**3.1. Macroscopic appearance of the LBW Ti‐6Al‐4V butt joints**

Visual inspection of laser weldments showed bright silver metallic surfaces from the top and root sides, indicating stable Ar shielding gas atmosphere during the LBW process. All obtained welds were fully penetrated and showed an hourglass shape. A typical transverse cross section of the obtained laser beam welded joint is shown in **Figure 2**. Three distinct regions of the weld are visible: the fusion zone (FZ), heat‐affected zone HAZ and base metal (BM). The FZ was distinguished by its columnar dendrites, which grew in the direction from the fusion line to the weld centre (see **Figure 2**). It should be noted that no significant differences between the as‐welded and heat‐treated conditions regarding the weld geometry were found.

**Figure 2.** Transverse cross section macrograph of the laser beam welded Ti‐6Al‐4V butt joint.

The most frequently observed defects in laser weldments of titanium alloys are underfills and porosity [3, 5, 16, 17]. These imperfections are particularly undesirable for structures subjected to cyclic loading because they lead to stress concentration and consequently premature crack formation. The evaporation and expulsion of the molten material from the weld pool and liquid metal flow around the keyhole are dominant processes affecting the formation of underfills [2, 18], which are always present in cases of autogenous laser welding. The use of an additional filler wire in the present work allowed overfilling to be produced and geometrical weld imperfections such as underfills to be partially eliminated. However, filler wire resulted in weld reinforcements from both face and root sides. Abrupt change in the thickness due to weld reinforcement leads to stress concentration at the weld toes and roots and consequently reduces the fatigue strength of the joints. Although the macrograph presented in **Figure 2** reveals almost no underfills, a single weld cross section cannot guarantee the uniformity of the weld profile over the whole length of the seam. This problem can usually be solved by extracting more than one specimen for metallurgical examination. In the present work, the maximum measured underfill depth was approximately 70 µm, which is less than 3% of the specimen thickness. The maximum observed reinforcement was approximately 350 µm. The geometric profile imperfections of laser weldments used in the aerospace industry are strictly limited by several standards: AWS D17.1 [19] and EN 4678 [20]. In terms of underfills and weld reinforcements, EN 4678 is more stringent; the maximum allowed underfill depth for butt joints is 5% of the total thickness and maximum reinforcement is 490 µm for the specimens of the 2.6‐mm‐thick material. All welds in our work confidently passed the acceptance criteria in terms of the weld profile imperfections for the aerospace industry.

The spherical shape of most pores observed in the present study indicates gas‐type porosity. A number of researchers have investigated the main causes of porosity when laser welding titanium alloys [18, 21, 22]. Potential sources for porosity formation are mainly from the presence of excessive hydrogen in the FZ, which is rejected upon solidification, and keyhole instability leading to the entrapment of shielding gases. The investigation of the influence of

welding parameters on the amount of porosity in the laser beam welded Ti‐6Al‐4V butt joints can be found elsewhere [2, 3, 5].

### **3.2. Microstructure and microtexture**


**Laryngeal Lesion Classification Based on Vascular Patterns in Contact Endoscopy and Narrow Band Imaging: Manual Versus Automatic Approach**

**Nazila Esmaeili 1,\*, Alfredo Illanes 1, Axel Boese 1, Nikolaos Davaris 2, Christoph Arens 2, Nassir Navab 3 and Michael Friebe 1,4**

Received: 29 May 2020; Accepted: 18 July 2020; Published: 19 July 2020

**Abstract:** Longitudinal and perpendicular changes in the vocal fold's blood vessels are associated with the development of benign and malignant laryngeal lesions. The combination of Contact Endoscopy (CE) and Narrow Band Imaging (NBI) can provide intraoperative real-time visualization of the vascular changes in the laryngeal mucosa. However, the visual evaluation of vascular patterns in CE-NBI images is challenging and highly depends on the clinicians' experience. The current study aims to evaluate and compare the performance of a manual and an automatic approach for laryngeal lesion's classification based on vascular patterns in CE-NBI images. In the manual approach, six observers visually evaluated a series of CE+NBI images that belong to a patient and then classified the patient as benign or malignant. For the automatic classification, an algorithm based on characterizing the level of the vessel's disorder in combination with four supervised classifiers was used to classify CE-NBI images. The results showed that the manual approach's subjective evaluation could be reduced by using a computer-based approach. Moreover, the automatic approach showed the potential to work as an assistant system in case of disagreements among clinicians and to reduce the manual approach's misclassification issue.

**Keywords:** laryngeal cancer; contact endoscopy; narrow band imaging; automatic classification; feature extraction; machine learning


*3.3. Validity of the Reference Equation*

According to 20% of the sample (*n* = 31), no significant differences (*p* = 0.984) were observed between the actual values performed by participants (319 [141; 360] steps) and those obtained by the equation (290 [173; 339] steps).

#### **4. Discussion**

This study determined a reference equation for IST performance and showed that the variability of results was explained by sex and age. It is important to mention that these values were obtained from participants over a wide range of ages between 19 and 93 years. The inclusion of age as a determinant variable for the variability of results was expected because the aging process causes skeletal muscle contractile function loss [29] and lower oxygen consumption [30], leading to a worse exercise capacity. Another explanation for these results is the greater probability of the difficulty for older adults to negotiate stairs as a marker of functional decline, which can influence the performance in step mode testing. This difficulty is not only associated with reduced lower-limb strength, but also with reduced sensation and balance, and an increased fear of falling [31]. In fact, age has been the most indicated predictor of performance in exercise field tests, namely in other steps tests [32–34], walking tests [16,17,35], and upper-limb exercise tests [17].

We also expected that sex could influence the performance of the IST. Sex is considered a strong predictor of exercise capacity [36] that is consistently observed in reference equations for the prediction of exercise capacity in field tests, especially in walking tests [35,37,38] and step tests [32–34].

On the other hand, we expected that other independent variables could influence the performance of the IST, highlighting body composition. Body composition, through anthropometric measures, can be a determinant variable in the assessment of exercise capacity [39]; however, the variables used in our study (weight, height, and BMI) did not influence performance in the IST. We hypothesized that weight could be a predictor of a smaller number of steps performed. Overweight, associated with more fat accumulation, increases the workload on horizontal (walking) and vertical displacements, which normally occur during step mode testing [40–42]. Despite the controversy over whether BMI is the best measure of obesity, BMI ranges are still based on excess body fat [28]. As such, it was expected that this variable also could negatively influence performance in terms of the number of step tests; however, this was not observed in our reference equation. The lack of variability in BMI values in our sample was not a limitation for this observation because the participants included in the development of the reference equation (80% of participants) presented a wide variety of BMI values (minimum of 17 and maximum of 37 kg/m2). Although it could be argued that the inclusion of patients with a lower (≤18.5 kg/m2: underweight) and higher ( ≥ 30 kg/m2: obese) BMI introduced a bias because reference values should be derived from apparently healthy individuals, the main aim of our study was to achieve maximum representativeness from community-dwelling people. There is no consensus in the literature regarding the inclusion of participants with the lowest and highest BMI values for the determination of reference equations for field test where these participants had been excluded from some studies [32,35,38] but not from others [33,43].

