**2. Methodology**

### *2.1. Data Acquisition*

The teleconsultations that had previously been classified that were used as the basis for training the algorithm are those which were acquired in the study by a previous study (López) (Table 1). They are part of the health records of the *Gerència Territorial de la Catalunya Central* of the *Institut Català de la Salut* covering the period from when the tool was first used until the date of its extraction for analysis purposes (8 April 2016 to 18 August 2018). Message deidentification was performed by substituting all possible names contained in the Statistical Institute of Catalonia database [13] with a common token and removing all other personal attributes. The classification method used for the conversations is

described and justified by López et al. 2019: Every healthcare professional who received an eConsulta labelled it according to whether, in their opinion, it avoided the need for a face-to-face consultation, led to an increased demand and by type of teleconsultation (Appendix A.1). These results of this annotation, with the corresponding messages, were used to train the text classification model using the three variables previously mentioned (Table 2).

**Table 1.** Data recorded by the teleconsulting system.

Most of the data were received with a tabular arrangement, and the texts and their labels were in different files that were merged according to the Conversation ID. The data cleaning was a multi-step process. Regarding the text: First, all the tokens of anonymized names were changed to a standard name of the country "Juan". The title was merged with the body of the message, adding the token "xxti" before the title and "tixx" after the title; that way we would not lose the information that this was the title. The texts were all converted to lowercase, and we extracted the length (in words and in characters) of every message to use as extra independent variables. As additional variables, the day of the month and time of the day were extracted from the date of the message.

#### *2.2. Vector Representation of Text in eConsulta Messages*

The emails needed to be represented in some way in order to use them as input for the models. A common practice in machine learning is the vector representation of words. These vectors capture hidden information about the language, such as word analogies and semantics, and improve the performance of text classifiers.

Four techniques have been used to generate the vector representation of texts. The Bag of Words (BoW) approach counts the number of times pairs of words appear in each document. The document is represented as a vector of a finite vocabulary. The Term Frequency–Inverse Document Frequency (TF–IDF) method assigns paired words a weight depending on the number of times they appear in a particular document (the Term Frequency), while discounting its frequency in other documents (Inverse Document Frequency): The more documents a word appears in, the less valuable that word is as a signal to differentiate any given document. Word2Vec is a two-layered neuronal network that trains and processes text. Its input is a corpus of text and its output is a set of vectors for the words in the corpus, with words represented by numbers. The initial vector assigned to a word cannot be used to accurately predict its context, meaning its components must be adjusted (trained) through the contexts in which they are found. In this way, repeating the process for each word, word vectors with similar contexts end up in nearby vector spaces. Fasttext [14] is used to obtain word2vec vectors. Finally, the objective of Doc2vec is to create a numerical representation of a document, regardless of its length. This approach represents each document by a dense vector, which learns to predict the words in the document [15]. In all cases, before carrying out the vectorization of the texts, these were first tokenized and any stop-words eliminated (those which are taken to have no meaning in their own right, such as articles, pronouns or prepositions).

In each instance, the vectors were enriched by supplementing them with similar texts in Catalan and Spanish [16]. The external data used to enrich the corpus were models of interactions extracted from online databases with colloquial language similar to that used in eConsulta. Where augmented BOW, TF-IDF and Word2Vec were used, word and character length and word density were also used as predictor variables.

#### *2.3. Training and Testing AI Algorithms*

The task addressed in this study is a multiclass classification with respect to the type of visit and two binary classifications for the other two variables (avoiding visit and increased demand). For each text vector representation algorithm five di fferent algorithms were implemented: Random Forest, Gradient Boosting (lightGBM), Fasttext, Multinomial Naive Bayes and Naive Bayes Complement [17]. Bayesian text classifiers are the most standard algorithms in this setting. A convolutional neural network was also used using the augmented Word2vec vectors. We tested the performance of the algorithms through a stratified 10-fold cross-validation: During 10 iterations/trainings, 9 divisions served as learning and 1 as a test.

The coe fficients of interest to evaluate the goodness of the algorithms were precision (the fraction of relevant instances between the retrieved instances/proportion of correct predictions of the total of all predicted cases) and sensitivity (the number of correct classifications for the positive class "true positive"). It was decided not to use the "accuracy" coe fficient since it is a metric that, given an unbalanced dataset like the one under investigation, can result in a very high score in spite of the fact that the classifier works poorly, since it assesses the number of total hits without taking into account whether most of the data is of the same class. The F value is used to determine a weighted single value of accuracy and completeness. The diagnostic value is assessed by means of the ROC curve. The goodness-of-fit of all the coe fficients is represented as a value between 0 and 1.

