**5. Results**

Figure 3 compares the results of RefProp 9.1 with those of approximations A1 and A3 for the liquid–vapor saturation boundary in a *Tr* − *s*∗ diagram for: (a) ammonia; (b) benzene; (c) methyl palmitate;and (d) D6. In the case of ammonia, approximation A3 gave better agreement with RefProp 9.1 than A1 for the saturated vapor branch, whereas we obtained the opposite behavior for the saturated liquid branch. This can be ascribed to the fact that the slope of the modified rectilinear diameter is slightly larger for A3 (−*b*A3 = 5.0275, obtained from Equation (25) with *c*ig∗ *p* (*T*M*r*) = 4.3795) than for A1 (−*b*A1 = 4.4225). Figure 3b shows that A1 and A3 yield similar results for the saturation entropies of benzene, with excellent agreement with RefProp 9.1 results except for *s*∗g for *Tr* < 0.6. In this case, the slope −*b*A1 = 18.5302 is very similar to −*b*A3 = 18.4997 (obtained from *c*ig∗ *p* (*T*M*r*) = 15.4544). In Figure 3c, the approximation A3 gives a better agreement with RefProp 9.1 than A1. This indicates that the slope −*b*A3 = 107.9614 (obtained from *c*ig∗ *p* (*T*M*r*) = 84.2017) yields better results than that of approximation A1 (−*b*A1 = 110.949). Finally, Figure 3d shows that A3 yields much better agreement with RefProp 9.1 than A1. We note that D6 gives rise to the maximum deviation between A1 and RefProp 9.1, as we shown below. This is clearly due to the fact that the slope −*b*A1 = 128.0031 for D6 is much larger than −*b*A3 = 120.7889.

**Figure 3.** Liquid–vapor saturation boundary in a *T*r-*s*∗ diagram for: (**a**) ammonia; (**b**) benzene; (**c**) methyl palmitate; and (**d**) D6. The solid lines correspond to the results of approximation A3 for the entropies of the saturated vapor *s*∗g,A3 (solid red line) and the saturated liquid *s*∗l,A3 (solid blue line). The dashed lines correspond to the results of approximation A1 for the entropies of the saturated vapor *s*∗g,A1 (dashed red line) and the saturated liquid *s*∗l,A1 (dashed blue line). The symbols are RefProp 9.1 results for *s*∗g (circles) and *s*∗l(triangles).

The only difference between approximations A1 and A3 comes from the value of the parameter *b* that is calculated from Equation (11) in the case A1 and from Equation (25) for A3. In Figure 4, we present a plot of *b*A3 vs. *b*A1 for the 121 fluids of RefProp 9.1 [17], which are also listed in Table A1. In all cases, we obtained negative values of *b* in the range −130 < *b* < −1 (notice that the modified rectilinear diameter relation is given by *b*(1 − *Tr*) and thus the slope of the straight line, −*b*, is always positive). Overall, the agreement between both approaches is very good except for very dry fluids (with large values of −*b*) where approximation A3 yields results for −*b* slightly smaller than those of approximation A1, as one can see in Figure 4a. Wet fluids are those for which *ξ*∗M < 0 and thus they present smaller values of −*b*. As shown in Figure 4b, the agreement between the results of A1 and A3 for wet fluids is still good but presents more spread. The transition from dry to wet fluids occurs for *b* ≈ −14 but it is not sharp, mainly due to the effect of the acentric factor in Equation (11).

**Figure 4.** The parameter *b*A3 vs. *b*A1. The symbols represent the values of *b*A3 and *b*A1 obtained from Equations (25) and (11), respectively, using RefProp 9.1 data [17]. The solid blue line corresponds to the identity *b*A3 = *b*A1.  The data for *b*A3 and *b*A1 are listed in Table A1.