The absence of differences between the number of steps achieved by participants and those predicted by the equation in 20% of participants of our sample is considered a strength in our study, suggesting that this equation is valid and can be applied in clinical practice. Another important strength was the accomplishment of the sample size calculated prior to the study, despite the restrictions due to the COVID-19 pandemic during data collection. Additionally, this equation was developed using only age and sex variables, facilitating its direct translation to clinical practice. However, the inclusion of other variables, such as peripheral muscle strength, to explore their influence in the performance of the IST is important in future studies. Additionally, in future studies, a larger sample size is important to determine normative values for the IST, contributing to greater information on its clinical interpretability.

This study has limitations that are important to mention. Firstly, the use of a convenience sample might have affected the results. More efforts are necessary to recruit participants from different settings and geographical locations to obtain a representative sample because our data collection was only performed in the north of Portugal. Despite the results from this study being obtained from participants over a wide range of between 19 and 93 years of age, it is important to mention that the number of participants in each age decade was not proportional, in which a lower number of participants were observed in the older decades. More participants in older decades are equally important, especially for the determination of normative values.

This is the first study to develop a reference equation for the IST in the Portuguese adult population and, to the best of our knowledge, one of the only studies to determine a national reference equation based on the performance of a step test (number steps). In fact, in the literature, most of the reference equations for step tests are developed with the intent to predict cardiorespiratory fitness, based on the estimation of maximum oxygen uptake [1,44–46]. Equations based on the performance of field tests provide advantages in clinical practice, yielding the utility of these tests as an outcome measure of exercise capacity. In addition, they provide an easy interpretation of patients' exercise capacity and prognosis in different conditions/diseases.

#### **5. Conclusions**

The established reference equation for the IST demonstrated that age and sex were the determinant variables for the variability of the results. This study also demonstrated that there were no differences between the actual values performed by participants and those obtained by the equation. These results will help to detect people with a lower exercise capacity, yielding the development of exercise programs and the assessment of their effectiveness.

**Author Contributions:** Conceptualization, R.V. and A.M.M.; methodology, R.V., C.C. and A.M.M.; software, R.V.; validation, C.C. and A.M.M.; formal analysis, R.V., C.C. and A.M.M.; investigation, R.V., A.T., C.S., F.M., L.T., L.M., T.G., C.M., C.C. and A.M.M.; resources, C.C.; data curation, R.V.; writing—original draft preparation, R.V., A.T., C.S., F.M., L.T. and L.M.; writing—review and editing, C.M., C.C. and A.M.M.; visualization, C.C. and A.M.M.; supervision, C.C. and A.M.M.; project administration, R.V. All authors have read and agreed to the published version of the manuscript.

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

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the School of Health—Polytechnic Institute of Porto (protocol code E0134, date of approval: 13 April 2020). The study was registered at ClinicalTrials.gov (registry number NCT04801979).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data are available upon request from the corresponding author.

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

#### **References**

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**1. Introduction**

The asymmetric intermolecular aldol addition catalysed by (*S*)-proline, proposed by List and co-workers in 2000 [1], is the prototype of enamine-based organocatalysis [2,3]. Proline is the smallest airand water-stable bifunctional catalyst; it is inexpensive, non-toxic, and available in both enantiomeric forms. It has been proven to catalyse enantioselective α-functionalizations of carbonyl compounds (aldol and Mannich reactions, Michael additions, α-halogenations, oxygenations, aminations, and so on), adopting reaction protocols that do not require inert atmosphere and anhydrous conditions and are carried out at room temperature [4,5].

The proline-catalysed aldol reaction [4,6–19] has been object of in-depth analyses after the first mechanistic rationale proposed by List and Houck [20], in particular, fundamental contributions have been given by Seebach [21], Armstrong and Blackmond [22,23], Sharma and Sunoj [24], Benaglia [25], and Gschwind [26,27]. However, proline scarce solubility in most organic solvents has limited its use in dimethylsulfoxide (DMSO), acetonitrile, or dimethylformamide (DMF). Moreover, proline often displays poor activity, requiring the use of high catalyst loadings and high reaction times, sometimes with unsatisfactory stereocontrol [1,28–36]. Because, in several cases, proline-catalysed aldol reactions are still underdeveloped, the last 15 years have witnessed an intense effort aimed at modifying the proline scaffold, following two directions: (1) the carboxylic group is replaced by a new hydrogen-bonding donor, such as a tetrazole, or by a sterically demanding group, such as the Hayashi–Jørgensen diarylmethanol and related compounds, as exhaustively reviewed by Trost [37]; and (2) the carboxylic group is retained and a supplementary substituent is bound to the proline scaffold. The new substituent, generally installed on the 4-OH group of 4-hydroxyproline, may play different roles: (*i*) it modifies the solubility profile of the parent amino acid, expanding the solvent choice to further classes [38]; and/or (*ii*) it enhances the catalyst activity and stereoselectivity, allowing a reduction of catalyst loading and reaction time; and/or (*iii*) it allows the catalyst immobilization on a solid support [39–56], adopting a biphasic condition reaction protocol. Despite that high levels of reactivity and selectivity have been achieved with these modified prolines, most of the aforementioned proline derivatives require multi-step syntheses, dramatically increasing the catalyst cost, a severe limitation particularly when the catalyst cannot be e fficiently recycled.

After having contributed to the synthesis of prolines, mostly modified with the incorporation of ionic tags on 4-position, and obtaining excellent results in terms of activity and stereoselectivity as well as catalyst recyclability [57–66], we decided to go back to the parent unmodified (*S*)-proline. We envisaged to improve the performance of this small, stable, inexpensive, non-toxic, and easily available organocatalyst exploring new experimental conditions.

The role of the solvent in determining the aldol reaction e fficiency was also addressed by other authors. Invariably, the use of unmodified proline (without additives) forced to choose polar aprotic solvents to obtain acceptable yields and selectivities [1,11,13–15,28–36,44,45]. A peculiar case was represented by ionic liquids (ILs) [67–72], which allowed in a few cases to decrease the catalyst loading (up to 1 mol%) and, during the work-up, to confine proline in a separate phase, enabling a simple product isolation and the reuse of the catalytic system. In recent literature, attempts are reported where proline is used in acetone/CHCl3 mixtures [73], in DMF at 4 ◦C (a condition that often requires several days) [74], in *tert*-butyl methyl ether (MTBE) [75], in deep eutectic solvents [76,77], or under solvent-free conditions, with [78–80] or without [81] the ball milling approach. However, many issues associated with the use of proline remain unsolved and polar aprotic solvents are characterized by several undesirable features (toxicity, high production cost, high environmental impact, di fficult product recovery) [82–84].

