**1. Introduction**

Sound conditions can have physiological and psychological effects on people in either a positive or negative way. Studies have demonstrated effects in educational spaces [1], working spaces [2], restaurants [3], canteens [4] and outdoor spaces [5]. Negative conditions can cause permanent hearing damage, increased stress [6], reduced efficiency at work [7], disturbance of sleep patterns [8] and interference in communications [9] as well as cardiovascular illnesses [10].

Therefore, it is increasingly compelling to embed sound condition considerations starting in the first stages of the design process. International standards indeed provide the requirements for running considerations at the design stage of new programs [11], and for existing functions, international standards give the terms, definitions, measurement conditions, procedures and evaluation methodologies [12–14]. Nonetheless, most of these conditions are invasive and concern the use of annoying sources that can affect normal user activities. For this reason, non-invasive sound-monitoring devices have been developed to provide real-time sound-data gathering.

These systems are framed in the consolidated trends of monitoring systems that help to maximise the energy savings, comfort and safety for the occupants [15]. The most commonly used sensing systems detect real-time information on the temperature and air quality and enable building environmental control systems, such as heating, ventilation, and air conditioning systems if the gathered data does not fulfill the fixed benchmarks.

**Citation:** Giglio, A.; Neuwerk, K.; Haupt, M.; Conti, G.M.; Paoletti, I. Textile-Based Sound Sensors (TSS): New Opportunities for Sound Monitoring in Smart Buildings. *Textiles* **2022**, *2*, 296–306. https:// doi.org/10.3390/textiles2020016

Academic Editor: Laurent Dufossé

Received: 29 March 2022 Accepted: 11 May 2022 Published: 19 May 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/).

Indoor environmental quality influences occupant productivity and health; therefore, its management is crucial, and sound has a prominent role. Sound-monitoring devices find applications in urban contexts [16] with low-cost [17] wireless sensor networks [18] embedding spatial statistical analysis [19], through considering indexes that embed subjective measures [20], in detecting noise levels while being powered by energy harvesting [21] and through the development of sensor nodes for accurate indoor sound-level measurements [22].

This article intends to compare the performances of sound sensors of the aforementioned cases with textile-based sound sensors (TSS). The combination of electronics and textiles is increasingly achieving important results in the trend for common computing. The rapid advancements of science and technologies keep revolutionizing traditional textiles and achieving new applications; smart textiles have more functions, including tactile sensing [23], displays [24], communicating [25], self-charging [26] and regulating body temperature [27] and humidity [28].

In the last decades, important advances have been achieved in sound sensors as well. They can measure correlation between the subjective assessment of perceived sound quality and the cardiac activity of the listeners [20], they can be embedded in gloves [29] and used for sound-direction detection, acoustic communications and heart-sound auscultation [30]. Their applications are mostly in wearable fabrics. Greinke used piezo electric films for sound measurement by sticking the film into fabric and sewing a conductive path with conductive yarn [31].

Nakad et al. designed and implemented a large-scale e-textile that functions as an acoustic beamforming array [32]. The prototype aims to find the location of a passing vehicle based upon the vehicle's acoustic emissions through a system that combines multiple lines-of-bearing to the vehicle's traffic. These lines-of-bearing are computed using an acoustic beamforming algorithm under the assumption that the vehicle is in the far field and lies in the same plane as the e-textile. They concluded that, at the physical scale, robust connectors are necessary for attaching electronic components, in order to insulate conductive elements in the fabric. At the system scale, the communication is energy-efficient and fault-tolerant and can serve a wide range of e-textile applications.

Comparisons between the performances of sound sensors have already been presented in the literature; however, a deep comparison of sound sensors for monitoring systems and TSS is still missing. This article intends to fill this gap.

#### **2. Research Methodology**

The article intends to compare the microphones embedded in sound-monitoring systems with TSSs. Only case studies published in scientific journals or accredited conference are reported.

An imperfect selection of materials, transducer modes and processing circuity can lead poor acoustic functionalities by decreasing the values of the signal-to-noise ratio (SNR) [33–35]. The SNR depends on the sensitivity and noise measured at a given acoustic pressure. The sensitivity is the converted sensing signal arising from the mechanical vibration with respect to the applied acoustic pressure. Therefore, the higher the value is, the better the performance. Furthermore, when the energy conversion takes place, an electrical noise—in form of a voltage/current—is also introduced followed by the thermalmechanical or Johnson noise [33,34,36]. As a consequence, the signal-to-noise ratio (SNR), sensitivity and noise floor (plotted in Table 1 with the related unit) are the parameters used for the comparison.

