild broodstock versus traditional hatchery broodstock fish, we collected traditional juvenile steelhead from two different hatcheries as well as corresponding first hatchery generation juvenile steelhead. Specifically, thirty wild broodstock juvenile fish and thirty hatchery broodstock fish were sampled from Cedar Creek Hatchery in the Nestucca River basin and North Fork Alsea Hatchery in the Alsea River basin, respectively (Figure 1).

#### *2.2. Sample Collection*

For both studies, samples were collected from already scheduled steelhead sacrifices. Fish were collected with backpack electroshockers from several Oregon river basins between October 2016 and March 2017 in accordance with Oregon Department of Fish and Wildlife permits. Fish were sacrificed with a buffered tricaine methanesulfonate (i.e., MS-222) overdose, weighed, cut from anal vent to gills, and gut digesta from stomach to intestines were squeezed into 50 mL conical tubes. To preserve the DNA content, intestinal samples were first placed on ice in the field and then placed into a −20 ◦C freezer within four hours of sampling. Within 24 h of sampling, samples were finally moved into an −80 ◦C freezer.

Figure 1. A map displaying sampling locations of wild steelhead intestinal samples. This is an image of the western Oregon coast between Portland, OR and Eugene, OR. Point shape, color, and inclusion of an "X" indicate recent ancestry, study origin, and river basin origin, respectively. The Oregon coast is located at the position of the red box on the border of the United States. Nestucca River basin samples are from the north sites in blue, Siletz River basin samples from the middle sites in green, and Alsea River basin samples from the southern sites in orange. **Figure 1.** A map displaying sampling locations of wild steelhead intestinal samples. This is an image of the western Oregon coast between Portland, OR and Eugene, OR. Point shape, color, and inclusion of an "X" indicate recent ancestry, study origin, and river basin origin, respectively. The Oregon coast is located at the position of the red box on the border of the United States. Nestucca River basin samples are from the north sites in blue, Siletz River basin samples from the middle sites in green, and Alsea River basin samples from the southern sites in orange.

#### *2.3. Microbiome Profiling and Analyses*

DNA extraction was conducted using the Qiagen DNeasy PowerSoil kit (QIAGEN, Germantown, MD, USA) with an addition of a 10 min incubation step at 65 ◦C, as explained previously [7]. The 16S V4 rRNA gene was amplified using Caporaso (515F/806R) primers according to previous protocols [8,9]. DNA was then quantified using a Qubit dsDNA HS kit (Thermo Fisher, Waltham, MA, USA), then pooled and cleaned with the QIAquick PCR Purification Kit (QIAGEN). Amplicons were sequenced at the Center for Quantitative Life

Sciences at Oregon State University with an Illumina MiSeq (v3 chemistry) generating 300 bp paired end reads. Sequences were generated for each study on distinct flow cells.

#### *2.4. Bioinformatics and Statistical Analyses*

We generated an amplicon sequence variant (ASV) table by running FASTQ sequence files through the DADA2 (v 1.9.0) pipeline [10]. Separately for each study, forward reads were truncated at 240 base pairs, chimeras were removed, and bacterial taxonomy was assigned with the SILVA rRNA database (release 128) and the Ribosomal Database Project's naïve Bayesian classifier [11]. We then created a phylogenetic tree using V4 rRNA gene sequence alignments via FastTree (v 2.1.10) [12]. We used the R (v 3.6.2) phyloseq package (v 1.3) to rarify sequence abundances for each sample within a study [13,14]. Pairwise Bray– Curtis dissimilarities for each gut microbial sample were calculated to compare abundanceweighted bacterial community compositions across sample location, steelhead weight, and management strategy using the vegan package (2.5–6) [15]. Monophyletic bacterial clades within taxonomic phylotypes were identified with the ClaaTU algorithm [16].

The non-metric multi-dimensional scaling (NMDS) plot was generated in R also using the vegan package to visualize the similarity of compositional abundance with a method that is robust to data sparsity [15]. Beta dispersion was calculated and compared with a Tukey HSD test using the vegan and stats packages, respectively. The coin package (v1.3-1) was used to conduct Kruskal–Wallis tests comparing bacterial cladal abundances across early life history categories and geographic location [17]. Multiple test correction was performed with the p.adjust() function in the stats package (v 3.6.2) with a false discovery rate cut-off of 0.05 [13]. Weighted pairwise UniFrac values were also calculated with vegan to determine the phylogenetic distance between bacterial clades present in the steelhead gut microbiome [15]. Additionally, we computed the straight line geographic distances between steelhead sample sites using the geosphere package (v 1.5-10) [18]. Hierarchical clustering (median, ward-d2) and dendrogram visualization was conducted using the stats package [13].

#### *2.5. Combination of Both Studies*

Data from both the geography and hatchery broodstock vs. wild broodstock studies were pooled and bioinformatically and statistically analyzed together. The combined FASTQ files were re-processed through DADA2 quality filtering, and forward reads were cut at 240 base pairs [10]. The phyloseq package was used to normalize the library size and randomly subsample (i.e., rarefy) to a maximum of 1576 reads for each sample (median reads per sample = 11,919), and 16S classification was conducted with the SILVA rRNA gene database. Phylogenetic tree inferences were conducted in FastTree, as in the two studies above [12]. Partitioning around medoids (PAM) cluster analysis was performed in R with the cluster package (v 2.1.0) [19].

#### **3. Results**

#### *3.1. Wild Juvenile Steelhead Trout Gut Microbial Communities Are Structured by Geography and Host Fitness*

To determine if the composition of the steelhead gut microbiome associates with steelhead geography, we rarefied to 13,635 bacterial reads and evaluated the beta diversity of the gut microbiome across locations (Supplementary Table S1). The bacterial community composition of the steelhead gut is significantly different across Oregon river basins, though the effect sizes are weak (PERMANOVA, Bray–Curtis, R2 = 0.06, *p* = 0.001) (Figure 2). This associative pattern is retained when comparing the beta diversity of individual sample sites, and moreover, the model improvably fits the data (PERMANOVA, Bray–Curtis, R 2 = 0.19, *p* < 0.05). These results indicate that a steelhead's gut microbiome is related to their geographic location, but the steelhead gut microbiome has a stronger association with the exact river or stream the fish inhabited.

association with the exact river or stream the fish inhabited.

formed in R with the cluster package (v 2.1.0) [19].

3. Results

and Host Fitness

Bray–Curtis, R2

Figure 2. Steelhead gut microbiome samples from three different river basins in Oregon roughly group together. Dendrogram showing hierarchal clustering (Ward's method with Ward's clustering criterion) comparing Bray–Curtis dissimilarities between samples. Samples are colored by river basin origin. Samples do not neatly separate into three groups, but the samples tend to cluster into smaller groups with like colors. The differences between steelhead gut microbial composition are confirmed statistically (PERMANOVA, R2 = 0.05, p < 0.01). **Figure 2.** Steelhead gut microbiome samples from three different river basins in Oregon roughly group together. Dendrogram showing hierarchal clustering (Ward's method with Ward's clustering criterion) comparing Bray–Curtis dissimilarities between samples. Samples are colored by river basin origin. Samples do not neatly separate into three groups, but the samples tend to cluster into smaller groups with like colors. The differences between steelhead gut microbial composition are confirmed statistically (PERMANOVA, R2 = 0.05, *p* < 0.01).

cut at 240 base pairs [10]. The phyloseq package was used to normalize the library size and randomly subsample (i.e., rarefy) to a maximum of 1576 reads for each sample (median reads per sample = 11,919), and 16S classification was conducted with the SILVA rRNA gene database. Phylogenetic tree inferences were conducted in FastTree, as in the two studies above [12]. Partitioning around medoids (PAM) cluster analysis was per-

3.1. Wild Juvenile Steelhead Trout Gut Microbial Communities Are Structured by Geography

(Figure 2). This associative pattern is retained when comparing the beta diversity of individual sample sites, and moreover, the model improvably fits the data (PERMANOVA,

is related to their geographic location, but the steelhead gut microbiome has a stronger

= 0.19, p < 0.05). These results indicate that a steelhead's gut microbiome

sins, though the effect sizes are weak (PERMANOVA, Bray–Curtis, R2

To determine if the composition of the steelhead gut microbiome associates with steelhead geography, we rarefied to 13,635 bacterial reads and evaluated the beta diversity of the gut microbiome across locations (Supplementary Table S1). The bacterial community composition of the steelhead gut is significantly different across Oregon river ba-

= 0.06, p = 0.001)

To discern which taxa may drive these river basin-specific patterns in community composition, we leveraged a phylogenetic approach that aggregates observed counts of ASVs among lineages that constitute monophyletic clades and applied Kruskal–Wallis tests to focus on clades whose aggregated abundances differ between river basins. In so doing, we resolved 21 bacterial clades that stratify the Alsea River basin from the Siletz and Nestucca basins. For example, a Ferruginibacter clade is more abundant in Alsea than in the Siletz and Nestucca basins (Figure 3A). We also found 36 clades whose abundances in the Nestucca basin differ from those in the Siletz and Alsea basins, including a clade of Sphingomonadaceae that is more abundant in the Nestucca basin (Figure 3B). Finally, we discovered four bacterial clades that differ in terms of abundance in the Siletz basin compared to the Nestucca and Alsea basins that includes one clade of Novosphingobium, two To discern which taxa may drive these river basin-specific patterns in community composition, we leveraged a phylogenetic approach that aggregates observed counts of ASVs among lineages that constitute monophyletic clades and applied Kruskal–Wallis tests to focus on clades whose aggregated abundances differ between river basins. In so doing, we resolved 21 bacterial clades that stratify the Alsea River basin from the Siletz and Nestucca basins. For example, a *Ferruginibacter* clade is more abundant in Alsea than in the Siletz and Nestucca basins (Figure 3A). We also found 36 clades whose abundances in the Nestucca basin differ from those in the Siletz and Alsea basins, including a clade of Sphingomonadaceae that is more abundant in the Nestucca basin (Figure 3B). Finally, we discovered four bacterial clades that differ in terms of abundance in the Siletz basin compared to the Nestucca and Alsea basins that includes one clade of *Novosphingobium*, two clades of *Aeromonas*, and one clade of *Flavobacterium* that are more abundant in the Siletz basin (Figure 3C). Microorganisms 2022, 10, x FOR PEER REVIEW 6 of 16 clades of Aeromonas, and one clade of Flavobacterium that are more abundant in the Siletz basin (Figure 3C).