The use of unmodified proline can be also combined with additives [85,86], such as water [85–87], acids [85,86,88], diols [89,90], amines [85,86], or thioureas [91–93]. In these cases, the additive can tune the solubility, the reactivity, and/or the stereoselectivity of native proline, making the asymmetric aldol process more e fficient [18]. In one case, the addition of achiral guanidinium salts as additives allows to switch the diastereoselectivity as a function of the counterion, for example, tetrafluoroborate versus tetraphenylborate [94]. Nevertheless, the achieved performance is not optimal yet (long reaction times, stereocontrol strongly depending on the substrate) and some drawbacks are still present, such as high proline loadings and the cost of the not recovered chiral additive. Significant advances were accomplished employing metal salts as additives [95–106]. In particular, Reiser and co-workers developed a strategy based on cobalt(II)-proline complexes, which ensured excellent results in direct aldol reactions involving aromatic aldehydes [106]. However, several disadvantages lead the avoidance of the use of metals, especially at an industrial level (costs, toxicity, environmental impact, limited sources) [107–109].

In the present work, we aim to avoid the use of both polar aprotic solvents and additives (being sometimes expensive, mostly non-recoverable, and contaminants, used in non-generalizable procedures), in order to develop an efficient and sustainable organocatalyzed aldol condensation protocol, which can be interesting from a scale-up and an industrial point of view. In particular, our goals are as follows: (1) a reduction of the process costs, related to employed solvents and reagents, but also purification and waste disposal; and (2) an improved reactivity, especially for poorly reactive substrates. We planned to achieve these objectives by using the following: (*i*) the native proline, a small, stable, inexpensive, and non-toxic organocatalyst; and (*ii*) the minimum amount of a low-cost, non-toxic reaction solvent, enabling a good process e fficiency and a simple and inexpensive final reaction work-up.

A number of research groups noticed that protic media were not suitable for aldol condensations promoted exclusively by native proline [15,29–33,87]. However, despite a plethora of studies focused on the use and the role of water (as solvent, co-solvent, or additive) [31,32,34,87,100–105,110,111], very few authors extended their investigations to alcohols [15,29,31,42,102,106], discouraged by the generally observed poor diastereo- and enantioselectivity. Only when proline was used in combination with metal salts as additives, the use of methanol as solvent [106] or co-solvent [102] a fforded acceptable results.

Intrigued by the few data available on the proline-mediated aldol condensation employing methanol, a prototypical green solvent [84,112] also in terms of LCA (life-cycle assessment) [113], we decided to

explore in depth the impact of methanol on the asymmetric intermolecular aldol condensation promoted by unmodified (*S*)-proline. It should be stressed, however, that efficient organocatalyzed aldol condensations invariably require a large excess of a liquid donor ketone (5–10 equivalents) that must thus be considered as a part of the reaction solvent-system.

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

#### *2.1. Optimization of the Reaction Protocol*

As model reaction, we selected the (*S*)-proline–catalysed aldol condensation between cyclohexanone **1a** and aromatic aldehydes **2** (Scheme 1). At the outset, we confirmed the low performance of proline in terms of stereocontrol in pure methanol, but soon we realized that the simple use of a hydroalcoholic solution as the reaction medium was highly profitable. Here, we report a comparison among (*S*)-proline–catalysed reactions between cyclohexanone **1a** and four different aromatic aldehydes **2a**–**d**, carried out in methanol/water (2/1 V/V), pure water, and pure methanol, respectively, all other parameters being kept identical (Table 1). The 2/1 V/V methanol/water mixture composition ensures that the aldol reaction takes place under homogeneous conditions.

**Scheme 1.** The benchmark aldol reaction.

**Table 1.** Comparison of different protic reaction media 1.

1 Reaction conditions: **1a** (5 equiv.), **2** (0.3 mmol), (*S*)-proline (10 mol%), rt, MeOH/H2O (20 μL/10 μL, 2/1 V/V) or H2O (10 μL), or MeOH (20 μL). 2 Determined by 1H NMR on the crude mixture. 3 Determined by chiral stationary phase (CSP)-HPLC on the crude mixture. 4 Here, 20 mol% of (*S*)-proline was used. rt = room temperature, h = hours, nd = not determined.

The data collected in Table 1 demonstrate the crucial role of water; if in pure water conversions are the lowest, enantioselectivity reaches the highest values. On the other hand, pure methanol displays the highest reactivity and the poorest stereocontrol. The 2/1 V/V methanol/water solution is able to combine the pros of the two pure solvents, providing the same conversions of pure methanol and almost the same *ee*s and good *dr*s observed in pure water.

In Table 2, the results are reported when the 2/1 V/V methanol/water solution was applied to aldol reactions between cyclohexanone **1a** and other aromatic aldehydes **2e**–**i** (Table 2).

**Table 2.** MeOH/H2O-based protocol applied to di fferent aromatic aldehydes **2** 1.

1 Reaction conditions: **1a** (5 equiv.), **2** (0.3 mmol), (*S*)-proline (10 mol%), MeOH/H2O (20 μL/10 μL), rt. 2 Determined by 1H NMR on the crude mixture. 3 Determined by CSP-HPLC on the crude mixture. 4 Here, 20 mol% of (*S*)-proline was used.

With the most reactive electron-poor aldehydes (**2a**, **2b**, **2e**, and **2f**), high conversion and high stereocontrol were achieved in only 19 h. Moreover, these results are excellent if compared with those reported in the literature for analogous transformations promoted by unmodified (*S*)-proline and exploiting more complex protocols [114–117]. Unfortunately, the limitations of the proline-catalysed aldol reactions were not completely overcome. In fact, electron-rich aromatic aldehydes were confirmed to be less reactive, requiring longer reaction times. More in detail, for substrates **2g** and **2h**, the conversions reached after 19 and 24 h, respectively, were modest; nevertheless, it is worth mentioning that the enantio- and the diastereoselectivities were both higher than those reported so far by proline-based protocols [118,119]. As far as the electron-rich *p*-methoxy benzaldehyde **2i** is concerned, the only example with proline (20 mol%) in DMSO reported a low conversion (15%) and absence of diastereoselection [105]. The e ffect on product conversion was even poorer when a Lewis acid and water were added. Exploiting our MeOH/H2O-based protocol, the product conversion remained poor (18%), but the reaction proceeded with good enantio- (90% *ee*) and diastereoselectivity (*anti*/*syn* = 86:14).

Once the performance of native proline in 2/1 V/V methanol/water solution had been examined, we explored the e ffect of a more methanol-rich aqueous mixture. In Table 3, aldol reactions of cyclohexanone **1a** and di fferent aldehydes **2** in 2/1 V/V and 4/1 V/V solutions are compared.