**Table 1.** The main parameters and relative units for acoustic sensor performance.

#### **3. Methods to Embed Sound Sensors in Textile** electronic components require an energy supply in order to be employed as a stand-

One of the most critical aspects for electronic textiles is the power supply. All electronic components require an energy supply in order to be employed as a stand-alone component. Avoiding conventional batteries important since it makes the garment similar to an ordinary one. Batteries are very bulky to add into the fabric, and they can limit the characteristics of the textile itself. Alternatives are given by flexible solar cells (Silicon Solar Inc, Bainbridge, New York, USA.) and micro fuel cells (Enfucell, Vantaa, Finland) since they can be used as a power supply for electronic devices. Other options are given by materials that are able to transform changing pressures (such as body motions or sound pressures in electric power [35]) using piezo electric materials [36]. The piezoelectricity is the generation of electrical polarization in a material under applied mechanical stresses. When a deformation occurs, it generates an electric charge. Vice versa, under applied charge, the material would deform in response [37]. alone component. Avoiding conventional batteries important since it makes the garment similar to an ordinary one. Batteries are very bulky to add into the fabric, and they can limit the characteristics of the textile itself. Alternatives are given by flexible solar cells (Silicon Solar Inc, Bainbridge, New York, USA.) and micro fuel cells (Enfucell, Vantaa, Finland) since they can be used as a power supply for electronic devices. Other options are given by materials that are able to transform changing pressures (such as body motions or sound pressures in electric power [35]) using piezo electric materials [36]. The piezoelectricity is the generation of electrical polarization in a material under applied mechanical stresses. When a deformation occurs, it generates an electric charge. Vice versa, under applied charge, the material would deform in response [37]. Piezoelectric material-based sensors offer two main advantages: (1) there is no specific requirement for the input power and (2) a broad dynamic range. For these

Piezoelectric material-based sensors offer two main advantages: (1) there is no specific requirement for the input power and (2) a broad dynamic range. For these reasons, most of the cases considered for the purpose of this article are piezoelectric-based acoustic sensors (from here on PAS) and micro-electrotechnical systems (from here on MEMS). reasons, most of the cases considered for the purpose of this article are piezoelectricbased acoustic sensors (from here on PAS) and micro-electrotechnical systems (from here on MEMS). Two methods are mainly used to embed sound sensors in textiles: 1. by attaching

Two methods are mainly used to embed sound sensors in textiles: 1. by attaching external sensors to the textile structures and 2. by embroidering piezo electric threads to create the fabric circuits. The two methodologies are described in the next paragraphs. external sensors to the textile structures and 2. by embroidering piezo electric threads to create the fabric circuits. The two methodologies are described in the next paragraphs. *3.1. Piezoelectric Acoustic Sensors (PAS) Films*

#### *3.1. Piezoelectric Acoustic Sensors (PAS) Films* According to the plane in which the sensing phase is placed, the energy conversions

According to the plane in which the sensing phase is placed, the energy conversions in piezoelectricity takes place in two transducing modes (Figure 1). In the case where it occurs in plane 31, we consider the D31 mode. If it occurs in direction 3, it is the D33 mode. in piezoelectricity takes place in two transducing modes (Figure 1). In the case where it occurs in plane 31, we consider the D31 mode. If it occurs in direction 3, it is the D33 mode.

[34],

**Figure 1.** Definition of the planes where the sensing phases can be placed. **Figure 1.** Definition of the planes where the sensing phases can be placed.

Upon an application of the acoustic pressure, the induced voltage (V) is defined as Upon an application of the acoustic pressure, the induced voltage (V) is defined as [34],

$$\mathbf{V} = \mathbf{E} \times \mathbf{s} \tag{1}$$

V = E × s (1) where E is the induced electric field and *s* is the electrode spacing. The electrode spacing (s) can be "t" or "d" (as shown in Figure 2), depending on the transducer mode. In D31 where E is the induced electric field and *s* is the electrode spacing. The electrode spacing (s) can be "t" or "d" (as shown in Figure 2), depending on the transducer mode. In D31

mode [39].

mode, the "3-1" refers to the induced polarization in direction 3 with respect to the per unit stress applied in direction 1 (Figure 2a) [35]. Thus, the thickness (t) limits the sensing signal. The improvement of the SNR in order to fit it with new technology demands has been achieved by incorporating different piezoelectric materials with different thicknesses, such as aluminium nitride (AlN) and D31 mode [36], sputtered zinc oxide (ZnO) and D31 mode [38] as well as lead zirconate titanate (PZT) and D31 mode [39]. time, it makes the sensor bulky and generates higher noise followed by mass and gravitational acceleration. For instance, Wang et al. reported a 60 dB SNR and a 34 dB noise floor by utilizing 0.7 μm thick PZT [39]; whereas, the reported sensitivity was only 0.49 mV/Pa, which is still a challenge for further signal processing. Therefore, an increase in film thickness is not a favourable solution to enhance the SNR.