Figure 3. Examples of bacterial clades that are more abundant in each of the three river basins sampled in the geography study. Boxplots visualizing the abundance of steelhead gut microbiome bacterial clades across three western Oregon river basins. Asterisk (\*) indicates a statistically significant result using Kruskal-Wallis tests and false discovery rate multiple test correction. (A) shows one clade's abundances from the genus Ferruginibacter, (B) from the family Sphingomonadcaeae, and (C) from the genus Novosphingobium. **Figure 3.** Examples of bacterial clades that are more abundant in each of the three river basins sampled in the geography study. Boxplots visualizing the abundance of steelhead gut microbiome bacterial clades across three western Oregon river basins. Asterisk (\*) indicates a statistically significant result using Kruskal-Wallis tests and false discovery rate multiple test correction. (**A**) shows one clade's abundances from the genus *Ferruginibacter*, (**B**) from the family Sphingomonadcaeae, and (**C**) from the genus *Novosphingobium*.

Despite these differences across location, we also resolved several microbial clades that were common to all locations. In particular, we identified 1489 clades that are signif-

Given the pattern of variation in the salmonid gut microbiome that we observed across locations, we next sought to determine if any salmonid gut microbial clades manifest phylogenetic compositions that are statistically structured by the geography of their host, which may imply population-level co-diversification. To discern such associations, we correlated the pairwise-weighted phylogenetic beta diversity and geographic distances of steelhead gut bacterial clades. This analysis revealed 395 monophyletic clades of bacteria whose phylogenetic compositional differences across samples correlates with the geographic distance spanning sampling locations (Supplementary Table S2). The gut microbial clades that display this phylogenetic distance by geographic distance structure include members of the families Sphingomonadaceae and Rhodobacteraceae. For example, forty-one Sphingomonadaceae clades have a weighted UniFrac value that is significantly correlated with geographic distance between sample site (Mantel test < 0.01) (Figure 4). These patterns indicate that the gut bacterial phylogeny of some clades is related to the geographic location of their host. However, our analysis was based on a limited number of sampling locations and relied on a test of correlation that may be subject to relatively

these conserved clades were present in every steelhead gut sample and they encompass taxa such as Flavobacterium, Hyphomicrobium, and Singulisphaera. Such microbes may manifest these ubiquitous distributions because they are common in the environment, apt at

high type I error rates.

colonizing the salmonid gut, or specifically selected for by the host.

Despite these differences across location, we also resolved several microbial clades that were common to all locations. In particular, we identified 1489 clades that are significantly more prevalent across samples than expected by chance (FDR < 0.05). Thirty-six of these conserved clades were present in every steelhead gut sample and they encompass taxa such as *Flavobacterium*, *Hyphomicrobium*, and *Singulisphaera*. Such microbes may manifest these ubiquitous distributions because they are common in the environment, apt at colonizing the salmonid gut, or specifically selected for by the host.

Given the pattern of variation in the salmonid gut microbiome that we observed across locations, we next sought to determine if any salmonid gut microbial clades manifest phylogenetic compositions that are statistically structured by the geography of their host, which may imply population-level co-diversification. To discern such associations, we correlated the pairwise-weighted phylogenetic beta diversity and geographic distances of steelhead gut bacterial clades. This analysis revealed 395 monophyletic clades of bacteria whose phylogenetic compositional differences across samples correlates with the geographic distance spanning sampling locations (Supplementary Table S2). The gut microbial clades that display this phylogenetic distance by geographic distance structure include members of the families Sphingomonadaceae and Rhodobacteraceae. For example, forty-one Sphingomonadaceae clades have a weighted UniFrac value that is significantly correlated with geographic distance between sample site (Mantel test < 0.01) (Figure 4). These patterns indicate that the gut bacterial phylogeny of some clades is related to the geographic location of their host. However, our analysis was based on a limited number of sampling locations and relied on a test of correlation that may be subject to relatively high type I error rates.

Geographic Distance Between Sample Sites (m)

**Figure 4.** Sphingomonodaceae cladal abundance from north to south geography sampling sites shows a relationship between the phylogenetic composition of the clade and geography. Scatter plot representing a Sphingomonadaceae clade that has a significant correlation between weighted UniFrac and physical straight-line distance between coordinates of sample sites (Mantel test < 0.01). The red line represents the slope of all the data points and shows the positive relationship between geographic distance and phylogenetic distance. The shading represents the 95% confidence interval. This significant trend indicates that sampling sites that are geographically closer together tend to host bacteria with a more similar phylogenetic history. Forty other Sphingomonadaceae clades also display weighted UniFrac values that correlate with geographic distance, and Sphingomonadaceae was the taxon with the most significant clades after this analysis.

Some of the variation in the composition of the gut microbiome observed here could hold implications for salmonid fitness. For example, larger sized salmonids have greater reproductive success (i.e., the number of offspring that survive to maturity) compared to their smaller siblings [20]. Accordingly, a larger animal size is related to greater fitness (i.e., reproductive success) in steelhead trout. We thus determined whether the composition of the gut microbiome links to this salmonid fitness indicator through a test of association. In particular, we compared the steelhead gut bacterial structure to the weight of all fish and found that the gut microbiome is associated with steelhead weight (PERMANOVA, Bray–Curtis, R2 = 0.1273, *p* = 0.03).

#### *3.2. Juvenile Steelhead Trout Gut Microbiome Varies as a Function of Hatchery Broodstock and Hatchery Location*

Traditional hatchery broodstock are subject to several genetic bottlenecks after each successive generation compared to wild broodstock fish (i.e., F1 hatchery populations with wild parents) that only experience one generation in a hatchery facility. Despite this fact, it remains generally unknown how hatchery broodstock origins impact the composition of the gut microbiome compared to their wild broodstock counterparts. Addressing this question is critical given the fact that traditional hatchery broodstock fish are less likely to survive than their wild born counterparts for reasons we do not fully understand.

After subsampling bacterial reads to 1237 reads, our analyses indicated that traditional hatchery broodstock fish carry different gut microbiome assemblages relative to their wild broodstock counterparts (PERMANVOA, Bray–Curtis, R2 = 0.07, *p* = 0.001) (Figure 5) (Supplementary Table S3). A total of 665 bacterial clades are differentially abundant across fish ancestry (Supplemetary Table S4). For instance, all 13 of the significant clades from the genus *Peptoniphilus* are more abundant in the gut microbiome of first-generation steelhead (Figure 6A). All four *Pleurocapsa* clades are more abundant in the guts of traditional hatchery broodstock steelhead (Figure 6B). Additionally, there appear to be hatchery-specific effects on the interindividual variation of the microbiome. For example, the NMDS plot of beta diversity shows that traditional North Fork Alsea Hatchery samples are more tightly gathered than the North Fork Alsea Hatchery wild broodstock samples. Thus, we compared the beta dispersion of the steelhead gut microbial samples and found that North Fork Alsea Hatchery wild broodstock samples are more dispersed than the traditional hatchery broodstock samples (Tukey HSD of beta dispersion <0.001). This differentiation in dispersion could contribute to the observed differences in beta diversity. Furthermore, we determined that the gut microbial structure of steelhead is also associated with their creek of origin, irrespective of their hatchery or wild broodstock status (PERMANOVA R2 = 0.29, *p* < 0.01), suggesting that specific aquatic environments play a role in shaping steelhead gut microbial structure. The contribution of geographic origin may also explain the overlap of North Fork Alsea Hatchery samples visible in the NMDS plot that is not seen between Cedar Creek Hatchery traditional broodstock samples and Cedar Creek Hatchery wild broodstock samples, as both North Fork Alsea Hatchery broodstocks were established using fish from the Alsea River and the Cedar Creek hatchery fish were established using fish from two different locations. There are 1664 bacterial clades with different abundances between the North Fork Alsea Hatchery and Cedar Creek Hatchery locations (Supplementary Table S5). All 29 of the clades assigned to the genera *Flavobacterium* are more abundant in the Cedar Creek Hatchery location (Figure 7A). Furthermore, most of the 33 clades assigned to the genus *Bacteroides* are also more abundant in the Cedar Creek Hatchery samples, but eight of the clades are more abundant in the North Fork Alsea Hatchery location. We visualized the abundance distributions of one of the *Flavobacterium* clades and one of the *Bacteroides* clades (Figure 7B). Collectively, our results indicate that broodstock generation and watersheds impact the assembly of the steelhead gut microbiome.


**Author details**

Suzanne Pruijssers\*, Ernst van Heurn and Nicole Bouvy Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**49**

*Endoluminal Techniques to Treat Obesity DOI: http://dx.doi.org/10.5772/intechopen.82733*

[1] WHO. Obesity and Overweight Factsheet. 2018. Available from: http:// www.who.int/news-room/fact-sheets/

with obesity: A meta-analysis with secondary analysis on weight loss and hormonal changes. Diabetes Care.