Doubling the methanol volume (40 μL), the conversions significantly improved with all the tested aldehydes, while maintaining an excellent to remarkable level of enantiocontrol (Table 3). The most reactive substrates (**2a**, **2b**, **2e**, and **2f**) provided excellent conversions in only 4 h, demonstrating an unprecedented reactivity of proline. Moreover, interesting amounts of product were obtained exploiting these reaction conditions for less electrophilic aldehydes as well (**2c,2d**, **2g,2i**; Table 3). Concerning the diastereocontrol, a slight drop of the *anti*/*syn* ratio was observed with some aldehydes when the volume of methanol was increased. Conversely, for benzaldehyde **2d** and 2-naphthyl aldehyde **2h**, the diastereoselection lightly improved. In the case of benzaldehyde **2d**, the better performance could be the result of the reduced amount of catalyst (10 mol%), exploitable thanks to the higher proline reactivity reached with larger amounts of methanol. In the case of the most reactive 4-nitrobenzaldehyde **2a**, we solved the problem of diastereoselectivity drop by adding the methanol amount in two portions (one half after 2 h), completely restoring the diastereocontrol, while maintaining a high reaction rate. In general, a good diastereoselectivity level is retained with this protocol (4/1 V/V methanol/water) compared with the literature data [114–119]. At the same time, reaction rates are significantly enhanced. Therefore, these reaction conditions represent the best trade-o ff between reactivity and stereoselectivity. In Table 3, this optimized protocol was extended to some other aldehydes (**2j**–**m**), with good results compared with the literature data [120–123]. In particular, aliphatic aldehyde **2j**, known as poorly responsive in this kind of organocatalysed reaction, reached an interesting conversion (63%) and remarkably high stereochemical results (>99% *ee* and *anti*/*syn* > 99:1), superior to those reported by other authors for unmodified proline [120].

**Table 3.** Optimization of the MeOH/H2O-based protocol 1.

1 Reaction conditions: **1a** (5 equiv.), **2** (0.3 mmol), (*S*)-proline (10 mol%), rt. 2 Determined by 1H NMR on the crude mixture. 3 Determined by CSP-HPLC on the crude mixture. 4 Here, 20 μL of MeOH was added after 2 h. 5 Here, 20 mol% of (*S*)-proline was used.

The next step of our investigation was directed to the ketone partner **1** of the asymmetric aldol condensation. In proline-catalysed aldol reactions, a typical drawback is represented by the excess of ketone over the limiting aldehyde generally required to achieve good yields. To increase the sustainability of the process, we planned to lower the ketone excess (Table 4).

Some aldehydes characterized by high or medium reactivity were selected for this study, in which the ketone amount was reduced to 2 equivalents. With almost all the tested substrates, high conversions and excellent *ee* values were again obtained. Although longer reaction times were required, the reaction rates remained worthy of note, especially when compared with the performance of other protocols in similar conditions. The main drawback of this procedure was a slight decrease of diastereoselectivity, an effect that is not immediately obvious. Benaglia, using the reaction progress kinetic analysis (RPKA) approach [25], a technique that allowed Blackmond et al. to define the kinetic rate law of proline-catalysed aldol reactions [23], proved the reversibility of the aldol reaction. Lowering the ketone excess leads to the following: (*i*) longer reaction times to preserve the same level of product conversion; and (*ii*) a less efficient opposition to the retroaldol reaction, which is a slow process within the time scale of our reactions. Both factors promote equilibrium on a little extent, likely accounting for the slightly decreased diastereocontrol observed when reduced amounts of cyclohexanone **1a** were used (Table 4). In conclusion, the high efficiency achieved by MeOH/H2O/(*S*)-proline-based protocol

allows to reduce the ketone excess, involving (*i*) slight adverse effects on aldol reaction performance; and (*ii*) benefits, such as lower costs and easier work up and product purification.

**Table 4.** Effects of cyclohexanone **1a** amount in the MeOH/H2O/(*S*)-proline-based protocol 1.

1 Reaction conditions: **2** (0.3 mmol), (*S*)-proline (10 mol%), MeOH/H2O (40 μL/10 μL), rt. 2 Determined by 1H NMR on the crude mixture. 3 Determined by CSP-HPLC on the crude mixture. 4 Here, 20 μL of MeOH was added after 2 h.

#### *2.2. Application of the Protocol to Other Ketones*

Afterwards, we focused on the application of the developed catalytic protocol to two different donor ketones **1b,1c** (Table 5). Considering the excellent performance (stereoselectivity and reaction rate) achieved employing the MeOH/H2O/(*S*)-proline protocol in the presence of 5 equivalents of **1a**, we decided for convenience to apply these conditions to the ketones investigation.

**Table 5.** MeOH/H2O/(*S*)-proline-based protocol applied to ketones **1b,c** 1.

1 Reaction conditions: **2** (0.3 mmol), **1** (5 eq.), (*S*)-proline (10 mol%), MeOH/H2O (40 μL/10 μL), rt. 2 Determined by 1H NMR on the crude mixture. 3 Determined by CSP-HPLC on the crude mixture. 4 Reaction carried out at 0 ◦C.

At first, we tested cyclopentanone **1b** with highly reactive 4-nitrobenzaldehyde **2a**, observing a particularly high reaction rate, with the transformation being complete in only 4 hours. This result is unprecedented in the presence of unmodified proline or most of its derivatives [124–127], confirming once again the high reactivity achievable employing the MeOH/H2O protocol. The corresponding product **3ba** was obtained with excellent *ee*, but low diastereoselectivity. This behaviour was expected because poorly diastereoselective aldol reactions catalyzed by proline or its derivatives were regularly reported for cyclopentanone **1b** [87,124–127]. To improve the diastereoselctivity, we lowered the reaction temperature to 0 ◦C and we obtained a good 78:22 *anti*/*syn* ratio, maintaining a high conversion in a reasonable time.

Considering the excellent performance achievable with MeOH/H2O/(*S*)-proline-based protocol, we were particularly interested in the results obtainable with less reactive aldehydes. In fact, 4-Br benzaldehyde **2g** and benzaldehyde **2d** provided the corresponding products (**3bg** and **3bd**, respectively) with good conversions and diastereoselectivities, and, noteworthy, with the best enantioselectivities ever achieved employing unmodified proline as catalyst [128].

As further confirmation, 2,2-dimethyl-1,3-dioxan-5-one **1c** (Table 5) also displayed good reactivity and stereoselectivity when reacted with less reactive aldehydes **2g** and **2d**. In particular, our results represent the first examples of organocatalyzed aldol condensation between 2,2-dimethyl-1, 3-dioxan-5-one **1c** and 4-Br benzaldehyde **2g** or benzaldehyde **2d**, promoted by only 10 mol% of proline [129–133].

At last, we applied our protocol to acetone **1d** as simple aliphatic ketone (Table S3, Section 2, Supplementary Materials). Although with 4-NO2 benzaldehyde **2a**, we obtained an unprecedented high reaction rate if compared with the published corresponding transformations, the enantioselectivity was poor, as commonly reported for the proline-catalysed aldol additions involving these substrates.

#### *2.3. Large-Scale Application of the Protocol*

Our aim is the development of an efficient and sustainable organocatalyzed aldol condensation protocol, which can be interesting from a scale-up perspective. Therefore, as a first step, we confirmed the excellent performance of the MeOH/H2O/(*S*)-proline-based protocol by carrying out the aldol condensation between moderately reactive benzaldehyde **2d** and cyclohexanone **1a** on a 10 mmol scale (gram scale). The desired product **3ad** was isolated in 78% yield and with high stereocontrol (90:10 *dr*, 95% *ee*), fully confirming the data obtained on small scale (Table 3).