The highest thickness values can increase the induced voltage; however, at the same

mode, the "3-1" refers to the induced polarization in direction 3 with respect to the per unit stress applied in direction 1 (Figure 2a) [35]. Thus, the thickness (t) limits the sensing signal. The improvement of the SNR in order to fit it with new technology demands has been achieved by incorporating different piezoelectric materials with different thicknesses, such as aluminium nitride (AlN) and D31 mode [36], sputtered zinc oxide (ZnO) and D31 mode [38] as well as lead zirconate titanate (PZT) and D31

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**Figure 2.** Piezoelectric acoustic sensor (PAS) with (**a**) D31 mode where t is the film thickness and (**b**) D33 mode where d is the electrode spacing [40]. **Figure 2.** Piezoelectric acoustic sensor (PAS) with (**a**) D31 mode where t is the film thickness and (**b**) D33 mode where d is the electrode spacing [40].

For this reason, the D33 mode, where the stress and strain take place in the "3-3" directions (Figure 2b), has been developed. In this mode, the design focuses on the electrode spacing because this mode is not related to the film thickness [40]. Shen et al. incorporated inter-digitated electrodes (D33 mode) to enhance the sensitivity of the piezo electric sensors (PAS) [40]. However, they did not obtain substantial improvement on sensitivity using 250 μm electrode spacing as the reported sensitivity was 0.126 The highest thickness values can increase the induced voltage; however, at the same time, it makes the sensor bulky and generates higher noise followed by mass and gravitational acceleration. For instance, Wang et al. reported a 60 dB SNR and a 34 dB noise floor by utilizing 0.7 µm thick PZT [39]; whereas, the reported sensitivity was only 0.49 mV/Pa, which is still a challenge for further signal processing. Therefore, an increase in film thickness is not a favourable solution to enhance the SNR.

mV/Pa which is far behind than what Wang et al. achieved using D31 mode [39]. The main drawback of the Shen et al.'s PAS is the material selection. The zirconate titanate (PZT) is good for energy scavenging due to its high piezoelectric constant when compared to other piezoelectric materials [41]. However, the incorporation of zirconate titanate (PZT) requires a special attention during the fabrication, i.e., for the poling process [42]. This is an additional drawback of zirconate titanate (PZT) because it shows the de-poling effect at higher electrode spacing starting from 16 μm which is 4 μm less than the nominal spacing of AlN, i.e., 20 μm [38,43,44]. For this reason, the D33 mode, where the stress and strain take place in the "3-3" directions (Figure 2b), has been developed. In this mode, the design focuses on the electrode spacing because this mode is not related to the film thickness [40]. Shen et al. incorporated inter-digitated electrodes (D33 mode) to enhance the sensitivity of the piezo electric sensors (PAS) [40]. However, they did not obtain substantial improvement on sensitivity using 250 µm electrode spacing as the reported sensitivity was 0.126 mV/Pa which is far behind than what Wang et al. achieved using D31 mode [39]. The main drawback of the Shen et al.'s PAS is the material selection.

As a result, the electric field as well as the sensing signal is lower at higher electrode spacing [43]. When compared to the PZT and D33, the combination AlN and D33 can be the better option for acoustic sensors. This combination does not show the de-poling effect since it depends on the lattice orientation [42]. Table 2 categorizes the previous studies by thickness, material, typology, sensitivity, SNR, noise floor and sensitivity peak. Others cases studies are plotted in Table 2 such as [44–47] for piezoelectric acoustic The zirconate titanate (PZT) is good for energy scavenging due to its high piezoelectric constant when compared to other piezoelectric materials [41]. However, the incorporation of zirconate titanate (PZT) requires a special attention during the fabrication, i.e., for the poling process [42]. This is an additional drawback of zirconate titanate (PZT) because it shows the de-poling effect at higher electrode spacing starting from 16 µm which is 4 µm less than the nominal spacing of AlN, i.e., 20 µm [38,43,44].

sensors in D31 mode. [48,49] refer to piezoelectric acoustic sensors in D33 mode and are plotted in Table 2 As a result, the electric field as well as the sensing signal is lower at higher electrode spacing [43]. When compared to the PZT and D33, the combination AlN and D33 can be the better option for acoustic sensors. This combination does not show the de-poling effect since it depends on the lattice orientation [42]. Table 2 categorizes the previous studies by thickness, material, typology, sensitivity, SNR, noise floor and sensitivity peak. Others cases studies are plotted in Table 2 such as [44–47] for piezoelectric acoustic sensors in D31 mode. [48,49] refer to piezoelectric acoustic sensors in D33 mode and are plotted in Table 2.