To provide a quantitative measurement of the performance of approximations A1 and A3, we consider the following expression for the percent relative deviation Δ*r*i of approximation Ai (i = 1, 3), which was introduced in [16]:

$$\Delta\_{\rm ri} = 100 \frac{\int\_{0.6}^{1} |s\_{\rm g}^\*(T\_r) - s\_{\rm g, \rm Ai}^\*(T\_r)| \mathrm{d}T\_r + \int\_{0.6}^{1} |s\_1^\*(T\_r) - s\_{\rm l, \rm Ai}^\*(T\_r)| \mathrm{d}T\_r}{\int\_{0.6}^{1} |s\_{\rm g}^\*(T\_r) - s\_{\rm l}^\*(T\_r)| \mathrm{d}T\_r} \, \mathrm{} \tag{29}$$

where *s*∗g and *s*∗l are RefProp 9.1 results. We obtained Δ*r*1 = 4.82% and Δ*r*3 = 3.42% for ammonia, Δ*r*1 = 2.11% and Δ*r*3 = 2.28% for benzene, and Δ*r*1 = 24.68% and Δ*r*3 = 14.12% for methyl palmitate.

Figure 5 compares the percent relative deviations of A1 and A3 for the 121 fluids of RefProp 9.1. To relate the performance of A1 and A3 to the dry or wet character of the fluid, the percent relative deviations are plotted as a function of the parameter *ξ*∗M. We note that, for the sake of clarity, the results are plotted with lines instead of symbols. As one can observe in Figure 5 (see also Table A1) the new approximation A3 fares better than A1 for fluids with *ξ*∗M>28, i.e., for very dry fluids. For the remaining fluids, both approximations yield similar results, in most cases with relative deviations less than 5% (below the dotted line in Figure 5). More concretely, in the case of the new approximation A3, we obtained an average percent relative deviation Δ*r*3 = 4.19% for all fluids of Table A1, with a maximum percent relative deviation max(Δ*r*3) = 15.56% for methyl stearate (the only fluid with Δ*r*3 > 15%). In the case of A1, one has [16] Δ*r*1 = 5.00% and max(Δ*r*1) = 34.10% for D6, with nine fluids of a total of 121 with Δ*r*1 > 15%. The reason for obtaining Δ*r*1 > Δ*r*3 can be clearly ascribed to the poorer behavior of A1 for very dry fluids. We note, however, that, in the two approximate treatments, 96 fluids have relative deviations less than 5%. Among the wet fluids (*ξ*∗M < 0), the largest relative deviations were obtained for helium (Δ*r*1 = 13.86% and Δ*r*3 = 14.38%) and R40 (Δ*r*1 = 12.65% and Δ*r*3 = 12.83%). Finally, we would like to note that, even with large deviations, e.g. Δ*r*1 = 34.10% for D6, one can obtain fairly good results, as shown in Figure 3d.

**Figure 5.** The percent relative deviations Δ*r*1 and Δ*r*3 vs. *ξ*∗M. For clarity, the deviations are plotted with lines: the dashed red line corresponds to Δ*r*1 and the solid blue line represents Δ*r*3. The dotted line indicates a deviation level of 5%. The data for Δ*r*1, Δ*r*3, and *ξ*∗M are listed in Table A1.

## **6. Summary**

In a previous work [16], a semiempirical method was developed for obtaining the liquid–vapor boundary of a fluid in a *Tr* − *s*∗ diagram. The method assumes that, for a certain value of the quality *q* ¯ = 0.385, the line of constant *q*¯ in the *Tr* − *s*∗ diagram (*s*∗*q*¯(*Tr*)) is very close to the straight line *s*∗*q*¯(*Tr*) ≈ *b*(1 − *Tr*), i.e., one has a modified rectilinear diameter relation for the saturation entropies. From this assumption, the semiempirical method only requires two ingredients: an appropriate expression for the enthalpy of vaporization and an approximate estimation of the parameter *b*. In what refers to the enthalpy of vaporization, perhaps the simplest choice is the extended corresponding states version [20] of the Watson equation [21] considered in [16] and in the present work. Two approximations, A1 and A2, where developed for *b* in [16]. The more accurate is approximation A1 with *b*A1 given by Equation (11) and therefore depending on the acentric factor *ω*, the parameter *ξ*∗M, and the reduced temperature *T*M*r*. The main drawback of A1 is that, while *ω* is available for most fluids, the other two parameters must be calculated for each fluid. Approximation A2 is less accurate but it has the advantage that, in addition to *ω*, it only requires the critical molar volume *νc* that can be accessed in most databases.