The next step was the accomplishment of the same reaction on a 100 mmol scale of the limiting reagent benzaldehyde **2d** (Scheme 2) in order to study some aspects in more detail.

**Scheme 2.** Process scale-up on 100 mmol of limiting aldehyde **2d**.

At first, we investigated the impact of the aldehyde addition rate on the reaction outcome (Table 6). With benzaldehyde **2d** not being very reactive, good conversions were recorded only after 23 h and we did not observe a significant difference depending on the addition rate of benzaldehyde (Table 6).

Then, we monitored product conversion and stereoselectivity for a longer reaction time (Table 6), to establish if a high conversion could be achieved without a significant loss in stereocontrol exploiting our reaction conditions. Indeed, as previously mentioned, aldol reaction is reversible and longer reaction times could make the retroaldol process competitive, providing a decreased diastereomeric ratio. Actually, we observed a slow increase of the product conversion, achieving 85% after 2 days, without a significant erosion of *anti*/*syn* ratio (in comparison with small scale-reactions, a slightly lower *dr* was recorded, which remained constant for the first 48 h). We confirmed that even the enantiomeric excess of the product remained at high levels (94% *ee* after 47 h).

**Table 6.** Process scale-up study 1.

1 Reaction conditions: **2d** (100 mmol), **1a** (500 mmol), (*S*)-proline (10 mol%), MeOH/H2O (13.33 mL/3.33 mL), rt. Total volume = 79 mL. 2 Determined by 1H NMR on the crude mixture. 3 Determined by CSP-HPLC on the crude mixture.

The results reported in Table 6 clearly show that the best reaction outcome is obtained at a reaction time representing the best balance between product conversion and stereocontrol. To further explore this effect, we compared the data obtained with different moderately or poorly reactive aldehydes (Table 7).

**Table 7.** Study of the reaction outcome as a function of the reaction time 1.

1 Reaction conditions: **2** (50 mmol), **1a** (5 eq.), (*S*)-proline (10 mol%), MeOH/H2O (6.67 mL/1.67 mL), rt. 2 Determined by 1H NMR on the crude mixture. 3 Here, 20 mol% of (*S*)-proline was used.

Concerning the stereoselectivity, in this study, we focused our attention on diastereoselectivity variation, which is much more impaired by retroaldol reaction (see Supplementary Materials for a study on enantioselectivity variation). The data collected in Table 7 demonstrate that the aldol transformation reaches a position, after which the product conversion no longer grows, while the *dr* continues to drop. The time required to achieve this situation depends on the aldehyde reactivity. On the other hand, the rate of retroaldol process is less affected by the aldehyde nature; therefore, the retroaldol effects are less troublesome for reactive aldehydes (high conversion in short time with high *dr*) and more marked for poorly reactive aldehydes (long time required to reach acceptable conversion with low *dr*). This study proves that, in the asymmetric aldol process promoted by proline, the reaction time providing the best performance (balance between conversion and stereoselectivity) strongly depends on the substrate; therefore, a careful investigation should be done before tackling a large-scale application.

A further point that we evaluated to increase the sustainability of our large-scale protocol was the reduction of the ketone excess. For this purpose, we applied the MeOH/H2O/(*S*)-proline-based protocol to moderately reactive benzaldehyde **2d** (50 mmol) in the presence of only 2 equivalents of cyclohexanone **1a**, monitoring the results over the time. After 71 h, we achieved the highest product conversion (83%) with an excellent 89:11 *dr*. Prolonging the reaction time (98 h) only led to a drop in *dr* (84:16). These findings suggest that, exploiting our protocol, a large excess of ketone (5 equivalents) only enhances the initial reaction rate, but it is not necessary for the achievement of an excellent final performance.


2.2. Direct simulation

### 2.2.1. Governing equations and finite difference formulation

Both flow and acoustic fields are solved by the two-dimensional compressible Navier-Stokes equations in a conservative form, which is written as:

$$\left(\mathbf{Q}\_t + (\mathbf{E} - \mathbf{E}\_\mathbf{v})\_x + (\mathbf{F} - \mathbf{F}\_\mathbf{v})\_y = \mathbf{0},\tag{3}$$

where Q is the vector of the conservative variables, E and F are the inviscid fluxes, and Ev and Fv are the viscous fluxes. The spatial derivatives and time integration were evaluated by the sixth-order accurate compact finite difference scheme [15] and a third-order accurate Runge-Kutta method. To suppress the numerical instabilities associated with the central differencing in the compact scheme, we use a tenth-order accurate spatial filter shown below:

Figure 1. Configurations for flow around a two-dimensional square cylinder.

$$a\_f \hat{\boldsymbol{\varphi}}\_{i-1} + \hat{\boldsymbol{\varphi}}\_i + a\_f \hat{\boldsymbol{\varphi}}\_{i+1} = \sum\_{n=0}^5 \frac{a\_n}{2} (\boldsymbol{\varphi}\_{i+n} + \boldsymbol{\varphi}\_{i-n}) \tag{4}$$

where φ is a conservative quantity and φb is the filtered quantity. The coefficients an are the same as the values used by Gaitonde and Visbal [16], and the parameter αf is 0.47.

### 2.2.2. Computational grids and boundary conditions

Figure 2 shows the computational domain and boundary conditions. The coordinates originate from the center of the cylinder. Generally, the nonreflecting boundary conditions based on the characteristic wave relations [17–19] are used at the inflow, upper, and outflow boundaries along with a buffer region. The role of the buffer region is similar to that of the "sponge region" of Colonius et al. [20]. At the wall, the nonslip and adiabatic boundary conditions are used.

For all the cases of M = 0.2–0.6, the same grids are used. The computational domain is divided into three regions of different grid spacings as shown in Figure 2: a vortex region [�4.0 ≤ x/d ≤ 30.0, �4.0 ≤ y/d ≤ 4.0], a sound region [�70.0 ≤ x/d < �4.0, 30.0 < x/d ≤ 70.0, �70.0 ≤ y/d < �4.0, 4.0 < y/d ≤ 70.0], and a buffer region [�500.0 ≤ x/d < �70.0, 70.0 < x/ d ≤ 500.0, �500.0 ≤ y/d < �70.0, 70.0 < y/d ≤ 500.0].

The spacing in the vortex region is prescribed to be fine enough to analyze the separated shear layer and the vortical structures in the wake of the cylinder. Figure 3 shows the computational grid near the cylinder. The spacing adjacent to the cylinder surface is Δxmin/d and Δymin/ d = 0.0025. With this grid distribution, the number of grid points within the separated shear layer for Re = 150 is 22 in the x, y direction (the thickness of the separated shear layer was estimated by δ/d ~ 1/Re0.5 and 0.08 for Re = 150 like the circular cylinder [6]), and the separated shear layer can be sufficiently captured. In the whole vortex region, Δx/d and Δy/d are less than 0.2, where the

number of grid points within a shed vortex is about 15 in the x, y direction (the size of the vortex is estimated to be about 3d by the spacing of the local maxima of vorticity in the computational

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331

Figure 3. Computational grid near cylinder for direct simulations. Every 10th grid line is shown for clarity.