[9] Ryder REJ, Munro L, Mcmaster JJ, Bessell J, Bascomb JM, Collins JE, et al. First risk-benefit data from the worldwide endobarrier registry. Diabetes. 2018;**67**(Supplement 1)

[10] Forner PM, Ramacciotti T, Farey JE, Lord RV. Safety and effectiveness of an endoscopically placed duodenaljejunal bypass device (EndoBarrier(R)): Outcomes in 114 patients. Obesity Surgery. 2017;**27**(12):3306-3313

[11] Quezada N, Munoz R, Morelli C, Turiel D, Hernandez J, Pimentel F, et al. Safety and efficacy of the endoscopic duodenal-jejunal bypass liner prototype in severe or morbidly obese subjects implanted for up to 3 years. Surgical Endoscopy. 2018;**32**(1):260-267

[12] Sandler BJ, Rumbaut R, Swain CP, Torres G, Morales L, Gonzales L, et al. Human experience with an endoluminal, endoscopic, gastrojejunal bypass sleeve. Surgical Endoscopy.

[13] Sandler BJ, Rumbaut R, Swain CP, Torres G, Morales L, Gonzales L, et al. One-year human experience with a novel endoluminal, endoscopic gastric bypass sleeve for morbid obesity. Surgical Endoscopy. 2015;**29**(11):3298-3303

[14] Moreno C, Closset J, Dugardeyn S, Barea M, Mehdi A, Collignon L, et al. Transoral gastroplasty is safe, feasible, and induces significant weight loss in morbidly obese patients: Results of the second human pilot study. Endoscopy.

[15] Deviere J, Ojeda Valdes G, Cuevas Herrera L, Closset J, Le Moine O,

Eisendrath P, et al. Safety, feasibility and

2011;**25**(9):3028-3033

2008;**40**(5):406-413

2018;**41**(5):1106-1115

[2] Ribaric G, Buchwald JN, McGlennon TW. Diabetes and weight in comparative

[3] Sjostrom L. Bariatric surgery and reduction in morbidity and mortality: Experiences from the SOS study. International Journal of Obesity. 2008;**32**(Suppl 7):S93-S97

[4] Ruban A, Ashrafian H, Teare JP. The EndoBarrier: Duodenal-jejunal bypass liner for diabetes and weight loss. Gastroenterology Research and Practice.

[5] Patel N, Mohanaruban A, Ashrafian H, Le Roux C, Byrne J, Mason J, et al. EndoBarrier(R): A safe and effective novel treatment for obesity and type 2 diabetes? Obesity Surgery.

[6] Schouten R, Rijs CS, Bouvy ND, Hameeteman W, Koek GH, Janssen IM, et al. A multicenter, randomized efficacy study of the EndoBarrier Gastrointestinal Liner for presurgical weight loss prior to bariatric surgery. Annals of Surgery. 2010;**251**(2):236-243

[7] Koehestanie P, de Jonge C, Berends FJ, Janssen IM, Bouvy ND, Greve JW. The effect of the endoscopic duodenal-jejunal bypass liner on obesity and type 2 diabetes mellitus, a multicenter randomized controlled trial. Annals of Surgery. 2014;**260**(6):984-992

[8] Jirapinyo P, Haas AV, Thompson CC. Effect of the duodenal-jejunal bypass liner on glycemic control in patients with type 2 diabetes

2018;**2018**:7823182

2018;**28**(7):1980-1989

detail/obesity-and-overweight

studies of bariatric surgery vs conventional medical therapy: A systematic review and meta-analysis. Obesity Surgery. 2014;**24**(3):437-455

**References**

*Endoluminal Techniques to Treat Obesity DOI: http://dx.doi.org/10.5772/intechopen.82733*


**1. Introduction**

Comprehensive understanding of the vision for urban areas encompasses a number of widely used concepts. The concepts of sustainability, resilience, adaptability, safety, transformation and liveability are more or less implicit as main guidelines for action [1,2], even if the understanding of these concepts is not generalized and is often vague or narrow [3]. Translation of these concepts into development strategies for the complex and dynamic urban systems can be an unreachable aim. However, as emphasized in Reference [3], "cities have proven to be remarkably resilient complex systems: many cities have existed for thousands of years and have persevered in the face of natural and human-induced disasters to become stronger and in some cases more resilient". Despite these debates, there is a need for a shift to a more sustainable and resilient path [1].

Aligned with this vision, and aware of the challenges that climate change imposes on urban areas, the option of dealing with specific associated hazards, while ensuring the involvement of multiple urban services and interested parties, allows for reducing the dimension of the problem.

Water related risks are amongst those that are significantly dependent on climate related events. The intrinsic dynamic nature of climate in each region already challenges the managers of urban systems. Climate change effects on the urban areas potentially aggravate existing conditions and lead to the emergence of new hazards or risk factors. Floods are a leading source of adverse consequences for urban areas [4,5].

City resilience, understood as the ability to absorb, adapt and recover from disruptive events in a path towards increasing sustainability [6], provides a broad conceptual structure to assess and support planning in urban areas. Any integrated and sustainable approach to increase resilience needs to be supported by sound knowledge. However, the complexity and dynamics of urban areas imply the acceptance of several limitations on data, tools and resources. Planning for increasing resilience can benefit from the use of diverse information and methods to add reliability and validity to the results. Furthermore, explicit consideration of uncertainties of climate phenomena and meteorological events [7] is critical, even if quantification is not always feasible.

Focusing on the water sector, events such as intense rainfall, storm surge, sea level rise and temperature increase are of concern in urban areas. Aggravation of these climate conditions has the potential to increase the likelihood and consequences of severe events, as well as to reduce the performance of urban water systems during less extreme conditions [7]. Cities and services providers must be prepared to cope with these challenges. The interplay between services providers, ensuring urban functions, is essential to face climate related events and to assess the resilience to multiple hazards. This requires an integrated and multi-sectoral approach taking into account strategic urban sector and their interactions [8–10], but significant gaps have been found in risk-based approaches [11]. As emphasized by Reference [9], conceptual approaches based solely on vulnerability and precaution are limited and the adoption of the concept of resilience as a new paradigm allows for the implementation of more integrated risk management in a systemic manner (p.237).

Cities and towns rely on water systems, some incorporating components built over 200 years ago, built gradually following population growth. These systems are functional and represent a high asset value. Rehabilitation rates are already lower than needs today and expectations are for continued deterioration and low investments [12], especially in sewerage. Service failures affect society, for instance, whenever volumes exceed transport, treatment or storage capacities, and excess water often results in flooding. Consequences of flood events are multidimensional, including adverse effects on the water services, health and safety of populations, socio-economy and environment. Mobility, wastes and electricity supply are some of the sectors often affected by flooding and potentially propagating their effects [8,11,13–16].

Assessment of resilience and selection of options to improvement depends on two key steps [17,18]: characterization of flood events, which determines exposed assets and population; and estimation of vulnerability to allow estimating magnitude of damages for specific types of events. Limitations on risk identification determine the robustness of subsequent analysis, from exposure to impacts estimation.

The work presented herein is part of a broader approach (RESCCUE: *Resilience to cope with climate change in urban areas – a multisectorial approach focusing on water* project) to enable city resilience assessment, planning and management by incorporating new and existing knowledge of the urban systems performance under climate change conditions in a water-centred multi-risk assessment of strategic urban services performance using a comprehensive resilience platform [10]. The assessment of urban resilience from a multisector approach is carried out for current and future climate scenarios, and includes multiple risks.

Sound assessment of the resilience to flooding requires the systematic identification of risks and corresponding hazards, risk factors and risk sources for dealing with current and expected future levels of risk in order to increase the resilience of cities, using the available information. This paper presents the developments in terms of risk identification related with climate change effects and services interdependencies, specifically for flood related hazards. The approach aims at setting a practicable methodology in a background of limitations in data and in ready-to-use tools using the city of Lisbon as a study case, including the spatial characterization of these hazards. The results are essential to supporting the assessment of the resilience to these hazards of essential urban functions such as mobility, wastes management and electricity supply, taking into account interdependencies and cascading effects. The paper details developments relevant for the mobility and wastes management sectors. The electrical sector, deemed essential for the city, has a Quality Service Zone Type A for the design and planning of the network, implying the existence of incremental layers of resilience and the robustness of the grid, while minimizing the impact in case of disruption. A Type A Zone has high-level redundancy in the electricity supply service [19].


**Acknowledgements**

The authors would like to thank the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) and the German Federal Ministry for Economic Affairs and Energy (BMWi) for funding and supporting the work presented in this chapter.


*2.3. Properties*

In this sub-section we study some properties of the MSHN distribution.

**Proposition 2.** *Let T* ∼ *MSHN*(*σ*, *q*)*, then when σ* = *q* = 1 *the density is*

$$f\_T(t) = \frac{4}{t^2} \left( \frac{1}{\sqrt{2\pi}} - \frac{2}{t} \exp(2/t^2) \Phi \left( -\frac{2}{t} \right) \right), \quad t > 0,\tag{5}$$

*where* Φ(·) *is the cdf of the standard normal.*

**Proof.** Using Proposition 1 for *σ* = *q* = 1, we have,

$$f\_{\Gamma}(t) = \frac{2}{\sqrt{2\pi}t^2} N\left(1, \frac{2}{z}, \frac{1}{2}, \frac{1}{2}\right) = \frac{2}{\sqrt{2\pi}t^2} \int\_0^\infty \exp\left(-\frac{2}{z}\mathbf{x}^{1/2} - \frac{1}{2v^2}\mathbf{x}\right) d\mathbf{x}, \quad t > 0. \tag{6}$$

Changing the variable *x* = *u*2 we obtain the result.

**Proposition 3.** *If T*|*W* = *w* ∼ *HN σw and Y*1/*q* = *W* ∼ *Wei*(*q*, 1/2) *then T* ∼ *MSHN*(*σ*, *q*)*.*

**Proof.** Since the marginal pdf of *T* is given by

$$f\_T(t; \sigma, q) = \int\_0^\infty f\_{T|W}(t|w) f\_W(w) \, dw = \frac{4q}{\sigma \sqrt{2\pi}} \int\_0^\infty w^q e^{-\frac{w^2 t^2}{2\sigma^2} - 2w^q} \, dw\_\sigma$$

and using the Lemma 1 in the Appendix A, the result is obtained.