In the present work, we developed a new approximation A3 where the parameter *b*A3 is given by Equation (25) and only depends on *ω* and on the ideal-gas isobaric molar heat capacity of the fluid *c*ig∗ *p* at a reduced temperature *T*M*r* = 0.81. We want to recall that excellent approximations for *c*ig∗ *p* are available for a large variety of fluids in most Thermophysical Properties databases. The new approximation has the virtues of approximations A1 and A2 without their problems: it has an accuracy similar to or even better than that of A1 and only needs the value of easily accessible parameters.

To conclude we would like to comment that the present work has also served to clarify the role played by the ideal-gas isobaric molar heat capacity in the shape of the liquid–vapor saturation boundary in a temperature–entropy diagram, in agreement with the results of other authors [11–15].

**Author Contributions:** Conceptualization, J.A.W. and S.V.; Formal analysis, J.A.W. and S.V.; and Writing— Original draft, J.A.W. and S.V.

**Funding:** This research was funded by Junta de Castilla y León of Spain grant number SA017P17.

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


**1. Introduction**

Respiratory diseases are common and frequently occurring diseases whose incidence has increased in recent years. Inhalation of dust and irritating gases are the main causes of respiratory diseases, which cause tremendous harm to human health [1]. *Alstonia scholaris* leaves, a traditional Chinese medicine from the Dai nationality, are mainly used to treat chronic respiratory diseases [2]. *A. scholaris* leaves are also used as a traditional medicine to treat respiratory diseases in India, Malaysia, the Philippines, and Thailand [2]. *A. scholaris* leaf extracts, especially alkaloids, are widely used to treat bronchitis and have significant e fficacy [3–7]. Luo et al. studied *A. scholaris* leaves and found an alkaloid component that beneficial e ffects respiratory diseases. This component has a positive e ffect on bronchitis and post-cold infections [8,9]; however, its half-life is short, which limits its clinical application.

Research and development of sustained-release formulations have always been a focus in drug research and have gradually begun to solve the problem of short half-lives. In recent years, polymer nanoparticles have shown to be e fficient drug carriers for encapsulating drugs [10]. At present, designing and selecting drug nanocomposites has mainly focused on amphiphilic block copolymers. Polyethylene glycol (PEG) is often used in the hydrophilic segment of the copolymers, while many homopolymers, copolymers and derivatives of degradable polymers, such as polylactic acid (PLA), polyglycolic acid (PGA) and polycaprolactone (PCL), are used in the hydrophobic segment [11–14]. Methoxy poly(ethylene glycol)-poly(lactide) copolymer (mPEG-PLA) is an amphiphilic polymer formed by grafting mPEG onto PLA. mPEG-PLA has excellent biocompatibility, a low molecular weight, and many hydroxyl groups and is nontoxic and widely used as a coating material in drug-delivery systems [15,16]. PEG blocks can improve the polymer's hydrophilicity and flexibility, prevent protein adsorption and avoid recognition and phagocytosis by the reticuloendothelial system (RES). PEG encapsulates the drug to form the "core", while the "shell" is formed by the outside hydrophobic segment, which constitutes the typical "core-shell" structure, with great advantages for drug release [17–19]. Therefore, in this work, total alkaloids from *A. scholaris* leaves (ASAs) were studied, and mPEG-PLA with di fferent molecular weights was used as the carrier material. A series of drug-loaded microspheres were prepared by the water-oil-water (W/O/W) double-emulsion technique. Based on the morphology, particle size, encapsulation e fficiency (EE), drug-loading e fficiency (LE), and in vitro drug release of the prepared microspheres, the best drug-loaded materials were screened out, and then the biological properties of its drug-loaded microspheres such as cytotoxicity, blood compatibility and anti-inflammatory activity were studied.