In the sound region, the spacing is prescribed to be larger than that in the vortex region but still fine enough to capture the acoustic waves. The spacings are Δx/d, Δy/d ≤ 0.23 except for the downstream region of the cylinder. In the downstream region, the largest spacings are Δx/d and Δy/d = 0.46. This is because the acoustic wavelength becomes longer than that in the upstream region due to the Doppler effects. In the whole sound region, more than 20 grid points are used per one acoustic wavelength of the tonal sound at the frequency of the vortex

After many preliminary tests, grid- and domain-size independence has been established for

The two-dimensional Lighthill's equation [Eqs. (1) and (2)] is solved based on the wave equation. Here, the open-source software, FrontFlow/blue-ACOUSTICS, was used. Here, the acoustic simulations are performed in a frequency domain using finite-element methods. A

results) and the vortices were sufficiently analyzed.

shedding, and the acoustic waves are sufficiently captured.

2.3.1. Governing equations and discretization formulation

component perturbed at the frequency f of quantify gf can be written as:

the solutions presented in this chapter.

2.3. Hybrid simulation

Figure 2. Computational domain and boundary conditions for direct simulations.

Figure 3. Computational grid near cylinder for direct simulations. Every 10th grid line is shown for clarity.

number of grid points within a shed vortex is about 15 in the x, y direction (the size of the vortex is estimated to be about 3d by the spacing of the local maxima of vorticity in the computational results) and the vortices were sufficiently analyzed.

In the sound region, the spacing is prescribed to be larger than that in the vortex region but still fine enough to capture the acoustic waves. The spacings are Δx/d, Δy/d ≤ 0.23 except for the downstream region of the cylinder. In the downstream region, the largest spacings are Δx/d and Δy/d = 0.46. This is because the acoustic wavelength becomes longer than that in the upstream region due to the Doppler effects. In the whole sound region, more than 20 grid points are used per one acoustic wavelength of the tonal sound at the frequency of the vortex shedding, and the acoustic waves are sufficiently captured.

After many preliminary tests, grid- and domain-size independence has been established for the solutions presented in this chapter.

### 2.3. Hybrid simulation

αfφbi�1 þ φbi þ αfφbiþ1 ¼ X

2.2.2. Computational grids and boundary conditions

330 Numerical Simulations in Engineering and Science

d ≤ 500.0, �500.0 ≤ y/d < �70.0, 70.0 < y/d ≤ 500.0].

Figure 2. Computational domain and boundary conditions for direct simulations.

Buffer region

Non-reflecting

same as the values used by Gaitonde and Visbal [16], and the parameter αf is 0.47.

5

an

2 φiþn þ φi�n

� �, (4)

n¼0

where φ is a conservative quantity and φb is the filtered quantity. The coefficients an are the

Figure 2 shows the computational domain and boundary conditions. The coordinates originate from the center of the cylinder. Generally, the nonreflecting boundary conditions based on the characteristic wave relations [17–19] are used at the inflow, upper, and outflow boundaries along with a buffer region. The role of the buffer region is similar to that of the "sponge region" of Colonius et al. [20]. At the wall, the nonslip and adiabatic boundary conditions are used.

For all the cases of M = 0.2–0.6, the same grids are used. The computational domain is divided into three regions of different grid spacings as shown in Figure 2: a vortex region [�4.0 ≤ x/d ≤ 30.0, �4.0 ≤ y/d ≤ 4.0], a sound region [�70.0 ≤ x/d < �4.0, 30.0 < x/d ≤ 70.0, �70.0 ≤ y/d < �4.0, 4.0 < y/d ≤ 70.0], and a buffer region [�500.0 ≤ x/d < �70.0, 70.0 < x/

The spacing in the vortex region is prescribed to be fine enough to analyze the separated shear layer and the vortical structures in the wake of the cylinder. Figure 3 shows the computational grid near the cylinder. The spacing adjacent to the cylinder surface is Δxmin/d and Δymin/ d = 0.0025. With this grid distribution, the number of grid points within the separated shear layer for Re = 150 is 22 in the x, y direction (the thickness of the separated shear layer was estimated by δ/d ~ 1/Re0.5 and 0.08 for Re = 150 like the circular cylinder [6]), and the separated shear layer can be sufficiently captured. In the whole vortex region, Δx/d and Δy/d are less than 0.2, where the

500

70

4

*y*/*D*

500

70

30

Non-slip, adiabatic wall

*x*/*D*

Vortex region

Sound region

### 2.3.1. Governing equations and discretization formulation

The two-dimensional Lighthill's equation [Eqs. (1) and (2)] is solved based on the wave equation. Here, the open-source software, FrontFlow/blue-ACOUSTICS, was used. Here, the acoustic simulations are performed in a frequency domain using finite-element methods. A component perturbed at the frequency f of quantify gf can be written as:

$$\mathbf{g}\_f = \tilde{\mathbf{g}}\_f(\mathbf{x}) \mathbf{e}^{i2\pi ft}.\tag{5}$$

r0=d ¼ 80:0, L=d ¼ 20, (10)

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Figure 4 shows the computational grid for the acoustic simulations. The spacing adjacent to the cylinder surface is Δxmin/d and Δymin/d = 0.1. In the whole domain, the grid spacing is less than 0.52, and more than 20 grid points are used per acoustic wavelength. The preliminary computations confirmed that the acoustic waves are sufficiently analyzed with these grid resolutions. The reflecting conditions are adopted on the cylinder wall. On the other boundaries, the

Figure 5 shows the Strouhal number of vortex shedding predicted by the present direct simulations. The Strouhal number St is the frequency nondimensionalized by the freestream velocity U0 and the side length of the cylinder d. The present results are compared with the results of the past incompressible simulation (St = 0.155) [13] and those of the past experiment (St = 0.162) [14] for the same Reynolds number. The flow condition of the experiment is approximately incompressible. The present Strouhal numbers for all the Mach numbers are slightly lower than those in past results. The present computational results show that the Strouhal number becomes lower as the freestream Mach number becomes higher. This is

where r is the distance from the center of the cylinder.

2.3.2. Computational grids and boundary conditions

nonreflecting boundary conditions are adopted.

3. Validation of computational methods

Figure 5. Effects of Mach number on frequency of vortex shedding.