**Proposition 4.** *Let T* ∼ *MSHN*(*σ*, *q*)*. If q* → ∞ *then T converges in law to a random variable T* ∼ *HN*(*σ*)*.*

**Proof.** Let *T* ∼ *MSHN*(*σ*, *q*) and *T* = *XY*1/*q* , where *X* ∼ *HN*(*σ*) and *Y* ∼ *Exp*(2). We study the convergence in law of *T*, since *Y* ∼ *Exp*(2) then *W* = *Y*1/*q* ∼ *Wei*(*q*, 1/2), we have that *E* (*W* − 1)2 = 1 22/*q* Γ(1 + 2/*q*) − 2 21/*q* Γ(1 + 1/*q*) + 1. If *q* → ∞ then *E* (*W* − 1)2 → 0, i.e., we have *W* P−→ 1 (see Lehmann [9]).

Since *T* ∼ *MSHN*(*σ*, *q*), by applying Slutsky's Lemma (see Lehmann [9]) to *T* = *XW* , we have

$$T \stackrel{\mathcal{L}}{\longrightarrow} X \sim HN(\sigma), \qquad \eta \to \infty,\tag{7}$$

that is, for increasing values of *q*, *T* converges in law to a *HN*(*σ*) distribution.

**Remark 1.** *Proposition 2 shows us that the MSHN*(1, 1) *distribution has a closed-form expression. Proposition 3 shows that an MSHN*(*σ*, *q*) *distribution can also be obtained as a scale mixture of an HN and a Wei distribution. This property is very important since it makes it possible to generate random numbers and implement the EM algorithm. Proposition 4 implies that, if q* → ∞ *then the cdf of an MSHN*(*σ*, *q*) *model approaches to the cdf of a HN*(*σ*) *distribution.*


Orthodontic-Periodontics: An Interdisciplinary Approach

*Shreya Kishore, Vanita Barai, Suvetha Siva and Keerthi Venkatesan*

### **Abstract**

Periodontal pathogenesis is a multi-factorial process and the orthodontist must recognize the clinical forms of inflammatory periodontal disease. Orthodontics is the most conservative and predictable treatment to improve numerous local etiological factors that contribute to periodontal disease including periodontal breakdown. Proper occlusal function and masticatory function are stimulatory to the gingival tissue and the attachment apparatus, while, conversely, a lack of function predisposes to disease that increases plaque retention and calculus formation along with gingival inflammation leading to increased loss of bony support. No matter how talented the orthodontist, a magnificent orthodontic correction can be destroyed by failure to recognize periodontal susceptibility. Therefore, identifying periodontally susceptible patients is critical for the outcome of the treatment. This chapter will highlight the importance of the short-term and long-term outcomes of orthodontic treatment, which are influenced by the patient's periodontal status before, during and after active orthodontic therapy.

**Keywords:** Bio-relationship, Interdisciplinary approach, Adjunctive periodontal procedures, Periodontium, Orthodontia, Periodontal healing

#### **1. Introduction**

Periodontal care should be directed towards eliminating the bacterial infection and preventing reinfection. This involves creating an environment which encourages self-cleansing and is less conducive to harboring pathogenic bacteria. Appropriate therapy for each individual depends on the type, severity and morphology created by the specific disease, along with cooperation from the patient. Regardless, elimination of as many plaque-retentive areas should always be the primary objective of a treatment. Large number of teeth are extracted to eliminate periodontal defects (that act as bacterial reservoirs) that can be corrected by simple tooth eruption [1].

Although orthodontic treatment may not be considered preventive or corrective of periodontitis, it is one of the solutions to reduce the local factors. Patients with predisposing periodontal health tend to experience movement in teeth, as there will be comparatively lesser periodontal support. Commonly occurring movements of teeth include migration of teeth, intrusion, extrusion and flaring of teeth. In such cases, orthodontic treatment helps in eliminating the malposition of teeth but also aids in long term maintenance [2].


*2.5. Parameterization of Depth-Induced Wave Breaking*

Three widely used parameterizations for characterizing depth-induced wave breaking in nearshore shallow waters were adopted in the present study and are briefly reviewed in this section. Battjes and Beji [47] proposed that the total energy dissipation can be distributed over the wave spectrum in proportion to the spectral density based on extensive laboratory experiments; hence, the wave-induced wave breaking (*Sbreak*) in the wave action density function is calculated as follows:

$$S\_{brck}(\sigma,\theta) = D\_{total} \frac{E(\sigma,\theta)}{E\_{total}} \tag{3}$$

where *Sbreak(σ*,*θ)* is the wave-induced wave breaking in spectral space (*σ*, *θ*), *Dtotal* is the total energy dissipation rate due to depth-induced wave breaking, *E(σ*,*θ)* is the wave energy in spectral space (*σ*, *θ*) and *Etotal* is the total wave energy.


**5. Comparison with existing methods**

One can attempt to make a comparison with the previous methods12, 16, 24 in terms of efficiency. The first one proposed by Uzam12, called *Algorithm U*, is totally based on the theory of regions. It solves six ESSPs in Example I. Then three control places are added on the net such that the controlled net is live and reversible. As for Example II, it solves 59 MTSIs. Nine control places are obtained. However, the proposed deadlock prevention policy called *Algorithm P* solves only two and 18 CMTSIs in Examples I and II, respectively.

A Computationally Improved Optimal Solution

*U ||*

*P ra*

*P rb*

for Deadlocked Problems of Flexible Manufacturing Systems Using Theory of Regions 71

*U ||*

*L ||*

*L*

 *||*

*Algorithm U* in Table 11 since the number of MTSIs and ESSPs are the same. In table 11, here, *Nsep* represents the number of MTSIs, and the *Nsep*/*U, Nsep*/*L* and *Nsep*/*P* represent the number of MTSIs of *Algorithms U, L*, and *P*, respectively. Obviously, the number of ||*U* in the plant model grows quickly from cases 1 to 8. For instance, when *M* (*p*15) = *M* (*p*18) = *M* (*p*19) = 5, ||*U* = 4311, meaning that one must solve 4311 MTSIs when *Algorithm U* is used. However, since ||*P* = 228, only 228 equations (MTSIs) need to be solved under *Algorithm P*. As a

1 282 205 16 59 18 30.5% 2 600 484 27 95 28 29.5% 3 972 870 26 103 26 25.2% 4 570 421 16 107 19 17.8% 5 4011 3711 42 288 42 14.6% 6 27152 26316 84 886 84 9.5% 7<PHONE_NUMBER>35 145 2115 145 6.9% 8<PHONE_NUMBER>90 228 4311 228 5.3%

**Table 11.** Parametersin the Plant and Partially Controlled Models with Varying Markings: *U* vs. *P*.

**Table 12.** Parametersin the Plant and Partially Controlled Models with Varying Markings: *L* vs. *P*.

In Table 12, the number of MTSIs calculated by *Algorithm L* can be controlled, but *Algorithm P* is more efficient in these cases. For instance, when *M* (*p*15) = *M* (*p*18) = *M* (*p*19) = 5, ||*L* = 192, meaning that one still has to solve 192 MTSIs when *Algorithm L* is used. However, ||*P* =108. Only 108 MTSIs need to be solved by using *Algorithm P*. Importantly, the computational cost can be reduced by using our proposed method when it is compared with those in12, 16. In conclusion, *Algorithm P* is more efficient in large reachability graph cases

The proposed policy can be implemented for FMSs based on the theory of regions and Petri nets, where the dead markings are identified in its reachability graph. The

1 282 205 1 8 1 12.5% 2 600 484 1 8 1 12.5% 3 972 870 6 10 6 60.0% 4 570 421 1 8 1 12.5% 5 4011 3711 9 15 9 60.0% 6 27152 26316 28 48 28 58.3% 7<PHONE_NUMBER>35 60 105 60 57.1% 8<PHONE_NUMBER>90 108 192 108 56.3%

result, *Algorithm P* is more efficient than *Algorithm U* in a large system.

**CASES** *|R| |ML| |RD|*

**CASE** *|R| |ML| |RD|*

than those in12-13.

**6. Conclusion**

The other one is proposed by Li *et al*. 16, 24 called *Algorithm L* in which only the theory of regions is used in Example I. Notice that both the controlled results of *Algorithms L* and *U* are the same in Example I. In Example II, using *Algorithm L,* eight MTSIs are solved and six control places are computed. However*,* under the two-stage control policy, only one set of MTSI is needed by using our new policy to obtain the controlled result that is as the same as *Algorithm L* in Example II. Note that both the definitions of ESSP and MTSI are the same. Hence, ESSP and CMTSI can be regarded as MTSI for the comparison purpose. The detailed comparison results are given in Table 10. However, only 18 MTSIs among 59 MTSIs are needed by using *Algorithm P*.

**Table 10.** Comparison of the Controlled Systems.

For Example II, eight MTSIs are required to obtain the six control places under *Algorithm L*. Hence, one can infer that its performance is better than that of *Algorithm U*. Only one set of CMTSI is needed to obtain the same control result by *Algorithm P*. As a result, one can conclude that our proposed policy is more efficient than the other two methods.