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


2.3.2. Start and Operation Procedure, Crystallization Progress, and Analytics Used

The starting point of all experiments was the preparation of the feed suspension. Therefore, the solvent was filled into the feed tank and circulated via the gear pumps through the columns and via the peristaltic pumps through the comminution bypasses. The required racemic solute mass for saturating the aqueous solution at the desired temperature of each experiment (Table 1, Tsat) plus 200 g racemic excess solid was afterward filled in the feed tank, and the suspension heated to Tsat, which was kept constant throughout the whole experiments. To avoid any risk of nucleation within the columns during the preparation step, the coolant temperature of the double jackets was set to one Kelvin above Tsat. After the mother liquor within the feed tank reached Tsat, the coolant temperature of the double jackets was set to one Kelvin below Tsat. In parallel, the heating hoses were set to 40 ◦C to prevent any nucleation or clocking within the tubes: all other steel pipes (Figure 3) were appropriately heat traced to prevent clocking. The liquid flow was stopped for seeding each column from the top (Figure 3, port) with a certain mass (Table 1, mSeed) of one of the pure, crystalline enantiomer once the respective temperatures were reached. In all experiments, crystallizer C1 was seeded with D-Asn·H2O and crystallizer C2 with L-Asn·H2O. Immediately after seed addition, the pumps were started again to fluidize the present crystals and to prevent nucleation in the stagnant fluid phase. After this initial seeding, both crystallizers were subsequently cooled to the planned operation temperature (Table 1, Tcrys). The fluidized seed crystals in both columns started to grow according to the present

supersaturation. Hence, they settled constantly due to their increasing mass towards the crystallizers' bottoms. All crystals, which reach the fluid phase inlet, were withdrawn into the inline seeding bypass, where they were ground. The generated crystal fragments were fed back to the process merged with the liquid inlet stream.

If the process conditions are chosen appropriately, the crystal fragments will grow (Figure 4a) large enough to settle within the cylindrical part and thus stay in the process. Then the overall crystal mass increases and the process progresses. The growing seeds start to settle, subsequently, on the top of the initial solid mass and the crystal bed increases in height.

**Figure 4.** (**a**) Schematic detail drawing of the progressing process at the height of the product outlet. The seed crystals move through the fluidized crystal bed until they are grown to a size at which they settle at the top of the bed. (**b**) Microscope photograph of washed product crystals.

The product withdrawal was initiated when the crystal bed first blocks the upper photoelectric barrier (L1, Figure 4a). The solenoid valve (V1, Figure 4a) was opened at this point and the crystal product is harvested until the lower photoelectric barrier (L2, Figure 4a) was not blocked by the fluidized crystal phase anymore. Afterward, the valves were closed and the crystallization progressed until the crystal bed height was large enough for the next product withdrawal. This periodic procedure continued and the process progressed towards its dynamic steady-state. Immediately after the product withdrawal, the product crystals were filtered and washed with an ethanol-water mixture (40 wt% EtOH, 60 wt% H2O). The dried product crystals (Figure 4b) were afterwards analyzed via high performance liquid chromatography (HPLC), X-ray powder diffraction (XRPD), and sieve analysis to evaluate each operation point with respect to process performance parameters (purity, yield, productivity, and size distribution, Equations (3)–(7)). The specifications of the applied analytics are given in Table 2.

The recycled, concentration-depleted mother liquor causes partial dissolution of the solid racemic excess within the feed tank. To minimize additional distortions of the feed concentration, and thus of the process, a piecewise addition of new solid excess material is required. Since the average product crystal mass of one withdrawal is approximately 20 g per column, subsequently, 50 g of racemic solid excess material was added to the feed tank after every product withdrawal.


**Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans**

Editors

**Javier Cuadrado Miguel A. Naya**

MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin

*Editors* Javier Cuadrado University of La Coruna˜ Spain

Miguel A. Naya University of La Coruna˜ Spain

*Editorial Office* MDPI St. Alban-Anlage 66 4052 Basel, Switzerland

This is a reprint of articles from the Special Issue published online in the open access journal *Sensors* (ISSN 1424-8220) (available at: https://www.mdpi.com/journal/sensors/special issues/multibody sensors).