**Table 2.** References on D31 and D33 piezo acoustic sensors and the relative achieved values. NR: Not reported.

#### *3.2. Piezoelectric Acoustic Sensors (PAS) Yarns*

The studies on piezoelectric yarns aim at overcoming their inability to control changing properties over a wide range of frequencies [50]. This has led to the breach of new applications fields, such as energy harvesting [51] and conformal acoustics [52].

The development of fabrication methods that facilitate multi-functional and multimaterial yarns enable several attractive properties for new applications. The preform-based thermal drawing process offers a scalable means of producing kilometre-long fibre devices with sub millimetric cross-sectional dimensions [53]. These long and flexible fibres can easily be assembled into fabrics [54]. Furthermore, the integration of electrodes into the fibre enables the straightforward electrical connection of the device to an external electrical circuit [55].

The latest advancements in this field have led to the development of piezoelectric fibres (based on polyvinylidene fluoride (PVDF) and its copolymer, polyvinylidene fluoridetrifluoroethylene, (PVDF-TrFE)), which are capable of emitting and detecting sound waves over a broad range of frequencies [50]. While the small cross-sectional area of these fibres enables both miniaturization and flexibility, it seemingly involves an equally small active area that potentially limits the fibre performance [52]. The research of Yan et al. overcame the traditional use of acoustic fabrics by introducing a fabric that operates as a sensitive audible microphone while retaining the traditional qualities of fabrics, such as machine washability and draping [30].

Key to the fibre sensitivity is an elastomeric cladding that concentrates the mechanical stress in a piezocomposite layer with a high piezoelectric charge coefficient, of approximately 46 picocoulombs per newton, due to the thermal drawing process [56]. With the fibre subsuming less than 0.1% of the fabric by volume, a single fibre draw enables tens of square metres of fabric microphone. The measured sensitivity of the fibre-on-membrane is 19.6 mV (at 94 dB and 1 kHz, making it comparable to that of off-the-shelf condenser and dynamic microphones [30].

#### **4. Sound Sensors Typologies in Monitoring System**

The advancements in low-power computing, microphone technology and networking have allowed to move from very expensive static acoustic sensors to low-cost easy-to-use ones. Dedicated stations have been upgraded with real-time data transmission capabilities, but the most important advancements have been achieved in elaborating more flexible sensor node that can perform advanced digital signal processing.

Mydlarz et al. identified three general categories by relating sensor functionality and cost [16]. For the purposes of this article, we considered their sound performance related to the dimensions. When the transfer factor is not specified, the following formula is used to calculate it from sensitivity values in dB re. V/Pa (decibel relative to 1 volt per 1 pascal:

$$\text{transfer factor} = 10^{\left(\frac{\text{sensitivity}}{20}\right) \times 1000} \tag{2}$$

If only the transfer factor is presented, the sensitivity is calculated with the following equation:

$$\text{sensitivity} = 20 \times \log\_{10} \left( \frac{\text{transfer factor}}{1000} \right) \tag{3}$$

Table 3 categorizes the case studies according with the typology, application field (Indoor or outdoor), sensitivity, transfer factor, signal-to-noise ratio and thickness. It shows that for sound-monitoring system in free field several typologies of microphone have been tested: from Microelectromechanical system (MEMS) to condenser microphones. In these cases, the sensitivity range from −38to −42.04 dB re. 1 V/Pa with a thickness between 1700 to 17,600 µm. Since the monitoring of noise pollution is more topical in socio-political debate about the comfort of our cities, there are more explorations on open air applications.

**Table 3.** Comparison of sound sensors typologies, thickness, and relative acoustic performances in monitoring systems.

Devices which embed all the hardware has adopted with a sensitivity higher than the previous examples at −41 V/Pa at 1 kHz [13]. The high performance represents an opportunity for furthermore applications, but the high volume represents a limitation respect with the necessity to save the net area of use of interiors from services spaces, such as false ceiling and false walls.

#### **5. Comparison of Textile-Based Sound Sensors and Other Microphones**

The sound sensors in current monitoring systems range between 1700 and 86,000 µm. The sensitivity coefficients cover a broad range between 7.9 to 17.78 mV/Pa re. at 1 kHz. It can be observed that the typologies of microphone in this case are mainly for environmental measurements except for [13]. In this latter, the low thickness is combined with middle low sensitivity respect to the other (Figure 3). These studies are identified in Figure 3 in gradient of green.