To examine and compare the efficiency of the proposed method with those in16, 24 in a system with large reachability graphs, one can use eight different markings of *p*1, *p*8, *p*15, *p*18, and *p*19: [6, 5, 1, 1, 1]T, [7, 6, 2, 1, 1]T, [7, 6, 1, 2, 1]T , [7, 6, 1, 1, 2]T, [9, 8, 2, 2, 2]T, [12, 11, 3, 3, 3]T, [15, 14, 4, 4, 4]T, and [18, 17, 5, 5, 5]T. Tables 11 and 12 show various parameters in the plant and partially controlled net models, where *M* (*p*15), *M* (*p*18), and *M* (*p*19) vary; |*R*|, |*ML*|, |*RD*|*U*, |*RD*|*L*, indicate the number of reachable markings (states), legal markings, and dead markings under *Algorithms U* and *L,* respectively. Additionally, MTSIs of *Algorithms U, L*, and *P* are symbolized by ||*U*, ||*L* and ||*P*, respectively. The last column is *ra* = ||*P* / ||*U* in Table 11, and *rb* = |*P* / ||*L* in Table 12. Notably, *Algorithm G*13 can be regarded as *Algorithm U* in Table 11 since the number of MTSIs and ESSPs are the same. In table 11, here, *Nsep* represents the number of MTSIs, and the *Nsep*/*U, Nsep*/*L* and *Nsep*/*P* represent the number of MTSIs of *Algorithms U, L*, and *P*, respectively. Obviously, the number of ||*U* in the plant model grows quickly from cases 1 to 8. For instance, when *M* (*p*15) = *M* (*p*18) = *M* (*p*19) = 5, ||*U* = 4311, meaning that one must solve 4311 MTSIs when *Algorithm U* is used. However, since ||*P* = 228, only 228 equations (MTSIs) need to be solved under *Algorithm P*. As a result, *Algorithm P* is more efficient than *Algorithm U* in a large system.

**Table 11.** Parametersin the Plant and Partially Controlled Models with Varying Markings: *U* vs. *P*.

**Table 12.** Parametersin the Plant and Partially Controlled Models with Varying Markings: *L* vs. *P*.

In Table 12, the number of MTSIs calculated by *Algorithm L* can be controlled, but *Algorithm P* is more efficient in these cases. For instance, when *M* (*p*15) = *M* (*p*18) = *M* (*p*19) = 5, ||*L* = 192, meaning that one still has to solve 192 MTSIs when *Algorithm L* is used. However, ||*P* =108. Only 108 MTSIs need to be solved by using *Algorithm P*. Importantly, the computational cost can be reduced by using our proposed method when it is compared with those in12, 16. In conclusion, *Algorithm P* is more efficient in large reachability graph cases than those in12-13.


**3. Discussion**

The prevalence of GOIA might be as high as 38%, and it is 3.3 times more common in men than in women [20,21]. The pathogenesis may be different for different drugs, even if the oral manifestations of gingival overgrowth are similar. GOIA starts as an enlargement of the interdental papilla of keratinized portions of the gingiva, and it is characterized by an increase in the connective tissue component. Bacteria accumulation appears to be an important uncomfortable effect of GOIA. GOIA may impair oral hygiene and lead to increased oral infections. Oral infection itself is a cause of gingival overgrowth [22]. In addiction, oral infection can potentially impair systemic health and could possibly compromise the general health of patients [22].

The mechanism of action of GOIA is still unknown, however it may be a consequence of the interaction between gingival fibroblasts, cellular and biochemical mediators of inflammation, and drug metabolites [22,23].

Gingival overgrowth is documented more frequently after intake of with phenytoin and rarely with others antihypertensive [24]. Furthermore, poor oral hygiene is indicated as an important risk factor for the expression of GOIA [25,26].

Cross-sectional studies have reported the relationship between bacterial plaque and GOIA. In fact, as previously reported, GOIA can favour the accumulation of bacterial plaque, which in turn determines gingival inflammation, causing gingival overgrowth [26]. The underlying mechanism of GOIA still remains to be fully understood, however two main inflammatory and non-inflammatory pathways have already been suggested [27–29]. One hypothesis may be that amlodipine may induce the alteration of collagenase activity as a consequence of decreased uptake of folic acid, blockage of aldosterone synthesis in adrenal cortex, and consequent feedback increase in the adrenocorticotropic hormone level and the up-regulation of keratinocyte growth factor [30]. Besides, inflammation may be a consequence of the toxic effect of amlodipine in periodontal pocket associated with C pathogens, leading to the up-regulation of several cytokine factors, such as transforming growth factor-beta 1 (TGF-β1) [9]. Another pathogenic mechanism of GOIA is focusing on the effects of amlodipine on gingival fibroblast metabolism and genetic predisposition. In fact, only a subgroup of patients that were treated with this amlodipine will develop GOIA, so it has been hypothesized that these individuals show an abnormal susceptibility to the drug. In fact, elevated levels of protein synthesis, most of which is collagen, characterize the fibroblast of GOIA in these patients. Treatment of GOIA is generally targeted on drug substitution and preventive protocols [12,31]. Surgical intervention is recommended when these measures fail to cause the resolution of GOIA. These treatment modalities, although effective, do not necessarily prevent the recurrence of the lesions [12]. Surgery for treatment of GOIA must be carefully assessed and it is normally performed for cosmetic/aesthetic needs before any functional consequences are present [1,32]. Most reports of GOIA have required surgical intervention [25].

To our knowledge, our study is the first one analysing the effect of amlodipine on genes that belong to the "Extracellular Matrix and Adhesion Molecules" pathway. In this study, gingival fibroblasts were treated for 24 h with 1000 ng/mL of amlodipine. The gene expression profile of 12 genes that belong to the "Extracellular Matrix and Adhesion Molecules" pathway was analysed. Most of the significant genes were up-regulated. (*CTNND2*, *COL4A1*, *ITGA2*, *ITGA7*, *MMP10*, *MMP11*, *MMP12*, *MMP26*), except for *COL7A1*, *LAMB1*, *MMP8*, and *MMP16*, which were down-regulated. These proteins preferentially induce extra cellular matrix deposition. This study demonstrated that, in human gingival fibroblasts that were cultivated in vitro, amlodipine could promote the activities of genes belonging to the "fibroblast matrix and receptors".

It might be part of the underlying reason for the persistent overgrowth of gingiva that was seen when bacterial plaque and local inflammation are present during amlodipine therapy. In fact, GOIA does not allow patient to maintain a good oral hygiene, and this is the reason why GOIA always determines the presence of bacterial plaque and inflammation, which in turn determines gingival overgrowth.

The data presented here suggest that amlodipine may contribute to an extracellular matrix deposition of human gingival fibroblasts inducing gingival overgrowth.

### **4. Materials and Methods**

### *4.1. Primary Human Fibroblast Cells Culture*

We used cells from ATCC® Cell Lines. The cryopreserved cells at the second passage were cultured in 75 cm2 culture flasks containing DMEM medium (Sigma Aldrich, Inc., St Louis, Mo, USA) supplemented with 20% fetal calf serum, antibiotics (Penicillin 100U/ml and Streptomycin 100 micrograms/ml-Sigma Aldrich, Inc., St Louis, Mo, USA).

Cell cultures were replicated for subsequent experiments and maintained in a water saturated atmosphere at 37 ◦C and 5% CO2.

### *4.2. Cell Viability Test*

A stock solution of amlodipine 1 mg/mL was prepared. Further dilutions were made with the culture medium to the desired concentrations just before use. The cell lines were seeded into 96-well plates at a density of 104 cells per well containing 100 μL of cell culture medium and incubated for 24 h to allow cell adherence. Serial dilution of amlodipine (5000 ng/mL, 2000 ng/mL, 1000 ng/mL, 500 ng/mL, 100 ng/mL) was added (three wells for each concentration). The cell culture medium alone was used negative control.

After 24 h of incubation, cell viability was measured while using PrestoBlue™ Reagent Protocol (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. Briefly, the PrestoBlue™ solution (10 μL) was added into each well containing 90 μL of treatment solution. The plates were then placed back into the incubator for 1 h, after which absorbance was measured at wavelengths of 570 nm excitation and 620 nm emission by an automated microplate reader (Sunrise™, Tecan Trading AG, Switzerland). Comparing the average absorbance in drug treated wells with average absorbance in control wells exposed to vehicle alone determined the percentage of viable cells.


When Slovenia in 2004 became a full member of the European Union and the European University Area, the Bologna Process started, to which the members of this area are bound. It encompasses a unique model regarding studies. This has meant reassessing and changing the traditional curricula towards a single-study structure within European Universities (Krajnc, 2009).

The Bologna study programmes at FCCE started during the academic year 2009/2010. Each year the results show that a lot of students register in the first study year, which causes a lot of pedagogic workload for the staff. As the application of IC learning environments is particularly useful when a lot of students are enrolled, Moodle was incorporated within some Bologna Courses i.e. Computer Science in Chemistry Course (CSC), and Process Calculation I Course (PC I) in the first semester, and Process Calculation II Course (PC II), Chemical Calculation II Course (CC II), and Process Balances Course (PB) in the second semester. On the basis of the previous experiences from the Process Synthesis Course, the electronic assessment of knowledge was also incorporated into the mentioned Bologna courses. Lectures at all courses were given once a week (3 hours every week). The lecturer explained the main points of the material, and the students learned the rest by themselves. The following explains the electronic assessment procedures at some courses.

At the Computer Science in Chemistry Course and Process Calculation I Course of the first semester, electronic assessment was introduced to the freshman three times, half an hour before regular lectures, and in a computer room of the Faculty. Each e-test was administrated only once. It was forbidden to write down the questions on the paper. A student was successful if at least 60 % of the answers were correct.