For citation purposes, cite each article independently as indicated on the article page online and as indicated below:

LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. *Journal Name* **Year**, *Volume Number*, Page Range.

**ISBN 978-3-0365-2357-6 (Hbk) ISBN 978-3-0365-2358-3 (PDF)**

© 2021 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications.

The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND.


**Novel Therapeutic Approaches for Skeletal Muscle Dystrophies**

Emanuele Berardi and Maurilio Sampaolesi

Additional information is available at the end of the chapter

#### **Abstract**

Muscular dystrophies (MDs) are inherited diseases that affect skeletal and cardiac muscle tissues. Cases range from mild to very severe, resulting in respiratory or cardiac failures. No cures are available for MDs and corticosteroid treatments, mainly deflazacort and prednisolone, only help to control the inflammatory process and slightly delay the progression of the disease. This is due to the beneficial effect on pulmonary function and scoliosis. Walkers and wheelchairs are used to strengthen patients' independence and walking ability. When respiratory and/or cardiac muscles become weak, mechanical ventilation is mandatory. In addition, hypertension, cataracts, excessive weight gain and vertebral fracture are often serious side effects of deflazacort and prednisolone treatments.

This chapter deals with the advanced therapies used to treat muscle degenerations, ranging from pharmacological to gene and/or cell treatments. We review previous trials that use cell delivery protocols in mice and patients. Here, donor satellite cells and myogenic progenitors are isolated from the bone marrow. We then proceed to describe the recently identified stem/progenitor cells in relation to their ability to exist within a dystrophic muscle and to differentiate into skeletal muscle cells. In this perspective, different known features of various stem cells are compared including mesoangioblasts and mesoderm-derived stem cells, which are associated with the pericyte compartment.

This chapter also provides an outline of the latest techniques used for the isolation/ generation and characterization of pluripotent and adult stem cells. We focus on their myogenic differentiation potential and the different strategies used for genetic manipula‐ tion including TALEN and CRISPR genome editing. We also explore the use of microRNAs as biological markers or as possible therapeutic targets to improve myogenic commitment of pluripotent and adult stem cells. Finally, based on the rapid advance in stem cell technology, we discuss a prediction of clinical translation for novel cell therapy protocols.

**Keywords:** Skeletal muscle regeneration, gene and cell therapy, TALEN and CRISPR ge‐ nome editing, microRNAs

© 2015 The Author(s). Licensee InTech. 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.


**7.9 Surgical treatment**

*Tendons*

**Stage Program**

Stage 1 Adequate warm up Ice after activity

*Program for patellar tendinopathy.*

Stage 2 Addition of period of rest and heat before activity

Stage 3 Addition of prolonged period of rest

**7.6 NSAIDS**

**Table 1.**

not assessed [46].

**7.7 Corticosteroids**

returning to activity.

**7.8 Other medical treatments**

Although the benefits of NSAIDs are dubious, they are the most common drug used for symptomatic relief [43]. Although the use of "anti-inflammatory" medication seems paradoxical for a condition that is essentially degenerative, it is believed NSAIDs might act via mechanisms different from their conventional anti-inflammatory actions [44]. In vitro studies in human cartilage have revealed a variable interaction of NSAIDs with glycosaminoglycans (GAGs) where some have been shown to stimulate and some to inhibit, its synthesis [45]. This mechanism also sheds light on its effect on the synthesis of extra-cellular matrix. In a double blinded placebo controlled study, the use of NSAIDs in tendinopathy, piroxicam did not benefit patients with Achilles tendinopathy however topical ketoprofen reached the target tissue in patients with patellar tendinopathy, but the clinical efficacy was

Physiotherapy(isometric quadriceps exercises and an elastic knee support)

Local anti-inflammatory treatments, including non-steroidal anti-inflammatory drugs (NSAIDs)