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**Figure 3.** Relationship between the thickness and sensitivity of the literature. The sensors of current monitoring systems are in the gradient of green ([Dong et al. 2019] [15], [Mydlarz et al. 2017] [16], [Santini et al. 2008,] [18], [Segura Garcia et al. 2016] [19], [Tan et al. 2014] [20], [Risojević et al. 2018] [21]). The PAS yarn is red ([Yan et al. 2022] [30]). The PAS film in D33 mode is the gradient of violet ([Hillenbrad and Sessler 2004] [48], [Rahaman et al. 2019] [49], . The MEMs are in gradient of blue[57], [Arya et al. 2015] [58], [Kuntzman et al. 2013] [59], [Wiliams et al. 2010] [60]) and reference microphone is yellow ([bksv.com] [61]). Apart from the reference microphones, which have the higher value of sensitivity **Figure 3.** Relationship between the thickness and sensitivity of the literature. The sensors of current monitoring systems are in the gradient of green ([Dong et al. 2019] [15], [Mydlarz et al. 2017] [16], [Santini et al. 2008] [18], [Segura Garcia et al. 2016] [19], [Tan et al. 2014] [20], [Risojevi´c et al. 2018] [21]). The PAS yarn is red ([Yan et al. 2022] [30]). The PAS film in D33 mode is the gradient of violet ([Segovia-Fernandez et al. 2017] [47], [Hillenbrad and Sessler 2004] [48], [Rahaman et al. 2019] [49]. The MEMs are in gradient of blue [57], [Arya et al. 2015] [58], [Kuntzman et al. 2013] [59], [Wiliams et al. 2010] [60]) and reference microphone is yellow ([bksv.com] [61]).

(in yellow in Figure 3) [61], the studied microphones or sound sensors do not exceed the 19.6 mV/Pa in Yan et al. [30]. This value is achieved by a piezo electric acoustic sensors yarn [30] (identified with red color in the Figure 3). The PAS films remain in a low thickness range since the higher value does not exceed the 240 μm with a sensitivity of 4.49 mV/Pa [39]. They are represented in gradient of violet in the Figure 3. The MEMS cover a broad range of sensitivity from 0.61[57] to 11.22 mV/Pa [59] at 1 Apart from the reference microphones, which have the higher value of sensitivity (in yellow in Figure 3) [61], the studied microphones or sound sensors do not exceed the 19.6 mV/Pa in Yan et al. [30]. This value is achieved by a piezo electric acoustic sensors yarn [30] (identified with red color in the Figure 3). The PAS films remain in a low thickness range since the higher value does not exceed the 240 µm with a sensitivity of 4.49 mV/Pa [39]. They are represented in gradient of violet in the Figure 3.

kHz. Their thickness is proportional to their sensitivity. It has to be considered that the thickness measure does not take in consideration the dimensions of all the other hardware that monitoring systems require. Amplifier, pre-amplifier, add more volume and consequently weight and mass and are an issue in mounting phase when service spaces, such as false ceiling or false wall, are tight. The TSS balanced the acoustic performance with the possibility to be adapted in aforementioned spaces. **6. Conclusions** The MEMS cover a broad range of sensitivity from 0.61 [57] to 11.22 mV/Pa [59] at 1 kHz. Their thickness is proportional to their sensitivity. It has to be considered that the thickness measure does not take in consideration the dimensions of all the other hardware that monitoring systems require. Amplifier, pre-amplifier, add more volume and consequently weight and mass and are an issue in mounting phase when service spaces, such as false ceiling or false wall, are tight. The TSS balanced the acoustic performance with the possibility to be adapted in aforementioned spaces.

#### **6. Conclusions**

The article aims to compare the sound performance of sound sensors applied in sound-monitoring systems with textile-based sound sensors. The necessity to provide a continuously informed systems to monitor the sound conditions in a space has led to assessing several typologies of microphones aiming to reduce the dimensions and increase the performance. These are requirements that can be fulfilled by the TSSs in both the film and yarn configurations. Table 4 presents how the sensitivity of textile-based sensors is comparable with MEMS, and in some cases, they even have higher performance. This is more so apparent, when considering the volume of all the hardware that MEMs require to complete a monitoring system. Figure 4 demonstrates that they would increase it considerably. that they would increase it considerably. **Table 4.** Comparison of parameters between Pas D31, Pas D33, Acoustics MEMs and microphones.