Python 3.7 and the following libraries were used for the algorithm training: numpy [18], matplotlib [19], seaborn [20], altair [21], scikit-learn [22], pandas [23], gensim [24], nltk [25], fasttext [14], pytorch [26] and lightGBM [27]. The majority of the code was carried out on Jupyter Notebooks [28].

### *2.4. Ethical Considerations*

The study was approved by the Ethical Committee for Clinical Research at the Foundation University Institute for Primary Health Care Research Jordi Gol and Gurina, registration number P19/096-P, and carried out in accordance with the Declaration of Helsinki [29].


**4. The impact of the siRNA structure on the efficiency of RNAi**

204 Practical Applications in Biomedical Engineering

2) "-" data is not available.

Thermostability

Thermoasymmetry

Nuclease resistance

Duration of circulation in the bloodstream

Cellular uptake

Target cellular uptake

Specificity of action

**Table 2.** Extensive and selective modification of siRNA

1) Bold letters – deoxyribonucleotides, underlined letters – 2'-O-Me, italics – 2'-F-analogs, B\_ – 5'-5'-, \_B – 3'-3'-inverted

**siRNA property The role of chemical modification Examples of modifications**

2'-О-Ме, 2'-F, 2'-F-ANA, 2'- O-MOE, 2'-O-DNP, 4'-S, LNA, ENA et al.

UNA, LNA, nucleobase modifications

Virtually all modifications

Chol, 2'-O-DNP, folate

> Peptides, antibodies, aptamers

1) see above; 2) UNA, 2'-O-Me, deoxyribonucleotides 3) 2'-O-Me 4) 2'-O-Me

To increase the thermostability of siRNA by providing the optimal conformation of nucleotides for base pairing65, 99, 120.

To increase the thermoasymmetry of the duplex by the decrease of thermostability at the 3'-flank of the sense strand or/and the increase of the thermostability at the 5'-flank of the sense strand of the duplex 99, 105, 107, 120.

To increase the duplex nuclease resistance by introduction of the chemically modified analogs of nucleotides in its structure153,76.

To increase siRNA affinity to serum proteins and the

To provide the effective mechanisms of siRNA penetration: receptor-mediating endocytosis, diffusion via cellular membrane or other ways (if the mechanism is unknown)153, 86, 126.

To increase the specificity of uptake by the attachment of the molecules with high binding affinity to surface of the cells of particular organs and tissues154.

To increase the specificity of the silencing by: 1) the increase of duplex thermoasymmetry99, 105, 107, 120; 2) alteration of binding affinity of the antisense strand of siRNA to mRNA-target155, 99, 82; 3) the absence of receptors providing the activation of immune response 64; 4) blocking the phosphorylation of the 5'- OH group of the sense strand of siRNA 123.

**Table 3.** Influence of the chemical modifications on siRNA properties

time of circulation 57, 65. PS, 4'-S, Сhol

deoxyribose, underlined bold letters – LNA-analogs, s – phosphorothioate bond between nucleotides.

The investigation of the structures of natural siRNAs formed by dsRNA processing with Dicer and endogenous miRNA revealed the common siRNA structures. "Classical" small interfering RNA resembles duplexes 18 - 23 bp in length [18, 22, 156, 157] with 2 nt overhangs at 3'-ends [40, 45] (fig. 9).

However, it was clearly demonstrated, that the silencing activity of structurally similar duplexes with different sequences varies significantly. As it was mentioned above thermodynamic asymmetry of the duplex and to a lesser extend the structure of mRNA target determines the siRNA activity [44, 45, 57, 58, 60]. Possibility to optimize the duplex structure was demonstrated in a number of publications. Introduction of nucleotide substitutions in siRNA, resulting in a formation of non-canonical base pairs or mismatches [38, 158, 159] is a perspective approach for the optimization of the thermodynamic properties of the duplex. The other approach utilize the inactivation of the sense strand of siRNA (for example, segmentation) to guarantee the incorporation of the antisense strand into activated RISC\* independent from the thermodynamic properties of the duplex [99]. The silencing activity of siRNA can be increased by the lengthening of the duplex and converting siRNA into Dicer substrate DsiRNA [160, 161] or by the modifications of the overhands affecting duplex thermodynamic asymmetry [162]. Single stranded analogs of siRNA can be also used as inducers of RNAi, in this case the problem of the strand selection does not exist [40, 77]. All mentioned approaches will be described in details below.