3.1. Validation of direct simulations

Using Eq. (5), Lighthill's equation can be written as:

$$\frac{\partial^2 \tilde{\rho}\_f}{\partial \mathbf{x}\_i \partial \mathbf{x}\_j} + k^2 \tilde{\rho}\_f = -\frac{1}{a\_0^2} \frac{\partial^2 \tilde{T}\_{i\sharp f}}{\partial \mathbf{x}\_i \partial \mathbf{x}\_j} \,. \tag{6}$$

where k = 2πf/a0 is the wavenumber. The right-hand side of Eq. (6) is computed by the results of the direct simulation in the present chapter. Also, acoustic waves at the frequency of the vortex shedding are focused on. To minimize the spurious errors, the computed acoustic sources are reduced smoothly to zero near the outflow boundary of the acoustic simulation by using the filter. Figure 4 shows the computational domain for the acoustic simulations and the outer shape of computational domain is circular with the cylinder at its center, and the radius is 100D. The above-mentioned filter is defined as:

$$
\widehat{A} = A \times \mathbb{G}(r - r\_0),
\tag{7}
$$

$$A = \mathfrak{d}^2 \frac{\tilde{T} \ddot{\eta}\_{\prime} f}{\partial \text{xi} \ddot{\partial} \text{x} \dot{\jmath}^{\prime}} \, \tag{8}$$

$$G(r\_{\rm d}) = \begin{cases} \frac{1}{2} \left( 1 + \cos \frac{r\_{\rm d}}{L} \pi \right) (80.0 < r \le 100.0) \\\\ 1.0 & (r \le 80.0) \end{cases} \tag{9}$$

Figure 4. Computational grids and boundary conditions for acoustic simulations. (a) Overall grids (every fifth grid line is shown for clarity) and (b) grids near cylinder (every grid line is shown).

$$r\text{0/d} = 80.0, \text{L/d} = 20,\tag{10}$$

where r is the distance from the center of the cylinder.

### 2.3.2. Computational grids and boundary conditions

gf ¼ g~fð Þx ei2π ft: (5)

Ab ¼ A � G rð Þ � r0 , (7)

ð Þ 80:0 < r ≤ 100:0

∂xi∂xj , (8)

,

(9)

, (6)

Using Eq. (5), Lighthill's equation can be written as:

332 Numerical Simulations in Engineering and Science

100D. The above-mentioned filter is defined as:

G rð Þ¼ d

shown for clarity) and (b) grids near cylinder (every grid line is shown).

1 2

8 >><

>>:

∂2ρ~f ∂xi∂xj

þ k 2 ρ~f ¼ � 1 a2 0

where k = 2πf/a0 is the wavenumber. The right-hand side of Eq. (6) is computed by the results of the direct simulation in the present chapter. Also, acoustic waves at the frequency of the vortex shedding are focused on. To minimize the spurious errors, the computed acoustic sources are reduced smoothly to zero near the outflow boundary of the acoustic simulation by using the filter. Figure 4 shows the computational domain for the acoustic simulations and the outer shape of computational domain is circular with the cylinder at its center, and the radius is

> A ¼ ∂2 Tij, f ~

rd L π � �

Figure 4. Computational grids and boundary conditions for acoustic simulations. (a) Overall grids (every fifth grid line is

1:0 ð Þ r ≤ 80:0

1 þ cos

∂2T~ij,f ∂xi∂xj

Figure 4 shows the computational grid for the acoustic simulations. The spacing adjacent to the cylinder surface is Δxmin/d and Δymin/d = 0.1. In the whole domain, the grid spacing is less than 0.52, and more than 20 grid points are used per acoustic wavelength. The preliminary computations confirmed that the acoustic waves are sufficiently analyzed with these grid resolutions.

The reflecting conditions are adopted on the cylinder wall. On the other boundaries, the nonreflecting boundary conditions are adopted.


**A. Appendices and nomenclature**

#### **A.1. Experimental procedures**

Patients and specimens: Samples of peripheral blood and epithelial tissue were obtained from 55 patients who were diagnosed with CIN2-3 (including cancer *in situ*) or microinvasive carcinoma (FIGO stage IA1) and underwent surgery in Oncological Dispensary of the Republic of Karelia. CIN and cervical cancer diagnosis was based on comprehensive physical examination, extended colposcopy findings, cytology, and histopathology tests, in full compliance with the approved standards for the diagnosis and treatment of patients with gynecological malignancies. All women engaged in this this study were informed and gave voluntary written consent. The research was approved by the Committee on Medical Ethics of Petrozavodsk State University and the Ministry of Healthcare and Social Development of the Republic of Karelia, and was done in accordance with the Declaration of Helsinki and good clinical practice guidelines. All women from patient group were positive for oncogenic HPV types (with the prevalence of HPV16 > 80%). Thirty healthy non-pregnant women without cervical abnormalities and HPV-infection at the time of blood sampling served as normal controls. Venous blood was collected immediately before the surgery or any other treatment and immediately processed for multicolor flow cytometry. Tissue samples were submerged in RNA stabilizing reagent right after excision and stored at −80.

**Author details**

Olga Kurmyshkina1

Federation

Federation

**References**

, Pavel Kovchur2

Petrozavodsk State University, Petrozavodsk, Russian Federation

\*Address all correspondence to<EMAIL_ADDRESS>
, Ludmila Schegoleva3

Immune Regulatory Network in Cervical Cancer Development: The Expanding Role of Innate...

1 Laboratory of Molecular Genetics of Innate Immunity, Institute of High-Tech Biomedicine,

2 Department of Hospital Surgery, ENT Diseases, Ophthalmology, Dentistry, Oncology, Urology, Institute of Medicine, Petrozavodsk State University, Petrozavodsk, Russian

3 Department of Applied Mathematics and Cybernetics, Institute of Mathematics and Information Technologies, Petrozavodsk State University, Petrozavodsk, Russian

of Medicine, Petrozavodsk State University, Petrozavodsk, Russian Federation

Open Biology. 2017;**7**(4):170006. DOI: 10.1098/rsob.170006

therapy. Virus. 2017;**9**(9):E254. DOI: 10.3390/v9090254

Pathology. 2016;**238**(2):166-179. DOI: 10.1002/path.4656

Virus. 2017;**9**(10):E293. DOI: 10.3390/v9100293

82. DOI: 10.1177/2051013617717914

fimmu.2017.00689

4 Department of Biomedical Chemistry, Immunology and Laboratory Diagnostics, Institute

5 Institute of High-Tech Biomedicine, Petrozavodsk State University, Petrozavodsk, Russia

[1] Calì B, Molon B, Viola A. Tuning cancer fate: The unremitting role of host immunity.

[2] Smola S. Immunopathogenesis of HPV-associated cancers and prospects for immuno-

[3] Alizon S, Murall CL, Bravo IG. Why human papillomavirus acute infections matter.

[4] Seelige R, Searles S, Bui JD. Innate sensing of cancer's non-immunologic hallmarks.

[5] Doorbar J. Model systems of human papillomavirus-associated disease. The Journal of

[6] Smola S, Trimble C, Stern PL. Human papillomavirus-driven immune deviation: Challenge and novel opportunity for immunotherapy. Therapeutic Advances in Vaccines. 2017;**5**(3):69-

[7] Qin Y, Ekmekcioglu S, Forget MA, Szekvolgyi L, Hwu P, Grimm EA, Jazaeri AA, Roszik J. Cervical cancer neoantigen landscape and immune activity is associated with human papillomavirus master regulators. Frontiers in Immunology. 2017;**8**:689. DOI: 10.3389/

Current Opinion in Immunology. 2017;**50**:1-8. DOI: 10.1016/j.coi.2017.09.005

and Tatyana Volkova4,5\*

http://dx.doi.org/10.5772/intechopen.72518

113

Flow cytometry: The following fluorophore-conjugated monoclonal antibodies were used: CD3-APC (Clone: UCHT1), CD4-FITC (Clone: MT310), CD8-FITC (Clone: DK25), CD16-FITC (Clone: DJ130c), CD56-RPE (Clone: C5.9) (Dako, Austria), CD25-APC (Clone: 4E3), CD45- VioBlue (Clone: 5B1), CD127-RPE (Clone: MB15-18C9), FoxP3-RPE (Clone: 3G3) (Miltenyi Biotec, Germany), STING/TMEM173-RPE (Clone: 723505, R&D Systems, USA). For blocking of non-specific antibody binding, FcR Blocking Reagent (Miltenyi Biotec) was used. For intracellular detection, cells were fixed and permeabilized using "FoxP3 Staining Buffer Set" (Miltenyi Biotec). Cells were acquired on a MACSQuant Analyzer flow cytometer (Miltenyi Biotec) and analyzed using MACSQuantify software.