The article aims to compare the sound performance of sound sensors applied in sound-monitoring systems with textile-based sound sensors. The necessity to provide a continuously informed systems to monitor the sound conditions in a space has led to assessing several typologies of microphones aiming to reduce the dimensions and increase the performance. These are requirements that can be fulfilled by the TSSs in both the film and yarn configurations. Table 4 presents how the sensitivity of textilebased sensors is comparable with MEMS, and in some cases, they even have higher performance. This is more so apparent, when considering the volume of all the hardware that MEMs require to complete a monitoring system. Figure 4 demonstrates

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**Table 4.** Comparison of parameters between Pas D31, Pas D33, Acoustics MEMs and microphones. **References Source Sensitivity mV/Pa at 1 kHz SNR dBA at 1 kHz Noise Floor Thickness μm**

**Figure 4.** The relations between the volume of the MEMS microphones themselves and with the hardware of the monitoring system. ([Dong et al. 2019] [15], [Mydlarz et al. 2017] [16], [Santini et al. 2008], [18], [Segura Garcia et al. 2016] [19], [Tan et al. 2014] [21], [Risojevi´c et al. 2018] [22]).

The low thickness of TSSs can facilitate use in tight service spaces, such as false ceilings and false walls, in order to reduce the aesthetic impact on the space design. Therefore, one of main requests for these systems is either the reduction of their shapes or a high degree of adaptability. Moreover, due to the aesthetic characteristics of the textile itself, in future works it could be interesting to demonstrate how they can be used to combine aesthetic features with sound-monitoring ones.

This feature can enable sound smartness in fabrics with active absorption behaviours to improve sound conditions in real time, thereby, opening new scenarios for the development of acoustic textiles.

**Author Contributions:** Conceptualization, investigation, writing—original draft preparation, A.G.; writing—review and editing, K.N.; supervision, M.H., G.M.C., I.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Data Availability Statement:** The data presented in this study are available in the article.

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

### **References**


**2.1 Binding of pancreatic α-amylase to small intestinal BBM**

Tissue sections of pig duodenum were immunostained with an anti-pancreatic α-amylase antibody. Entire duodenal tissue sections were stained with the pancreatic α-amylase antibody when there was a large amount of food in the stomach (during non-fasting), but hardly stained when there was little in the stomach (during fasting) [14]. The localization of exogenous pancreatic α-amylase was examined by staining a 1-cm section of the duodenum of a fasted pig with the pancreatic α-amylase antibody. Tissue sections fixed in formalin and embedded in paraffin were immunostained to detect pancreatic α-amylase. The duodenal sections were agitated in pancreatic α-amylase solution at 4°C. As a result, pancreatic α-amylase bound to the BBM, which is the upper end of the duodenal epithelium (**Figure 1**), and α-amylase staining increased in a time-dependent manner with agitation. Mannan inhibited the binding of pancreatic α-amylase to BBM duodenum sections incubated in α-amylase solution for 30 min. On the other hand, galactan and colominic acid inhibited binding of α-amylase to BBM after 10 min of agitation, but did not inhibit binding of α-amylase to BBM agitated for 30 min (data not shown) [14]. Pancreatic α-amylase bound to duodenum BBM, and its binding was inhibited by

**Figure 1.** *Binding of pancreatic α-amylase to pig duodenum BBM.*

*New Insights into Metabolic Syndrome*

has not been completely elucidated yet.

of *N*-glycans of glycoproteins depending on pH.

the amylase to degrade polysaccharides. The α-amylase in pancreatic juice and saliva clearly functions as a digestive enzyme. It is an endo-type enzyme that randomly cleaves α-1,4 glycosidic bonds such as starch and glycogen to produce maltose and oligosaccharides [1]. Therefore, α-amylase in digestive juices is an essential enzyme for animals consuming a starch diet. α-Amylase has been found in liver [2], brain [3], blood, urine, and cancer cells [4] in humans, but its physiological significance

It has been reported that porcine pancreatic α-amylase binds to an *N*-linked glycan of glycoproteins [5]. It has been shown that the binding of porcine pancreatic α-amylase to *N*-linked glycans is different from that of the polysaccharide as a substrate. It shows that the carbohydrate-binding activities of pancreatic α-amylase are not common to all types of α-amylase. α-Amylases from barley, *Bacillus subtilis*, and mammalian saliva do not have this activity. Porcine pancreatic α-amylase binds mainly to transferrin having complex-type biantennary *N*-glycans, fetuin having complex-type triantennary *N*-glycans, and ribonuclease B having high-mannose *N*-glycans. However, it does not bind to bovine submandibular gland mucin having *O*-glycans or bovine serum albumin having no sugar chains. The carbohydratebinding activities of porcine pancreatic α-amylase are affected by pH. Porcine pancreatic α-amylase has a high affinity for both complex type and high-mannose *N*-glycans under pH 5.5. On the other hand, the binding activity is seen with only the high-mannose *N*-glycans, and the binding to the complex *N*-glycans is reduced under neutral pH. Thus, pancreatic α-amylase selectively recognizes the structure