**Figure 9.** Structural repertoire of siRNA. The triangle indicates single stranded nick.

#### **4.1. The influence of nucleotide substitutions on the silencing activity of siRNA**

Structure - Functions Relations in Small Interfering RNAs 207

**Reference**

158

159

74

166

165

**%**

98 94.5 99.5 99.8 99.8 99.6 99

67.5 79.5

> 79 92

77.5 84.5

82.5 89.5

> 86 72 95

> 92 89 20

> 0 50 0

**Substitutions 2,3) Silencing efficiency,**

**Target, model system Type of**

*P.luciferase*, **(+2/+ 23)**,

Hela cells

*P.luciferase*, **(+21/+ 43),**

Hela cells

*Lamin A/C* **, (+829/+ 851),**  Hela cells

*Lamin A/C***, (+608/+ 630),**  Hela cells

*Dnm T1***, (+70/+ 89),** Hela cells

*Dnm T1***, (+185/+ 203),** Hela cells

Hela cells

Hela cells

*F.luciferase***,**

NIH3T3 cells

*MGC29643,*  **(+576/+596)**  Неla cells

*GPR39, (MGC29643*  **(+576/+596)а)** Неla cells

*Jagged-1,*  **(+3382/+3402)**

plasmid, transfected into НЕК 293Т cells

*R.luciferase/P.luciferase* **с ,**

plasmid, transfected into

*R.luciferase/ P.luciferase* **a,** plasmid, transfected into

plasmid, transfected into

plasmid, transfected into

plasmid, transfected into

**siRNA 1)**

1

*- G9 → C9 G6,9 → C6,9 G6,9,13 → C6,9,13 G3,6,9,13,17 → C3,6,9,13,17*

*C8 → G8*  A12 → U12 *C8,* A12 → *G8,* U12

C12 → G12 *A8 → U8 A8,* C12 → *U8,* G12

*C18 → U18*

*C5 A12C15 → U5G12U15*

*C18A→ A18U C1G → U1U*

A18C → U18U, A12→U12

C18A → U18U, U12→A12

G18A → U18U, G12→U12

U18U → A18A, G12→U12

2

1

2

1 2

1 2

1 2

1 2

1

2

1

2

1

1 -

1 -

1 -

 **4**)

Thermodynamic properties of siRNA play a key role on the stages of RISC activation and mRNA target cleavage, determining the efficiency of strand dissociation, strand selection and mRNA cleavage. Since that, nucleotide substitutions affecting thermodynamic stability of the duplex could change the silencing activity of siRNA. The nature of the changes depends on the type of substitutions and the location of the substitutions in siRNA structure. The data on the impact of nucleotide substitutions in the silencing activities of siRNAs reported in the literature are summarized in Table 4.

The kinetics of mRNA cleavage directed by anti-*F.luciferase and anti*-*sod1* siRNA, containing nucleotide substitutions in one of the strands of the duplex were exanimated in details in [38]. It was shown, that the substitution of cytosine with uracil at the 5'-end of the sense strand of anti-*F.luciferase* siRNA, resulting in U:G pair formation (stabilized by two hydrogen bonds)[163]), reduced the target mRNA cleavage rate. At the same time, the rate of the antisense RNA (complementary to the first target) cleavage increased substantially. The analysis of the binding of siRNA strands with RISC\* revealed, that single nucleotide substitution at the position 1 of the sense strand reduce the incorporation of the antisense strand in the complex, whereas the efficiency of the sense strand incorporation into RISC\* increased (fig. 10 A).

Nucleotide substitution at the 3'-end of the sense strand of anti-*sod1* siRNA resulting in the formation of А:G mismatch (fig. 10 B), caused the opposite effect: the rate of mRNA cleavage increased, while the rate of antisense mRNA cleavage decreased. This result indicates that the efficiency of the sense strand incorporation into RISC\* decreases. The observed effect could be caused both by preferential incorporation of the antisense strand into RISC complex, and by non-perfect complementarity between the sense strand of siRNA and its target (antisense mRNA), but the results of the additional experiments with the substitution of G by C at the 5'-end of the antisense strand (fig. 10 B) verified the key role of preferential RISC loading [38]. Thus, it was clearly demonstrated, that single nucleotide substitutions at the flank regions of siRNA could change the thermodynamic asymmetry and to determine the preferential incorporation of one strand into RISC\*: destabilization of the duplex at the 3'-end of the sense strand increase the activity of siRNA , the destabilization of the opposite end of the duplex, reduce the silencing activity [38].