Corticosteroids are known for reducing the symptoms arising from the inflamed synovial structures. However the role of corticosteroids remains controversial in management of tendinopathy. According to Jozsa and Kannus [47] steroids are contraindicated in acute phase of tendinopathy and in the late chronic phase of tendinopathy when the tendon degeneration is advanced which may lead to tendon rupture. However it has proved beneficial when diluted with anesthetic for diagnostic reasons and to minimize adverse effects and in conditions where 1–6 week rest period combined with a programme of gradual strengthening is required before

Aprotinin, an 85 amino acid 65 kDa basic polypeptide extracted from bovine lungs has shown to offer better pain relief than steroids at least in short term. However aprotinin which is a strong inhibitor MMP (matrix metalloproteinase) is less effective in insertional tendinopathy as compared to main body [48]. Another non-surgical treatment option includes use of sclerosing agent with chemical irritant (e.g. polidocanol) [8, 49, 50]. These targets the neovascularization and accompanying nerves. The use of platelet-rich plasma injection has been tried in tendinopathy and favorable outcome have been found [51–53]. However still there is no level 1 or level II studies about role of PRP in patellar tendinopathy. The glyceryl trinitrate (GTN) patch [54, 55], which delivers nitric oxide (NO) to pathological tendon which play role in tendon healing. But we still need level1or level II evidence

**62**

to support it.

Patellar tendon surgery is indicated in patients who have failed conservative management more than 6 weeks [56–58]. A variety of surgical procedures have been described such as resection of the tibial attachment of the patellar tendon with realignment, drilling of the inferior pole of the patella, macroscopic necrotic area excision [59], repair of macroscopic defects, longitudinal tenoplasty/tenotomy of the tendon [60] percutaneous longitudinal tenotomy, percutaneous needling [61] and arthroscopic assisted decompression [62, 63] of the tendon, possibly with excision of the inferior pole of the patella however the effectiveness of any single procedure has not been elucidated.


*3.2. Coating Characterisation*

It was shown that, with the selected parameter set, it was possible to produce well adhering and dense coatings from all single oxides and their ternary blends. The results of the roughness measurements for the as-sprayed coatings shown in Figure 3 reveal clear differences. In the case of single oxides, the TiO*x* coating has the highest as-sprayed *R*z value with approximately 70 ± 2 μm. The Cr2O3 coatings show the lowest roughness with approximately 33 ± 2 μm. Coatings produced from the powder blends show roughness values between these limits. The as-sprayed Rz value of the ACT, CAT, and TAC coatings are 50 ± 4 μm, 49 ± 3 μm, and 55 ± 6 μm, respectively. By grinding and polishing the roughness of the samples, it can be reduced by more than 90%. As can be seen in Figure 3, the Rz values after polishing are in the range of 1.3 ± 0.2 μm for Cr2O3 and 3.2 ± 0.2 μm for Al2O3. The roughness of the TiO*x* coating can even be reduced by almost 98% by polishing and indicates particularly good machinability. The coatings from the blends show a similar behavior. The Cr2O3-rich CAT coating with 2.3 ± 0.5 μm have the lowest roughness. After polishing, all coatings have a comparable roughness, which makes them suitable for wear testing.

**Figure 3.** Roughness values of as-sprayed and polished coated samples.

The results of coating thickness and porosity after 10 passes are shown in Figure 4. The coating thickness gives an indication of the deposition rate of the single oxides and the blends. In the case of the individual oxides, the highest coating thickness (469 ± 16 μm) was measured for the TiO*x* coating, while the chromia coating has the lowest coating thickness. A similar observation was made by others [17]. For the coatings from the blended powders, the titanium oxide-rich TAC coating with 430 ± 18 μm shows significantly higher thickness than the ACT and CAT coatings, where the coating thickness is 342 ± 14 μm and 369 ± 16 μm, respectively.