The biological significance of the *N*-glycan binding found in pancreatic α-amylase in vivo is unknown. Pancreatic α-amylase is synthesized in pancreatic acinar cells, packed into acidic zymogen granules (pH 5.5), and secreted into alkaline pancreatic juice (pH 8.0) [6]. Pancreatic juice flows into the duodenum and mixes with gastric acid where it is neutralized, and pancreatic α-amylase exerts its enzymatic activity. The pH in the middle of the duodenum falls from pH 6.5 to 4.5 in a 3-hour period after a meal [7]. There are glycoproteins with *N*-glycans in pancreatic zymogen granules, its membrane, and the lumen of the small intestine [8–11]. These suggest that the *N*-glycan-binding activity of pancreatic α-amylase may be play a role in the packing of pancreatic zymogen granules, its exocytosis in the pancreas, and digestion and absorption of carbohydrates in the small intestine. In this study, we elucidated the roles of the *N*-glycan-binding activity of pancreatic α-amylase in the small intestine by identifying the glycoproteins to which the α-amylase binds on the small intestinal brush border membrane (BBM), the luminal surface of the small intestine where many glycoproteins are located. The functions and localizations of the identified α-amylase-binding-glycoproteins and analyses of interactions between α-amylase and the glycoproteins revealed that pancreatic α-amylase has the following regulatory functions other than as a digestive enzyme: (1) enhancement of α-glucosidase, sucrase-isomaltase, (2) regulation of sodium-dependent glucose uptake, and (3) localization of pancreatic α-amylase in the small intestine. Furthermore, the new discoveries show that duodenal epithelial cells express α-amylase, which is essential for proliferation and differentiation of

**2. Identification of glycoproteins that bind pancreatic α-amylase in the**

In the small intestine, epithelial cells in the luminal villi have a brush border on the surface, and alkaline phosphatase and other membrane-type digestive enzymes

**200**

small intestinal epithelial cells.

**small intestinal BBM**

mannan, indicating that α-amylase binds to duodenal BBM in a mannose-specific manner, even at the tissue level.

One-centimeter duodenum sections from fasted pigs were incubated with pancreatic α-amylase (10 μM) in PBS (pH 7.2) including phenylmethylsulfonyl fluoride (final concentratation 1 mM) at 4°C for 30 min, then fixed and paraffinembedded. The paraffin sections were immunostained with rabbit anti-α-amylase IgGs-HRP. The color was developed with DAB/H2O2 and then counterstained with hematoxylin.


**Abstract**

The purpose of this chapter is to review some important, recent theoretical discoveries regarding the effect of temperature on the property of plasmons. These include their dispersion relations and Landau damping rates, and the explicit dependence of plasmon frequency on chemical potential at finite temperatures for a diverse group of recently discovered Dirac-cone materials. These novel materials cover gapped graphene, buckled howycomb lattices (such as silicene and germanene), molybdenum disulfide and other transition-metal dichalcogenides, especially the newest dice and *α*-T 3 materials. The most crucial part of this review is a set of implicit analytical expressions about the exact chemical potential for each of considered materials, which greatly affects the plasmon dispersions and a lot of many-body quantum-statistical properties. We have also obtained the nonlocal plasmon modes of graphene which are further Coulomb-coupled to the surface of a thick conducting substrate, while the whole system is kept at a finite temperature. An especially rich physics feature is found for *α*-T 3 materials, where each of the above-mentioned properties depends on both the hopping parameter *α* and temperature as well.

**Keywords:** finite temperature effects, plasmon dispersion, 2D materials


**12. State-of-the-art of immunology in canine melanoma**

Canine melanoma is an immunogenic tumor, and investigations of different aspects associated with immune cells in tumor development and progression have been reported in the literature [39–41]. Moreover, some studies have evaluated different cancer immunology aspects of canine melanoma, podoplanin [42], and chondroitin sulfate proteoglycan-4 (CSPG4) [40]. Podoplanin is a type I transmembrane protein that is expressed in different cells of the immune system, including lymphatic endothelial cells. Podoplanin overexpression has been investigated in several cancers, including canine melanomas. Since the development and application of a monoclonal antibody against podoplanin, these markers have been recognized as important for canine melanoma immunotherapy [43]. CSPG4 has become very important for canine melanoma owing to the number of vaccines produced against this protein [39, 44, 45].

Its expression has been reported in canine melanoma, and different clinical trials based on vaccines or electrogene therapy have been conducted [39, 44, 45]. A review of the PubMed database for the past ten years is provided in **Table 2** summarizing clinical trials involving dogs with melanoma treated with immunotherapies.