**Figure 10.** The scheme of the experiment described in 38. **А.** Substitution at the 5'-end of the sense strand of anti-*F.luciferase* siРНК. **B.** Substitution at the 3'-end of the sense strand (left) or at the 5'-end of the antisense strand (right) of anti-*sod1* siRNA.

increased (fig. 10 A).

siRNAs reported in the literature are summarized in Table 4.

**4.1. The influence of nucleotide substitutions on the silencing activity of siRNA**

Thermodynamic properties of siRNA play a key role on the stages of RISC activation and mRNA target cleavage, determining the efficiency of strand dissociation, strand selection and mRNA cleavage. Since that, nucleotide substitutions affecting thermodynamic stability of the duplex could change the silencing activity of siRNA. The nature of the changes depends on the type of substitutions and the location of the substitutions in siRNA structure. The data on the impact of nucleotide substitutions in the silencing activities of

The kinetics of mRNA cleavage directed by anti-*F.luciferase and anti*-*sod1* siRNA, containing nucleotide substitutions in one of the strands of the duplex were exanimated in details in [38]. It was shown, that the substitution of cytosine with uracil at the 5'-end of the sense strand of anti-*F.luciferase* siRNA, resulting in U:G pair formation (stabilized by two hydrogen bonds)[163]), reduced the target mRNA cleavage rate. At the same time, the rate of the antisense RNA (complementary to the first target) cleavage increased substantially. The analysis of the binding of siRNA strands with RISC\* revealed, that single nucleotide substitution at the position 1 of the sense strand reduce the incorporation of the antisense strand in the complex, whereas the efficiency of the sense strand incorporation into RISC\*

Nucleotide substitution at the 3'-end of the sense strand of anti-*sod1* siRNA resulting in the formation of А:G mismatch (fig. 10 B), caused the opposite effect: the rate of mRNA cleavage increased, while the rate of antisense mRNA cleavage decreased. This result indicates that the efficiency of the sense strand incorporation into RISC\* decreases. The observed effect could be caused both by preferential incorporation of the antisense strand into RISC complex, and by non-perfect complementarity between the sense strand of siRNA and its target (antisense mRNA), but the results of the additional experiments with the substitution of G by C at the 5'-end of the antisense strand (fig. 10 B) verified the key role of preferential RISC loading [38]. Thus, it was clearly demonstrated, that single nucleotide substitutions at the flank regions of siRNA could change the thermodynamic asymmetry and to determine the preferential incorporation of one strand into RISC\*: destabilization of the duplex at the 3'-end of the sense strand increase the activity of siRNA , the

destabilization of the opposite end of the duplex, reduce the silencing activity [38].

**Figure 10.** The scheme of the experiment described in 38. **А.** Substitution at the 5'-end of the sense strand of anti-*F.luciferase* siРНК. **B.** Substitution at the 3'-end of the sense strand (left) or at the 5'-end of

the antisense strand (right) of anti-*sod1* siRNA.

Structure - Functions Relations in Small Interfering RNAs 209

The elevation of the thermodynamic asymmetry by single nucleotide substitution at the 1th position of the antisense strand was reported to increase or have no influence on the silencing activity of different siRNAs, targeted to *sod1 / F.luciferase* mRNA or the complementary sequence (antisense mRNA) [164] (Table 4). In turn, the equal efficiency of the cleavage of *htt* mRNA and *htt* antisense mRNA by thermodynamically symmetrical siRNA suggests the

Introduction of the nucleotide substitutions at the 3'-end of the sense strand of siRNA duplex resulted in the formation of the mismatches, has led to the creation of the structurally new class of small interfering RNAs – fork-like siRNAs (fsiRNAs) [158]. More effective silencing of the expression of *R.luciferase/P.luciferase* gene by fsiRNAs then by classical siRNA targeted to the same sequences was demonstrated in Hela cells (Table 4). The most pronounced augmentation of the activity was observed for siRNA with initially moderate activity [158]. Fork-like siRNA with two nucleotide substitutions at the 3'-end of the sense strand was found to be the most active [11, 158, 159] (Table 4). Introduction of from 2 to 4 nucleotide substitutions at the 3'-end of the sense strand of siRNA targeted *sod1*