In order to obtain freshman's feedback on the applicability, usefulness, and efficiency of e-assessment, at the end of the semester students filled-in a questionnaire and answered certain questions. It was comprised of 16 questions, 13 of which were multiple-choice type questions and three were essay-type questions. The questionnaire was classified into four parts where students gave their opinions on:

109 of the students filled-in the questionnaire. The results showed that 10 % of students used the electronic-learning environment Moodle every day, 82 % once a week, and the rest (8 %)

E-Learning Usage During Chemical Engineering Courses 133

From among the 109 students who started the electronic-assessment of their knowledge at CSC and PC I, 78 students (72 %) finished all e-tests successfully, 19 students (17 %) resigned from electronic-assessment because of negative grades, and 12 students (11 %) resigned from e-assessment because they changed their mind about such a kind of assessment or study, in general. Some students also realised that such a kind of work is too difficult for

The analysis of 116 active students i.e. those who finished the experimental computer work in the computer room, after completing the lectures at CSC and PC I, showed that 78 of them completed all the e-tests successfully. The others (38 of the active students or 33 %) had to move to the classical oral exam. The results showed that the lecturers' workloads regarding oral examinations decreased by 67 %. So, what does this mean in hours regarding lecturers' workloads? When you consider that one student needs approximately half an hour for a classical oral examination, 78 students meant 39 less hours needed for oral examinations, which is almost one working week. Within such a time-period, a lecturer could do other things e.g. research work, additional notes regarding course material, prepare new problems for written exams etc. It is also important to point out that the students saved time, too. They did not need extra time at the Faculty for the examination, so

Enthusiasm for introducing new methods into the educational process is not as great amongst the teaching staff as with the students. This was already apparent at the time of the ELEUM application. The first responses from the lecturers and assistants were obtained at the end of the academic year 2005/2006, on the basis of a questionnaire which was sent to all teaching staff at the Faculty. The results showed that half of the teaching staff was completely disinterested in e-learning or they were so occupied with other duties that they had no time to answer the questionnaire (Krajnc, 2009). The other half showed resistance to

Anyway, awareness of electronic-teaching and learning has expanded among the staff from year to year. The more experienced lecturers in e-learning are constantly encouraging colleagues towards the new method of working. The application of different activities within e-learning are presented every year at the "*Slovenian Chemical Days, Conference"* which takes place at the FCCE in Maribor every autumn. The Computer Centre of the UM, Department for e-learning, prepares learning workshops three times a year. Recently, in December 2010, a Workshop on the electronic-teaching environment Moodle's usage was held at FCCE in Maribor. The Workshop was led by a lecturer of the Faculty who has many years experiences in e-learning. The participation of the teaching staff was very low. Only six lecturers and assistants were interested in Moodle application during the pedagogical process. At the end of the Workshop, participants filled-in an electronic questionnaire which included six questions concerning Moodle's application. On the question »*How often do you use Moodle*?« one answered several times a year, two of them replied never, and three of them said once a week. Their knowledge of Moodle was estimated at a 1,7 grade on a five point scale (1-insufficient, 2-sufficient, 3-well, 4-very good, 5-excellent). They said, they used

they saved time and money on bus or train tickets, or fuel if they had a car.

**3.2 The response of the teaching staff to e-learning**

use of electronic-teaching tools within their courses.

reading the question wrongly.

them.

Moodle:

once a month. They also said that the combination of traditional and electronic method of learning suited them and that they also wanted such a kind of work in other courses.

More than 71 % of the students' replies were the same as their older colleagues in the Process Synthesis Course, i.e. that they chose the electronic-assessment of knowledge because they had to become acquainted with smaller portions of the course material at once, the other students (29 %) chose the e-test because they wanted to avoid the oral exam in the professor's office. Three quarters of the students (74 %) said that after the first e-test they could better prepare for the others because after the first one they acquired a feeling for such a kind of examination. Almost all students (94 %) thought that they had enough time to answer all the questions in the e-assessment.

The lecturer also received a significant response about the intelligibilities and difficulties of the questions. The result showed that almost half the students (42 %) thought that the questions were always clear and easy to understand, and 50 % thought they were almost always understandable. 8 % of students replied that questions were sometimes understandable and sometimes not. Furthermore, 79 % of students said that questions were medium-difficult, 13 % thought they were easy, and 8 % that they were tough questions.

In one of the questions, the students compared electronic-assessment with the traditional oral exam. Almost half of the students (46 %) thought that the electronic-assessment of knowledge was easier than the classical one, 45 % said that it was easier and of higher quality, one student said it was of higher quality but difficult, and four students replied that it was easier but of a lesser quality than the classical oral exam. More than half of the students (68 %) felt less stressed at an e-examination as they had to confront the lecturer at a classical oral exam but more than a quarter of the students did not feel psychological burdened themselves by the e-test.

For the essay-type questions students gave their opinions on:

The students mainly said that the information was clear enough, effective, and practical. They wanted to have such information at other courses. The reasons for failures in e-tests were the lack of learning, reluctance at the exam, superficiality, difficult questions, and absence from lectures.

The advantages of the e-examination were:

The disadvantages were:

reading the question wrongly.

132 E-Learning – Engineering, On-Job Training and Interactive Teaching

once a month. They also said that the combination of traditional and electronic method of

More than 71 % of the students' replies were the same as their older colleagues in the Process Synthesis Course, i.e. that they chose the electronic-assessment of knowledge because they had to become acquainted with smaller portions of the course material at once, the other students (29 %) chose the e-test because they wanted to avoid the oral exam in the professor's office. Three quarters of the students (74 %) said that after the first e-test they could better prepare for the others because after the first one they acquired a feeling for such a kind of examination. Almost all students (94 %) thought that they had enough time to

The lecturer also received a significant response about the intelligibilities and difficulties of the questions. The result showed that almost half the students (42 %) thought that the questions were always clear and easy to understand, and 50 % thought they were almost always understandable. 8 % of students replied that questions were sometimes understandable and sometimes not. Furthermore, 79 % of students said that questions were medium-difficult, 13 % thought they were easy, and 8 % that they were tough questions.

In one of the questions, the students compared electronic-assessment with the traditional oral exam. Almost half of the students (46 %) thought that the electronic-assessment of knowledge was easier than the classical one, 45 % said that it was easier and of higher quality, one student said it was of higher quality but difficult, and four students replied that it was easier but of a lesser quality than the classical oral exam. More than half of the students (68 %) felt less stressed at an e-examination as they had to confront the lecturer at a classical oral exam but more than a quarter of the students did not feel psychological

The students mainly said that the information was clear enough, effective, and practical. They wanted to have such information at other courses. The reasons for failures in e-tests were the lack of learning, reluctance at the exam, superficiality, difficult questions, and

learning suited them and that they also wanted such a kind of work in other courses.

answer all the questions in the e-assessment.

burdened themselves by the e-test.

The advantages of the e-examination were:

instant feedback of the results,

ambiguous questions and answers,

no possibility of repeating e-tests,

e-test failure,

absence from lectures.

on-going learning,

 less time to learn, you are not under stress.

The disadvantages were:

quickly forget the theory,

For the essay-type questions students gave their opinions on: information about the Course activities through Moodle,

advantages and disadvantages of e-assessing knowledge.

From among the 109 students who started the electronic-assessment of their knowledge at CSC and PC I, 78 students (72 %) finished all e-tests successfully, 19 students (17 %) resigned from electronic-assessment because of negative grades, and 12 students (11 %) resigned from e-assessment because they changed their mind about such a kind of assessment or study, in general. Some students also realised that such a kind of work is too difficult for them.

The analysis of 116 active students i.e. those who finished the experimental computer work in the computer room, after completing the lectures at CSC and PC I, showed that 78 of them completed all the e-tests successfully. The others (38 of the active students or 33 %) had to move to the classical oral exam. The results showed that the lecturers' workloads regarding oral examinations decreased by 67 %. So, what does this mean in hours regarding lecturers' workloads? When you consider that one student needs approximately half an hour for a classical oral examination, 78 students meant 39 less hours needed for oral examinations, which is almost one working week. Within such a time-period, a lecturer could do other things e.g. research work, additional notes regarding course material, prepare new problems for written exams etc. It is also important to point out that the students saved time, too. They did not need extra time at the Faculty for the examination, so they saved time and money on bus or train tickets, or fuel if they had a car.

#### **3.2 The response of the teaching staff to e-learning**

Enthusiasm for introducing new methods into the educational process is not as great amongst the teaching staff as with the students. This was already apparent at the time of the ELEUM application. The first responses from the lecturers and assistants were obtained at the end of the academic year 2005/2006, on the basis of a questionnaire which was sent to all teaching staff at the Faculty. The results showed that half of the teaching staff was completely disinterested in e-learning or they were so occupied with other duties that they had no time to answer the questionnaire (Krajnc, 2009). The other half showed resistance to use of electronic-teaching tools within their courses.

Anyway, awareness of electronic-teaching and learning has expanded among the staff from year to year. The more experienced lecturers in e-learning are constantly encouraging colleagues towards the new method of working. The application of different activities within e-learning are presented every year at the "*Slovenian Chemical Days, Conference"* which takes place at the FCCE in Maribor every autumn. The Computer Centre of the UM, Department for e-learning, prepares learning workshops three times a year. Recently, in December 2010, a Workshop on the electronic-teaching environment Moodle's usage was held at FCCE in Maribor. The Workshop was led by a lecturer of the Faculty who has many years experiences in e-learning. The participation of the teaching staff was very low. Only six lecturers and assistants were interested in Moodle application during the pedagogical process. At the end of the Workshop, participants filled-in an electronic questionnaire which included six questions concerning Moodle's application. On the question »*How often do you use Moodle*?« one answered several times a year, two of them replied never, and three of them said once a week. Their knowledge of Moodle was estimated at a 1,7 grade on a five point scale (1-insufficient, 2-sufficient, 3-well, 4-very good, 5-excellent). They said, they used Moodle:

E-Learning Usage During Chemical Engineering Courses 135

During the academic years 2008/2009, 2009/2010 and 2010/2011, a group of students who had the possibility of using the multimedia e-chapter on the Process Synthesis Course, gave feedback about its usage to the lecturer on the basis of a questionnaire. It consisted of 8 questions, 5 of which were multiple-choice questions, and 3 essay-type questions. The questionnaire was filled-in by 53 students. Among these were also those who had not used the e-chapter. The main reason why they had not used it was that they did not know that such a kind of chapter even existed, because they had not followed the news and