In addition to evaluating immunotargets for canine melanoma, several studies have investigated the association between immune markers and melanoma prognosis,

#### **Table 2.**

*Summary of the articles published in the past ten years with clinical studies evaluating different immunotherapies for canine melanoma.*

including intratumoral infiltration of immune cells. The prognostic significance of CD3+ and CD20+ cell infiltration of canine oral melanoma has been investigated; and high infiltration of CD20+ cells is associated with metastasis, frequency of recurrence, shorter survival time, and high rate of tumor-related deaths, and disease-free interval [51]. Therefore, a high infiltration of CD20+ cells is associated with several negative prognostic factors. Yasumaru et al. [52, 53] evaluated the presence of CD8+ and CD4+ infiltrating T cells in oral melanoma using flow cytometry and concluded that tumor-infiltrating lymphocytes predict the aggressiveness and prognosis of patients with oral melanoma.


**Acknowledgements**

in overall LVAD infection control within hospitals are also helpful in preventing infections [86–88]. Pocket infections must typically be managed with surgical debridement in the operating room with techniques such as omental wrapping of the pump housing to cover exposed metal and to close surgical defects [89, 90]. In rare instances, extrapolating from the orthopedic surgery literature, antibiotic impregnated beads have been placed in the pocket (reviewed in [91, 92]) although this has not been studied in a rigorous manner. Arguably, tissue levels of parenteral antibiotics are sufficient to treat residual infection once source control has been achieved. Placement of an additional foreign body in the pocket may not be advised, especially since the antibiotic concentrations from the beads will eventually wane, requiring subsequent bead exchange or removal. Repeated exposure to sub-inhibitory concentrations of antibiotic can lead to selection of antibiotic resistant organisms. Indolent pathogens such as *M. chimaera* or in the case of fungal infections may necessitate exchange of the pump and other components that are involved. LVAD endocarditis requires explanation and extended antimicrobial therapy, potentially with lifelong suppression if re-implanted or if cardiac transplantation occurs [42, 48, 50]. Optimal peri-implant antibiotic prophylaxis has not been established in a rigorous trial. However, "best evidence" was provided in a review by Acharya et al. [93] and consists of antibiotic coverage for Staphylococci, Enterococci, *Pseudomonas* and *Candida* spp. They concluded that use of an extended spectrum beta-lactam plus vancomycin in areas where rates of methicillin resistant *S. aureus* are high, a fluoroquinolone, fluconazole and mupirocin ointment (nasal application) in the "peri/post-operative" period (~3 days) was recommended. Prophylactic antibiotics are not recommended to prevent driveline infection after the immediate post-operative period [94].

The development of biventricular or LVAD devices with transcutaneous energy sources ("TETs") will eliminate driveline infections [95]. However, this remains the "holy grail" for developers of mechanical circulatory support devices [96, 97]. Magnetically levitated pumps help reduce the rates of reoperation (and attendant complications like infection) [7]. Changes in size and materials involved in these devices can also reduce risk of thrombosis and enable easier explanation and reimplantation should complications arise [98]. Minimally invasive procedures such as offpump implantation and alternative implant sites may also lead to reduced infection risk [99].

Left ventricular assist device (LVAD) infections are important causes of morbidity and mortality in patients who receive these mechanical circulatory supports as a bridge to transplantation (BTT) or as destination therapy (DT) (for individuals who are not candidates for cardiac transplant). Infections are more common among persons who received pulsatile flow LVADs as opposed to newer continuous flow (CF) devices. Other risk factors for infection include obesity, renal failure, depression and immunosuppression although HIV positive LVAD recipients have not had increased rates of infection in the limited number of recipients to

**7. Future directions**

180 Advanced Concepts in Endocarditis

**8. Conclusions**

The author would like to acknowledge the editor, Dr. Michael Firstenberg and Dr. Robert Bonomo for critical reading and suggestions to improve this manuscript.


**7. Amyloid plaques**

Even though amyloid plaques can be categorized into different groups depending on their structure, all types of -amyloid protein (A) are present in them. When APP is degraded proteolytically by - and -secretase, an amino acid peptide known as A is produced. The primary results of this cleavage are A1–40 and A1–42. The development of amyloid oligomers and fibrils, which come together to form amyloid plaques, is predisposed by a relative excess of A1–42. Since the generation, processing, and/or trafficking of amyloid is connected to the proteins encoded by APP, PS1, PS2, SorL1, and ApoE, this suggests that amyloid plays a significant role in the etiology of AD [37].


*Edited by Ki Young Kim*

The title of this book, Plasmonics: Principles and Applications, encompasses theory, technical issues, and practical applications which are of interest for diverse classes of the plasmonics. The book is a collection of the contemporary researches and developments in the area of plasmonics technology. It consists of 21 chapters that focus on interesting topics of modeling and computational methods, plasmonic structures for light transmission, focusing, and guiding, emerging concepts, and applications.

ISBN 978-953-51-0797-2

Plasmonics - Principles and Applications

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