The increase of the thermodynamic asymmetry of the duplex by the introduction of the mismatches at the ends of the strands cannot guarantee the positive influence on the activity. It is known, that the region of the "guide" strand spanning from 2 to 6 position determines the efficiency of the interaction of siRNA with Ago2 [21, 30, 31]; this fact limits the introduction of substitutions in this region. Nevertheless, С→U substitution in 2d position of the antisense strand of siRNA targeted *Jagged-1* mRNA increased the silencing effect from 0 to 50% in НЕК 293Т cells transfected with vector, containing cDNA fragment of the target gene [165] (Table 4). This data suggests, that the substitutions in the antisense strand resulted in the formation of non-canonical base pairs is more tolerable than the substitutions resulted in the formation of mismatches. In the other study, single nucleotide substitutions at 19th position of the sense strand or at the 1st position of the antisense strand resulting in the formation of the mismatches as well as non-canonical base-pairs reduced the activity of anti-*EGFP* siRNA in H1299 cells. It was assumed that the reduction of the efficiency of the interaction of TRBP (but not the Dicer) with siRNA was the possible reason

Introduction of nucleotide substitutions in the central part of siRNA duplex could be used for the destabilization the central region and the subsequent elevation of the silencing activity. Nevertheless, this type of structure modification could switch the mode of siRNA action to miRNA-like mechanism [167] (fig. 4). It was demonstrated in experiments on HeLa cells, that substitutions in 9th and 10th positions of the sense strand of siRNA leads to the 2 - 4.5-fold increase of IC50 as compared with IC50 for siRNA with classical duplex 36. Substitutions in the sense strand or in both strands of siRNA [167] reduced the efficiency of RNAi (Table 4).

Thus, the introduction of nucleotide substitutions could be successfully used for the design of siRNA characterized by favorable thermodynamic asymmetry and low thermostability of the central part of the duplex. This approach can be applied for the creation active siRNA

equal probability of sense or antisense strand incorporation into RISC\* [38].

and *htt* mRNAa correspondingly increased the efficiency of silencing [38].

of the observed effect [24] (Table 4).

1)

2) Numeration of the nucleotides from the 5'-end.

3) Substitutions in the sense strand are presented in normal letters; substitutions in the antisense strand are presented in *italic*.

4) *P.luciferase s* (а) – a gene or a fragment of gene encoded sense (s ) or antisense (a) RNA.

5) *АPPL(S)/luciferase –* recombinant gene, containing mutant London (L) or Swedish (S) type of *APP* allele.

b) Silencing activity of structurally modified siRNA is presented as the ration of IC50 (primary siRNA) / IC50 (modified siRNA), where IC50 is the concentration of siRNA, inducing –50 % silencing of the target gene.

**Table 4.** The influence of the nucleotide substitutions in siRNA on the efficiency of RNAi

The elevation of the thermodynamic asymmetry by single nucleotide substitution at the 1th position of the antisense strand was reported to increase or have no influence on the silencing activity of different siRNAs, targeted to *sod1 / F.luciferase* mRNA or the complementary sequence (antisense mRNA) [164] (Table 4). In turn, the equal efficiency of the cleavage of *htt* mRNA and *htt* antisense mRNA by thermodynamically symmetrical siRNA suggests the equal probability of sense or antisense strand incorporation into RISC\* [38].

208 Practical Applications in Biomedical Engineering

**siRNA 1)**

1 -

1 -

2 -

2 -

1 -

1 -

1 -

15'-NNNNNNNNNNNNNNNNNNNNN-3' 3'-NNNNNNNNNNNNNNNNNNNNN-5'

– a gene or a fragment of gene encoded sense (s

25'-NNNNNNNNNNNNNNNNNNN-3' 3'-NNNNNNNNNNNNNNNNNNNNN-5'

2) Numeration of the nucleotides from the 5'-end.