**Figure 4.** Thickness and porosity of plain oxide coatings (A, C, T) and coatings from blends (ACT, CAT, and TAC).

When studying the porosity, it is noticeable that different levels exist between the individual oxides as a result of the identical spray parameters. While the porosity of the Al2O3 coating is about 5.0% ± 1.0%, the TiO*x* coating with a porosity of 1.6% ± 0.1% is significantly denser. As illustrated in Figure 4, the alumina-rich ACT and chromium oxide-rich CAT coatings have similar porosities of 3.7% ± 0.8% and 3.0% ± 0.5%, respectively. Only the TAC coating with a high content of TiO*x* shows a lower porosity of 1.7% ± 0.2%.

Low magnification SEM images of the cross sections of the coatings from the blends are shown in Figure 5a,c,e. The characteristic microstructure of thermal spray coatings, characterized by unmolten particles, pores, microcracks, and a lamellar structure, is observed. Splats from the individual oxide particles are clearly distinguishable. The high magnification images in Figure 5b,d,f show that the coatings of each blend consist of individual splats of a comparable grayscale denoted as I, II, and III in each of the images.

The results of the measurements of local chemical composition of these individual splats by EDS are compiled in Figure 6. The dark areas (SEM area I) in all coatings have a composition of approximately 60 at % oxygen and 40 at % aluminum, while the elements titanium and chromium were not detected. The bright areas (SEM area II) assigned to Cr2O3 contain a significant proportion of titanium in the range between 0.9 at %. and 2.2 at %. It is also noticeable that these Cr2O3 lamellae contain more oxygen than expected (slightly above 60 at %). Variations in the grayscales in these lamellas were found to be caused by variations of the oxygen content. The areas III with an intermediate grayscale relate to the titanium oxide splats.

**Figure 5.** SEM images (BSD detector) of APS Al2O3-Cr2O3-TiO2 composite coatings: top row: ACT-coating: (**a**) overview image, (**b**) detailed image with marked areas for the EDS measurement. middle row: CAT-coating: (**c**) overview image, (**d**) detailed image with marked areas for the EDS measurement. bottom row: TAC-coating: (**e**) overview image, (**f**) detailed image with marked areas for the EDS measurement. The EDS measurements of the marked areas are shown in Figure 6.

The results of the hardness measurements are presented in Figure 7 and show that all single oxide coatings have high hardness values above 1000 HV0.3, while the Cr2O3 coating has the highest hardness of 1250 ± 79 HV0.3. The coatings from powder blends do not reach the hardness of the plain chromia and alumina coatings. Only the chromium oxide-rich CAT coating has a hardness of 1074 ± 65 HV0.3, which is higher than the hardness of the TiO*x* coating. The lowest hardness was found for the ACT coating.

**Figure 6.** EDS analysis of composite coatings: chemical composition of the material areas marked in Figure 5b,d,f.

**Figure 7.** Hardness and sliding wear rates of plain oxide coatings (A, C, T) and composite coatings (ACT, CAT, TAC).

The results of the sliding wear tests are also shown in Figure 7. The Al2O3 coating shows the highest wear rate (8.2 ± 0.1 × 10−4 mm3·N−1·m−1), which is more than twice than that of the TiO*x* coating. The wear resistance of the chromium oxide coating is so high that no meaningful wear rate was measured. The coatings from the blends also show a high wear resistance. The ACT and TAC coatings have a very similar wear rate. The chromium oxide-rich CAT coating proves to be more wear resistant.

The presentation of the XRD patterns, displayed in Figure 8, is limited to the range 2θ = 18◦–82◦. For the powder blends, the presence of α-Al2O3 (corundum), Cr2O3 (eskolaite), and different titanium oxide phases, as expected from the pattern of the individual oxides (see Figure 2) was found. The XRD patterns of the coatings from the blends, shown in Figure 8, reveal the presence of α-Al2O3, γ-Al2O3, Cr2O3 (eskolaite), and different titanium oxide phases. A shift of the peak positions relative to the standards did not occur. Due to the inhomogeneous distribution of oxygen, the intensity of the suboxide peaks is low. A quantitative determination of the phase is not possible. A change in the intensity of some peaks was observed. For the TAC coating, the TiO*x* peaks of 2θ = 26◦–30◦ lose significantly in intensity in the coating compared to the powders. The intensity of the TiO2 rutile peaks at 2θ = 27.4◦ (110) and 2θ = 54.2◦ (211) increases markedly. For all coatings, especially for the CAT and TAC coatings, a decrease of peak intensity of α-Al2O3 from powder to coating was detected.