The results showed that students mainly used both possibilities for learning i.e. the chapter in classical text-book, which is available, and the multimedia electronic chapter (72 %). Of those students who used the multimedia e-chapter, 77 % thought that such a kind of chapter was more appropriate for learning than the classical chapter because it consists of modules for dynamic learning, and 88 % said that they needed less time for studying the chapter material with the e-chapter in comparison with the classical one. More theory was retained in the memory. The same number of students realised that the multimedia e-chapter usage

On the question as to why they did or did not use the multimedia e-chapter, students gave

One student said: »*The content in the multimedia e-chapter is more transparent and regulated.*

One student thought: »*I prefer the classic way of learning from my notes where I can underline the*

The answer of one student was interesting: »*Such learning is tiring for the eyes. You have to look*

Undergraduate-study reforms have placed the student at the centre of the education process. The curricula have been mainly reduced, so that students themselves undertake more responsibilities for better study results. For this reason, the traditional methods of teaching and learning should now be supplemented by non-traditional methods and technologies. These include active and cooperative learning, project work, and e-learning, which help students achieve better results. Students at the FCCE in Maribor, Slovenia now have significant experience with non-traditional learning methods, especially with elearning. They use electronic-learning environments and e-materials, which enable communication between lecturer-student and the assessment of knowledge. Different kinds of e-tools enable the students to obtain good study results. Since the Chapter focuses on the experiences of e-learning usage from both the students' and pedagogic staffs' points of view, the electronic environments, and their functionalities were not presented in detail. They

have already been described in other sources (Krajnc, 2006; Krajnc, 2009).

was a good preparation for the electronic-assessment of knowledge.

Another replied: »*It is great because you can check your knowledge*.«

Another replied: »*I like the colour-coded words in the e-chapter*.«

instructions on Moodle, regularly.

different answers.

*Learning is more friendly*.«

*at the screen continuously*.«

**4. Conclusion**

*important things, and annotate the notes*.«

On the question »*Do you mean that Moodle facilitates the implementation of work and saves time*?« three of them agreed, one said it does not save time but facilitates the implementation of the pedagogic process, two of them could not agree or disagree with the statement as they had not used Moodle yet. Four participants of the Workshop knew that UM organises educational workshops on Moodle application three times a year but they had not participated in any of them yet. Two participants knew and already participated to them. The answers on the question »*Why don't you use Moodle more often*?« were similar i.e. they did not have enough time for additional education and they did not know enough about the Moodle application.

#### **3.3 Multimedia e-text-books (e-material)**

Because at e-learning, students' educations are largely left to them, text-books should be prepared in appropriate forms. Beside electronic learning environments and its tools and activities, which could be used within the learning process, multimedia electronic textbooks are useful tools, which additionally implement the education process. A lot of sources and modules can be inserted into such text-books such as: video, animations, internet links, short quizzes with different type of questions etc. In general, learning with multimedia e-materials is more motivated and successful compared with live lessons or other media (video, simulation, and a combination of graph and audio presentations), which enable easier learning. Such material adapts students to various learning styles and facilitates a constructive and enquiry-based approach to learning (Clark & Feldon, 2005; Krnel & Bajd, 2009). When students use multimedia e-text-books, they can better prepare themselves for examinations. Usually, they easily pass e-tests, oral, and written exams and colloquiums.

A quality multimedia e-text-book may only be prepared by the lecturer who teaches the subject. The preparation of an e-text-book is a great challenge, but interesting and responsible work, which takes a lot of time and effort. The lecturer often asks himself/herself what information should be included in e-material. He/she needs to be aware that the content should be clear and concise. Because multimedia e-material may contain animations, quizzes, online links etc., the lecturer should know where and how to enter these tools. His/her skills and knowledge of using them should be comprehensive.

An example of a multimedia e-chapter has already been created for the Process Synthesis Course at the FCCE in Maribor. The chapter is entitled Reaction-path Synthesis and it is an electronic version of the chapter, which is included in the classic text-book, and is usually available to students. The lecturer wanted to know how students will accept this version and what the study results will be achieved. Different types of electronic modules are included within the e-material as: cloze activities, multi-choice type questions, external websites, true-false questions, wiki articles, and reading activities. The eXe-learning XHTML editor was used for creating the multimedia e-chapter (New Zealand Government Tertiary Education Commission et al., 2011).

On the question »*Do you mean that Moodle facilitates the implementation of work and saves time*?« three of them agreed, one said it does not save time but facilitates the implementation of the pedagogic process, two of them could not agree or disagree with the statement as they had not used Moodle yet. Four participants of the Workshop knew that UM organises educational workshops on Moodle application three times a year but they had not participated in any of them yet. Two participants knew and already participated to them. The answers on the question »*Why don't you use Moodle more often*?« were similar i.e. they did not have enough time for additional education and they did not know enough about the

Because at e-learning, students' educations are largely left to them, text-books should be prepared in appropriate forms. Beside electronic learning environments and its tools and activities, which could be used within the learning process, multimedia electronic textbooks are useful tools, which additionally implement the education process. A lot of sources and modules can be inserted into such text-books such as: video, animations, internet links, short quizzes with different type of questions etc. In general, learning with multimedia e-materials is more motivated and successful compared with live lessons or other media (video, simulation, and a combination of graph and audio presentations), which enable easier learning. Such material adapts students to various learning styles and facilitates a constructive and enquiry-based approach to learning (Clark & Feldon, 2005; Krnel & Bajd, 2009). When students use multimedia e-text-books, they can better prepare themselves for examinations. Usually, they easily pass e-tests, oral, and written exams

A quality multimedia e-text-book may only be prepared by the lecturer who teaches the subject. The preparation of an e-text-book is a great challenge, but interesting and responsible work, which takes a lot of time and effort. The lecturer often asks himself/herself what information should be included in e-material. He/she needs to be aware that the content should be clear and concise. Because multimedia e-material may contain animations, quizzes, online links etc., the lecturer should know where and how to enter these tools. His/her skills and knowledge of using them should be comprehensive.

An example of a multimedia e-chapter has already been created for the Process Synthesis Course at the FCCE in Maribor. The chapter is entitled Reaction-path Synthesis and it is an electronic version of the chapter, which is included in the classic text-book, and is usually available to students. The lecturer wanted to know how students will accept this version and what the study results will be achieved. Different types of electronic modules are included within the e-material as: cloze activities, multi-choice type questions, external websites, true-false questions, wiki articles, and reading activities. The eXe-learning XHTML editor was used for creating the multimedia e-chapter (New Zealand Government Tertiary

 for informing and sending exam grades, for the publication of study materials,

**3.3 Multimedia e-text-books (e-material)**

for displaying a list of students.

for questionnaires,

Moodle application.

and colloquiums.

Education Commission et al., 2011).

During the academic years 2008/2009, 2009/2010 and 2010/2011, a group of students who had the possibility of using the multimedia e-chapter on the Process Synthesis Course, gave feedback about its usage to the lecturer on the basis of a questionnaire. It consisted of 8 questions, 5 of which were multiple-choice questions, and 3 essay-type questions. The questionnaire was filled-in by 53 students. Among these were also those who had not used the e-chapter. The main reason why they had not used it was that they did not know that such a kind of chapter even existed, because they had not followed the news and instructions on Moodle, regularly.

The results showed that students mainly used both possibilities for learning i.e. the chapter in classical text-book, which is available, and the multimedia electronic chapter (72 %). Of those students who used the multimedia e-chapter, 77 % thought that such a kind of chapter was more appropriate for learning than the classical chapter because it consists of modules for dynamic learning, and 88 % said that they needed less time for studying the chapter material with the e-chapter in comparison with the classical one. More theory was retained in the memory. The same number of students realised that the multimedia e-chapter usage was a good preparation for the electronic-assessment of knowledge.

On the question as to why they did or did not use the multimedia e-chapter, students gave different answers.

One student said: »*The content in the multimedia e-chapter is more transparent and regulated. Learning is more friendly*.«

Another replied: »*It is great because you can check your knowledge*.«

One student thought: »*I prefer the classic way of learning from my notes where I can underline the important things, and annotate the notes*.«

Another replied: »*I like the colour-coded words in the e-chapter*.«

The answer of one student was interesting: »*Such learning is tiring for the eyes. You have to look at the screen continuously*.«

#### **4. Conclusion**

Undergraduate-study reforms have placed the student at the centre of the education process. The curricula have been mainly reduced, so that students themselves undertake more responsibilities for better study results. For this reason, the traditional methods of teaching and learning should now be supplemented by non-traditional methods and technologies. These include active and cooperative learning, project work, and e-learning, which help students achieve better results. Students at the FCCE in Maribor, Slovenia now have significant experience with non-traditional learning methods, especially with elearning. They use electronic-learning environments and e-materials, which enable communication between lecturer-student and the assessment of knowledge. Different kinds of e-tools enable the students to obtain good study results. Since the Chapter focuses on the experiences of e-learning usage from both the students' and pedagogic staffs' points of view, the electronic environments, and their functionalities were not presented in detail. They have already been described in other sources (Krajnc, 2006; Krajnc, 2009).

E-Learning Usage During Chemical Engineering Courses 137

Felder, R., Woods, D. R., Stice, J. E. & Rugarcia, A. (2000). The future of Engineering

Floyed Smith, T., Baah, D., Bradley, J., Sidler, M., Hall, R., Daughtrey, T. & Curtis, C. (2000).