G1 → U1 C19 → A19 *G1 → U1 C19 → A19*

G1 → U1 C19 → A19 *G1 → U1 C19 → A19*

C18C → U18U

G18C → U18A

G19 → C19

G19 → A19 G19 → C19 G19 → U19 *C19 → A19 C19 → U19 C19 → G19*

C1 → A1 A19 → C19 A19 → G19 A19 → U19 G9 → A9 G9 → C9 G9 → U9 A10 → C10

other substitutions in the sense strand (2 – 8, 12 – 18 positions)

3) Substitutions in the sense strand are presented in normal letters; substitutions in the antisense strand are presented in

b) Silencing activity of structurally modified siRNA is presented as the ration of IC50 (primary siRNA) / IC50 (modified

5) *АPPL(S)/luciferase –* recombinant gene, containing mutant London (L) or Swedish (S) type of *APP* allele.

siRNA), where IC50 is the concentration of siRNA, inducing –50 % silencing of the target gene. **Table 4.** The influence of the nucleotide substitutions in siRNA on the efficiency of RNAi

Structure of siRNA Strand Length of the

) or antisense (a) RNA.

**Substitutions 2,3) Silencing efficiency,**

**%**

0 45

0 80

55 50

1 b**)** 0.3 1.15 1.2 1.25 4.5 3.3 2.15 2.3 0.2 – 1.3

sense antisense

sense antisense **Reference**

164

159

159

24

36

strand, nt

21 21

19 21

**Target, model system Type of**

**,**

*sod1/F.luciferase* **c**

*sod1/F.luciferase* **a,** plasmid, transfected into

*АPP(L)/luciferase* **5),** plasmid, transfected into

НЕК 293 cells

НЕК 293 cells

НЕК 293 cells

НЕК 293 cells

*EGFP, (+306/+324)*

H1299

*EGFP, (+396/+414)*

H1299

1)

*italic*. 4) *P.luciferase s* (а)

*F.luciferase*,

Неla SS6 cells

siRNA type

*АPP(S)/luciferase***,** plasmid, transfected into

human lung carcinoma

human lung carcinoma

plasmid, transfected into

plasmid, transfected into

Introduction of the nucleotide substitutions at the 3'-end of the sense strand of siRNA duplex resulted in the formation of the mismatches, has led to the creation of the structurally new class of small interfering RNAs – fork-like siRNAs (fsiRNAs) [158]. More effective silencing of the expression of *R.luciferase/P.luciferase* gene by fsiRNAs then by classical siRNA targeted to the same sequences was demonstrated in Hela cells (Table 4). The most pronounced augmentation of the activity was observed for siRNA with initially moderate activity [158]. Fork-like siRNA with two nucleotide substitutions at the 3'-end of the sense strand was found to be the most active [11, 158, 159] (Table 4). Introduction of from 2 to 4 nucleotide substitutions at the 3'-end of the sense strand of siRNA targeted *sod1*  and *htt* mRNAa correspondingly increased the efficiency of silencing [38].

The increase of the thermodynamic asymmetry of the duplex by the introduction of the mismatches at the ends of the strands cannot guarantee the positive influence on the activity. It is known, that the region of the "guide" strand spanning from 2 to 6 position determines the efficiency of the interaction of siRNA with Ago2 [21, 30, 31]; this fact limits the introduction of substitutions in this region. Nevertheless, С→U substitution in 2d position of the antisense strand of siRNA targeted *Jagged-1* mRNA increased the silencing effect from 0 to 50% in НЕК 293Т cells transfected with vector, containing cDNA fragment of the target gene [165] (Table 4). This data suggests, that the substitutions in the antisense strand resulted in the formation of non-canonical base pairs is more tolerable than the substitutions resulted in the formation of mismatches. In the other study, single nucleotide substitutions at 19th position of the sense strand or at the 1st position of the antisense strand resulting in the formation of the mismatches as well as non-canonical base-pairs reduced the activity of anti-*EGFP* siRNA in H1299 cells. It was assumed that the reduction of the efficiency of the interaction of TRBP (but not the Dicer) with siRNA was the possible reason of the observed effect [24] (Table 4).

Introduction of nucleotide substitutions in the central part of siRNA duplex could be used for the destabilization the central region and the subsequent elevation of the silencing activity. Nevertheless, this type of structure modification could switch the mode of siRNA action to miRNA-like mechanism [167] (fig. 4). It was demonstrated in experiments on HeLa cells, that substitutions in 9th and 10th positions of the sense strand of siRNA leads to the 2 - 4.5-fold increase of IC50 as compared with IC50 for siRNA with classical duplex 36. Substitutions in the sense strand or in both strands of siRNA [167] reduced the efficiency of RNAi (Table 4).