**Figure 8.** Diffraction patterns of the powder blends and corresponding coatings: (**a**) ACT, (**b**) CAT, and (**c**) TAC.


**Diagnostic Accuracy and Interpretation of Urine Drug Testing for Pain Patients: An Evidence-Based Approach**

Amadeo Pesce1, Cameron West1, Kathy Egan-City1 and William Clarke2 *1Millennium Research Institute, 2Johns Hopkins School of Medicine, USA*


**5. Conclusions**

A hot water wash prior to carcass chilling did not significantly reduce microorganisms assessed under the conditions evaluated in this study. Dry chilling of carcasses can potentially increase the shelf life of meat products as it delays the growth of bacteria under the refrigerated conditions of storage during transport and distribution. Data collected can be used to select chilling systems to maximize shelf life, especially in long-term refrigerated storage conditions of never frozen beef products. The optimal shelf life of striploins can be achieved using dry chilling air systems, which will guarantee the required 130 days of shelf life for the export of fresh, never frozen beef from Australia to the EU. The use of spray chilling schemes increases available water for the growth of bacteria resulting in higher growth rates of bacteria during the long-term refrigerated storage and therefore a reduced shelf life. This extended quality preservation over an extended shelf life period allows more flexibility in beef exports, especially for major producers that are far from target consumer markets. Understanding the best parameters for beef carcass processing and storage will allow the beef industry to select optimized chilling schemes for long-term storage and increased consumer acceptability.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/foods10061403/s1. Table S1. Experimental design of no washed and hot water washed carcasses in a beef processing facility at each sampling point, before and after carcass wash, and 24-h carcass chilling, Table S2. Experimental design at each sampling date for the extended shelf-life evaluation of beef striploins. Table S1. Experimental design of no washed and hot water washed carcasses in a beef processing facility at each sampling point, before and after carcass wash, and 24-h carcass chilling. Table S2. Experimental design at each sampling date for the extended shelf life evaluation of beef striploins.

**Author Contributions:** Conceptualization, M.M.B., M.X.S.-P. and M.F.M.; methodology, D.E.C., R.M., S.J.F., K.E.H., M.M.B. and M.X.S.-P.; validation, D.E.C., M.F.M. and M.X.S.-P.; formal analysis, D.E.C. and M.X.S.-P.; investigation, D.E.C., R.M., S.J.F., K.E.H., M.M.B., M.F.M. and M.X.S.-P.; resources, M.M.B., M.F.M. and M.X.S.-P.; data curation, D.E.C.; writing—original draft preparation, D.E.C.; writing—review and editing, D.E.C., M.X.S.-P., M.F.M. and M.M.B.; visualization, D.E.C., and M.X.S.- P.; supervision, M.M.B., M.F.M. and M.X.S.-P.; project administration, D.E.C., K.E.H., M.M.B., M.F.M. and M.X.S.-P.; funding acquisition, M.M.B., M.F.M. and M.X.S.-P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded through the joint efforts of the International Center for Food Industry Excellence at Texas Tech University and beef processor Teys Australia.

**Institutional Review Board Statement:** Not Applicable.

**Informed Consent Statement:** Not Applicable.

**Data Availability Statement:** All data from the research conducted are available on request from the corresponding author. The data are not publicly available due to the privacy of our industry collaborator that allowed for the project to be conducted.

**Acknowledgments:** We would like to acknowledge the hard work of the Texas Tech University Food Microbiology Laboratory personnel, who made the processing and storing of striploins possible. Furthermore, we would like to acknowledge the plant personnel who helped the project and made everything within the harvest and fabrication floor run smoothly, as well as the great hospitality throughout our stay in Brisbane, Australia.

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