Real-time PCR: Total RNA was extracted from tissue samples or ficoll-isolated PBMC with Trizol Reagent (Invitrogen). cDNA was synthesized from DNAse I-treated RNA (1 mg RNA per 1 reaction volume) using ProtoScript II (New England BioLabs, UK) or RevertAid First Strand cDNA Synthesis Kit (Fermentas, ThermoScientific, USA). Amplification was performed in StepOnePlus thermal cycler (Applied Biosystems, USA) using qPCRmix-HS-SYBR+HighROX reaction mix (Evrogen, Russia).

Statistical analysis: Data analysis was performed using R software. Mann-Whitney U-test was used to evaluate the differences between the patient and the control groups; the difference was considered to be statistically significant at p < 0.05.


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**20**

*Russian Federation*

**Gene Therapy of Hematopoietic and Immune**

Hematopoietic stem cells (HSCs) present arguably the best entry point for gene therapy of hematopoietic and immune systems since genetically modified HSCs are long-lived and would eventually transfer the therapeutic constructs to all their descendants. However, gene therapy via HSCs, although conceptually simple, has proven to be a technically formidable problem that has yet to be solved successfully. Despite overtly positive results obtained in gene therapy experiments performed with mouse and larger animal models, these achievements did not translate into clinically acceptable outcomes for non-human primates and human patients, with exception of a few specific disease instances where a therapeutic gene brought about significant survival advantages to transduced cells (Cavazzana-Calvo et al., 2000, Schmidt et al, 2003). Major differences between outcomes of conceptually similar experiments in mice and primates underscore the notion that the fundamental principles governing functioning of hematopoietic system in small short-lived vs. larger long-lived animals differ significantly. Low degree of chimerism obtained in experiments with primates and humans is likely a result of intrinsically low efficiency of viral transduction of long-term repopulating (LTR) HSCs coupled with subsequent massive silencing of integrated constructs (Ellis, 2005; Horn et al, 2002). One may hypothesize that this situation reflects a better protection of hematopoietic system from external

influences, in particular invasion of foreign genetic material, in longer-living animals.

of the efficient gene therapy via HSCs; some of these strategies are discussed below.

**2. Improvements of vectors and ex vivo HSC transduction protocols**

However, our deepening knowledge of molecular mechanisms underlying functioning of HSCs within the organism provides hints as to what strategies may lead to the development

Numerous studies indicate that lentiviral vectors that are capable of transducing nondividing cells may represent a more promising tool for introduction of genetic material into HSCs compared to retroviral vectors (Uchida et al, 1998, Case et al., 1999). This may be attributed to a largely quiescent nature of LTR HSCs, especially in larger animals (Cheshier et al., 1999, Shepherd et al., 2007). Since even lentiviral vectors transduce more efficiently dividing cells than quiescent ones (Trobridge et al., 2004), the current transduction protocols relied until recently on the use of culture conditions that induced entry of HSCs into cell

**1. Introduction**

**Systems: Current State and Perspectives**

Maria Savvateeva1, Fedor Rozov1,2 and Alexander Belyavsky1 *1Engelhardt Institute of Molecular Biology, Russian Academy of Sciences*

*2University of Oslo, Centre for Medical Studies Russia, Moscow*


**5.3 The procurement process**

The question of where the needed materials, components or services should be purchased – that is the assignment of suppliers – is the starting point for the procurement process (Cuber & Schmidt, 2012). While some suppliers might be known for instance due to already existing business relationships, others still need to be found and chosen. Thus, the search for suppliers is the next task within the procurement process, if an appropriate supplier of a certain material, component or service is in fact unknown. Hence, this task basically serves the purpose of identifying potential suppliers. To determine whether a supplier is generally capable of providing the required materials, parts or services, a corresponding exchange of specification information is necessary at this point. This interaction between the producer and potential suppliers is represented by a producer-supplier-interface in the course of the inter-company order execution (cf. KL4 in Fig. 14).

The suppliers are asked – in form of bid requests - to submit a respective proposal. That means intent information as well as consent information are exchanged. After the suppliers´ bids have been received, those are assessed according to company-specific criteria such as lowest price or earliest date of delivery. If it turns out in the following, that the created order plans do not comply with the overall project requirements, the created plans will have to be adjusted and the described activities need to – at least partially – be executed again. If the requirement of the producer is satisfied by the request of the supplier, the bid is classified as realizable and the respective supplier is assigned. Within the following task of order-approval, the producer first of all dispatches the orders to the involved suppliers. The corresponding exchange of consent information leads to the

Configuration Logic of Standard Business

2012).

Processes for Inter-Company Order Management 665

necessitates a regular exchange of monitoring information in the course of ordermonitoring, which is represented by a further producer-supplier-interface (cf. KL7 in Fig. 15). Another important task within the process of monitoring & controlling is the Entry of Change Requests. Those changes mainly refer to specification- or schedule-related aspects. During the following clarification of Change Requests, the feasibility of the requested changes is assessed together with the customer in due consideration of the current project situation. Since unexpected events such as the mentioned changes or delays due to malfunctions or labor slacks are naturally unpredictable, the primarily set project plans have to be adjusted continuously according to the information created in the course of the monitoring of progress and the clarification of Change Requests. That is in fact the main content of the project coordination. Upon the coordination of the project plans, it is subject to the project coordination to anticipate the occurred changes, as well as to compensate and counter their effects. In order to still realize the guaranteed delivery dates, the modified project schedules and schemes have to be forwarded to the respectively affected in-house departments or suppliers, where the detailed plans should be adjusted accordingly. If the delivery date is no longer realizable, the process-activity of project planning and order coordination of the project planning process has to be carried out again (Cuber & Schmidt,

Fig. 15. Detailed structure of the monitoring and controlling process (Schmidt, 2008)

The product/service-type-related sequence of order-handling-processes is in combination with the different product/service-types as well as the different business-relationship types

**6. Information requirements in the coordination points**

producer-supplier-interface KL5 in the course of the inter-company order execution (cf. Fig. 14). Each order is eventually monitored and controlled in the course of the order monitoring & controlling, during which monitoring & controlling information have to be exchanged (cf. KL6 in Fig. 14).

Fig. 14. Detailed structure of the procurement process (Schmidt, 2008)