Thus, the introduction of nucleotide substitutions could be successfully used for the design of siRNA characterized by favorable thermodynamic asymmetry and low thermostability of the central part of the duplex. This approach can be applied for the creation active siRNA targeted to any desired sequence for silencing of mutated or chimerical genes. However, there is not enough data publish up to date for the formulation of the universal rules for the design of fork-like siRNA and siRNA with destabilized center, the activity of resulted siRNA cannot be predicted and should be determined experimentally.

Structure - Functions Relations in Small Interfering RNAs 211

homologous genes in *C.elegans* [170]. Later, it was assumed that the minor fraction of dsRNA in the preparations of ssRNA obtained by *in vitro* transcription was the agent that silence the expression of the target genes 1. However, the ability of antisense, but not sense ssRNA (22 – 40 nt) to induce gene silencing was experimentally verified in *C.elegans* [171]. It was demonstrated that mRNA degradation induced by ssRNA proceeds via RISC\* assembling (fig. 9) [131,122]. The evaluation of the silencing activity of anti-*luciferase* sssiRNA in HeLa cells demonstrated, that the required concentration of ss-siRNA was 8-fold higher, than the concentration of classical siRNA to reach the similar level of gene silencing. In the other report, it was shown, that the concentration of ss-siRNA essential for the RISC assembling was 10 – 100 higher than the concentration of double stranded siRNA analogous [122]. High sensitivity of single stranded RNA to ribonucleases [62], and less efficient interaction with the RNAi machinery proteins [131,122] were supposed to be the possible

Thus, the application of non-modified ss-siRNA as inhibitors of gene expression is not

During the search of the effective inductors of RNAi, able to silence target gene at low (nanomolar and lower) concentrations, it was found that dsRNAs 25-30 bp in length which are substrates of Dicer (here and after DsiRNA – Dicer-substrate siРНК), are significantly more active in comparison with "classic" or "conventional" siRNAs [161, 172, 173, 174]. To compare interfering activity of DsiRNA and conventional siRNA the duplexes of different length (21-30 bp) and structure (presence or absence of 3' or 5' dinucleotide overhangs) targeting *EGFP* were used [174]. The interfering activity of dsRNA was evaluated at concentration ranging from 50 pMol to 50 nMol using HEK293 cells transfected with the plasmid encoded EGFP. It was shown that at subnanomolar concentrations (50 *pM* – 200 *pM*) DsiRNAs were significantly more active than siRNA. Among duplexes tested the DsiRNA 27 bp in length with blunt ends displays the highest interfering activity: this DsiRNA (1 nM) inhibited expression of the target gene by 95% (Table 5) while corresponding siRNA was almost inactive [174]. It turned out, that this DsiRNA (27 bp, blunt ends) is processed by Dicer yielding pull of different siRNAs 21bp in length. Seven siRNAs (21 bp with 3'-dinucleotide overhangs) generated by single-nucleotide shift along the *EGFP* mRNA sequence homologous to DsiRNA were synthesized to answer the question can the synthetic siRNA be as active as this particular DsiRNA. It was shown that at the concentrations 50 pM and 200 pM neither each synthetic siRNA nor pull of synthetic siRNAs silence expression of EGFP as efficiently as corresponding DsiRNA. Interestingly, in the case if DsiRNA was processed by Dicer *in vitro* and then transfected into the cells the silencing efficiency of this processed DsiRNA was similar to the activity of synthetic siRNAs [174]. It has been suggested, than after DsiRNA cleavage Dicer did not dissociated from the complex with DsiRNA and thus governed the mode of interaction of R2D2 (*D*.*melanogaster*) or TRBP (*H.sapiens*) and, as a consequence, the unequivocal orientation of siRNA within the RISC. This provides for incorporation into the RISC the antisense strand of the duplex.

reasons of the lower efficiency of RNAi induction by ssRNA.

beneficial in comparison with double stranded siRNA.

**4.4. dsRNA (27-30-mers) as Dicer substrates**


**2. Materials and Methods**

All consecutive patients affected by ICC and undergoing surgery were considered. Inclusion criteria were (a) aged ≥18 years; (b) ICC size >50 mm; (c) preoperative PET-CT with evidence of tumour areas having a heterogeneous uptake. Exclusion criteria were: (a) diagnosis of mixed hepato-cholangiocarcinoma at the final pathology; (b) preoperative chemotherapy or any preoperative loco-regional treatment, including thermal ablation, chemoembolisation, or radioembolisation; (c) uncontrolled diabetes or any metabolic alteration preventing an accurate SUV evaluation. The standard preoperative imaging included thoracoabdominal CT and hepatic magnetic resonance imaging (MRI). A multidisciplinary team discussed the management of every patient. Informed consent was signed by all the participants. The local ethics committee approved the study (approval number: 146/20 on 20 February 2020).