Granda, J. C., Uria, C., Suarez, F. J. & Garcia, D. F. (2010). Supporting Technologies for

Hadley, K. R. & Debelak, K. A. (2009). Wiki Technology as a design tool for a Capstone

Hussmann, S., Covic, G. & Patel N. (2004). Effective Teaching and Learning in Engineering

Krajnc, M. (2008). Electronic assessment of knowledge in chemical engineering courses,

Krajnc, M. (2009). E-learning Environment Integration in the Chemical Engineering Education Process, *Int. J. Eng. Ed.*, Vol. 25, No. 2, pp. 349-357. ISSN: 0949-149X. Krnel, D. & Bajd, B. (2009). Learning and e-materials, *Acta Didactica Napocensia*, Vol. 2, No. 1,

Lau, H. Y. K. & Mak, K. L. (2005). A Configurable E-learning System for Industrial Engineering, *Int. J. Eng. Ed.*, Vol. 21, No. 2, pp. 262-276. ISSN: 0949-149X. Le Roux, G. A. C., Reis, G. B., de Jesus, C. D. F., Giordano, R. C., Cruz, A. J. G., Moreira Jr., P.

Maurice, S. A. & Lissel, S. (2006). Evaluating Online Testing Technology, *Int. J. Eng. Ed.*, Vol.

New Zealand Government Tertiary Education Commission, The Auckland University, The

Paik, W., Lee, J. Y. & McMahon, E. (2004). Facilitating Collaborative Learning in Virtual

Peat, M. (2000). Towards first year biology online: a virtual learning environment. *Educational Technology & Society*, Vol. 3, No. 3, pp. 203-207. ISSN 1436-4522. Pei-Chen, S., Tsai, R. J., Finger, G., Yueh-Yang, C. & Yeh, D. (2008). What drives a succeeful

Electronics, *Int. J. Eng. Ed.*, Vol. 20, No. 2, pp. 161-169. ISSN: 0949-149X. Krajnc, M. (2006). Incorporating e-learning into educational process, *Proceedings of CHISA*

*2006* on CD-ROM, Prague, August 2006. ISBN 80-86059-45-6.

*Engr. Education*, Vol. 44, No. 1, pp. 9-12. ISSN: 0009-2479.

learning XHTML editor. In: *online*. July 2011, Available from:

22, No. 4, pp. 839-848. ISSN: 0949-149X.

*Workshops*, Brisbane, Australia, November 2004.

1, pp. 26-39. ISSN: 0009-2479.

pp. 97-107. ISSN 2065-1430.

*http://exelearning.org/wiki*

111-128, InTech, ISBN 978-953-307-092-6.

2479.

2479.

9.

Education, Part 2. Teaching Methods that work, *Chem. Engr. Education*, Vol. 34, No.

A Synchronous Distance Education Course for Non-Scientists Coordinated Among Three Universities, *Chem. Engr. Education*, Vol. 44, No. 1, pp. 30-34. ISSN: 0009-

Synchronous E-learning, In: *E-learning Experiences and Future*, Soomro, S. (ed.), pp.

Design Course, *Chem. Engr. Education*, Vol. 43, No. 3, pp. 194 – 200. ISSN: 0009-

Education using a Novel Web-based Tutorial and Assessment Tool for Advanced

*Proceeding of CHISA 2008* on CD-ROM, Prague, August 2008. ISBN 978-80-02-02047-

F., Nascimento, C. A. O. & Loureiro, L. V. (2010). Cooperative Weblab: A Tool for Cooperative Learning in Chemical Engineering in a Global Environment, *Chem.*

Auckland University and Technology, Tairawhiti Polytechnic. (2001). eXe-the

(and Sometimes Mobile) Environments, *Proceedings of WISE 2004 International*

e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. *Computers & Education* , Vol. 50, No. 4, pp. 1183-1202. ISSN: 0360-1315.

Students' feedback on the multimedia electronic-chapter of the text-book showed that such a kind of e-material contributes to a better understanding of the subject's content and can better prepare them for electronic and classical examinations. Students who choose the electronic manner for learning usually finish their course obligations within the course timeframe or within one or two weeks after finishing the lectures. For this reason, more time is left for other courses.

Good study results were obtained with on-going electronic-assessment of knowledge, especially at Bologna Courses within the first and second semesters of a study year, when a lot of students are enrolled. It is important that students are not forced into new ways of working because this can lead to stress, but rather allow them to always choose between the traditional way of learning with the text-books.

The pedagogic staff at the FCCE in Maribor already have seven years of experience in elearning. The results show that the incorporation of electronic-learning environments into education process improves lectures and the quality and efficiency of the study. E-learning leads to a heavier workload for the lecturer at the start, but this reduces over time.

Electronic-learning environments offer a lot of modules and activities that require the continuous enhancement of lecturers' knowledge. Pedagogic staff at the FCCE have the opportunity to enhance their skills through various workshops organised by the UM or the Faculty.

There are challenges for the future. The lecturers who already successfully use e-learning during their courses should encourage other colleagues to use new methods of learning. Sceptic lecturers should know about e-learning implemented lectures to make them more dynamic. The great challenge is to convince lecturers that pedagogic work is also research work like other scientific research. It is recommended that pedagogic staff focus their efforts and time on multimedia e-material production. The faster tempo of life namely shows that, it will be necessary to optimise study time, so the use of quality multimedia e-text-books will be inevitable in the future.

#### **5. References**

Students' feedback on the multimedia electronic-chapter of the text-book showed that such a kind of e-material contributes to a better understanding of the subject's content and can better prepare them for electronic and classical examinations. Students who choose the electronic manner for learning usually finish their course obligations within the course timeframe or within one or two weeks after finishing the lectures. For this reason, more time is

Good study results were obtained with on-going electronic-assessment of knowledge, especially at Bologna Courses within the first and second semesters of a study year, when a lot of students are enrolled. It is important that students are not forced into new ways of working because this can lead to stress, but rather allow them to always choose between the

The pedagogic staff at the FCCE in Maribor already have seven years of experience in elearning. The results show that the incorporation of electronic-learning environments into education process improves lectures and the quality and efficiency of the study. E-learning

Electronic-learning environments offer a lot of modules and activities that require the continuous enhancement of lecturers' knowledge. Pedagogic staff at the FCCE have the opportunity to enhance their skills through various workshops organised by the UM or the

There are challenges for the future. The lecturers who already successfully use e-learning during their courses should encourage other colleagues to use new methods of learning. Sceptic lecturers should know about e-learning implemented lectures to make them more dynamic. The great challenge is to convince lecturers that pedagogic work is also research work like other scientific research. It is recommended that pedagogic staff focus their efforts and time on multimedia e-material production. The faster tempo of life namely shows that, it will be necessary to optimise study time, so the use of quality multimedia e-text-books

Clark, R. E. & Feldon, D. F. (2005). Five Common but Questionable Principles of Multimedia

Dongil, S., Yoon, E. S., Park, S. J. & Lee, E. S. (2000). Web-based interactive virtual laboratory

*and Chemical Engineering*, Vol. 24, No. 2-7, pp. 1381-1385, ISSN: 0098-1354. Dougiamas, M. (1999). Moodle (Modular Object-Oriented Dynamic Learning Environment),

Excell, P. S. (2000). Experiments in the use of multiple-choice examinations for

In: *online*, July 2011, *https://estudij.uni-mb.si*

Learning, In: *The Cambridge Handbook of Multimedia Learning*, Mayer, R. E. (Ed.), pp. 97-116, Cambridge University Press, ISBN 0-521-83873-8, ISBN 0-521-54751-2, New

system for unit operations and process system engineering education, *Computers*

electromagnetics-related topics, *IEEE Trans. Education*, Vol. 43, No. 3, pp. 250-256,

leads to a heavier workload for the lecturer at the start, but this reduces over time.

left for other courses.

Faculty.

will be inevitable in the future.

**5. References**

York.

ISSN: 0018-9359.

traditional way of learning with the text-books.

**9**

*Taiwan (R.O.C.)*

**Interactive WhiteBoard:**

Kai-Ti Yang1 and Tzu-Hua Wang2,\* *1National Taiwan Normal University 2National HsinChu University of Education*

**Designs for Biology Teaching**

**Effective Interactive Teaching Strategy**

The goal of this chapter is to design interactive teaching strategies with Interactive WhiteBoard (IWB) and investigate their effectiveness on Biology teaching. In recent years, with the rapid development of Information Communication Technology (ICT), integrating multimedia presentation tools to perform better teaching has become easier in today's classroom. Among many ICT systems, the innovation and introduction of IWB has not only changed the traditional classroom but symbolizes a key revolution in the history of whiteboard development. Researchers have identified a number of advantages of using IWB in teaching and learning: flexibility and versatility, multimedia/multimodal presentation, improving teaching efficiency, supporting planning and the development of resources, improving students' skills of using ICT technology, interactivity and participation during course, improving students' learning motivation, and improving students' understanding (BECTA, 2007; Glover, Miller, Averis, & Door, 2005; Holmes, 2009; Northcote, Mildenhall, Marshall, & Swan,2010;Slay, Sieborger, & Hadgkinson-Williams, 2008; Smith, Higgins, Wall, & Miller, 2005; Wall, Higgins, Smith, 2005). The IWB realizes interactive operations between the whiteboard and the computer. It has become a new interface to consolidate all teaching resources in a traditional classroom. Many countries, such as the United Kingdom, Japan, Singapore, Malaysia, China, and Russia, have invested heavily in the IWB and attempted to implement it in schools of all levels. In Taiwan, the government also invests a large amount of money to introduce IWB into classrooms. Since 2006, the Taiwan's Ministry of Education officially announced that more than \$50 million NTD (roughly \$15 million USD) would be invested in promoting the preliminary integration of IWB into instruction. Following the trend of integrating IWB into teaching, this research tries to understand how to make good use of the advantages of IWB to make

students have better learning effectiveness on junior high school Biology.

Among the topics of junior high school Biology, cell division, photosynthesis, cell respiration, food chain, food web and evolution are the topics difficult to teach and learn. Both teachers

**1. Introduction**

\* Corresponding Author