2.5.2. The Self-Adaptive Differential Evolution (SADE) Algorithm

Differential evolution (*DE*) is a population-based search technique introduced by Storn and Price [53]. The technique is an outstanding tool used to handle stochastic global optimization problems, which requires tuning and varying a few parameters to get the optimized results. The governing parameters of *DE* depend significantly on the nature of the problem to be optimized. However, the optimization process, in which the controlling parameters are tuned using different strategies, is excessively time consuming, making the technique computationally expensive [54]. Qin and Suganthan [55] developed the self-adaptive differential evolution (*SADE*) technique to overcome this drawback. *SADE* is capable of self-adapting the controlling parameters in a much shorter time compared to *DE*. *SADE* is also superior to other optimization algorithms such as particle swarm optimization (PSO), especially for solving numerical problems with medium dimensions [56]. Detailed information on the workflow and the mathematical formulations used in this algorithm have been obtained by many researchers [54,55,57]. *SADE* has been successfully implemented in many application in the petroleum industry, such as oil production optimization [58] and prediction of spud mud rheology [59].


**1. Introduction**

The establishment and reevaluation of nutrient requirements in poultry is a dynamic process due to constant increases in feed consumption, growth rate, and the amount of dietary protein, and amino acid (AA) transformed into body protein in chicken meat over time, as a result of genetic selection programs [1–3]. The advancement of each of these factors necessitates the constant labor of AA to maintain high levels of productivity, especially when we consider that in modern animal production, new concepts such as sustainability in meat production are emerging, as a result of the constantly increasing societal demand for food production through environmentally friendly practices.

Decades ago, one of the responses to achieving high levels of efficiency in the transformation of feed into high-quality protein was the development of the concept of the ideal AA ratio, which seeks to maximize efficiency.

However, when comparing the AA profiles recommended by various sources, there is a significant difference between them. For example, among the main essential AA in poultry, arginine (Arg), methionine (Met), threonine (Thr), and tryptophan ratios of 94–120, 36–46, 58–73, and 14–20 have been proposed over time. One reason for these disparities is that these available AA ratios were proposed over 50 years, from 1965 to 2014 [3, 4]. During this time, significant advances in broiler growth have been made, as well as the development of other concepts such as the use of digestible AA ratios, in conjunction with a steady improvement in the nutritional quality of vegetable feedstuffs through selection, and an ever-increasing amount of new information on the composition and availability of nutrients in feed ingredients.

Another strategy, in addition to the use of ideal AA ratios, to improve broiler production efficiency is the use of low-CP diets supplemented with available feed-grade amino acids [3, 5, 6] to fulfill the AA requirements according to different recommendations [7, 8], ensuring the birds productivity at least at the same level shown by birds. Furthermore, using low-CP rations improves nitrogen efficiency by avoiding excess nitrogen excreted in the form of uric acid, reducing environmental pollution caused by nitrogen and ammonia emissions, and lowering the carbon footprint of feed manufacturing through changes in the type and amount of raw material included in the feeds.

While these feeding strategies are still being refined in terms of research and practical application, they must keep up with changes in broiler genetic potential. Furthermore, they must adjust to new nutritional concepts, such as the use of functional AA. Functional AAs are defined as AAs that participate and regulate key metabolic pathways that improve organism health, survival, growth, development, lactation, and reproduction [4, 9]. Functional AA's descriptive roles in nutrition and health, as well as the metabolic pathways involved, have been documented [4]. In recent years, there has been a large number of publications on this topic, as well as several outstanding reviews on the use of functional AA to improve the immune response and digestive capabilities in chickens, including the embryonic developmental stage and the growth stage on the farm [10–12]. According to a recent review [12], AA supplementation strategies can positively contribute to immune and gut health. In the present chapter, an attempt was made to analyze the available information on the use of Arg, Thr, and Met as functional AA aimed at establishing a pattern between the improvement in immune response and digestive physiology with improvements in broiler growth, estimate an AA requirement, and discuss the implications regarding the readjustment of feeds based on functional AA formulation and their application in broilers kept in commercial settings.


**2.1 Collection of plant materials and identification**

Plant species collected were organized as complete herbarium specimens and identified as outline by the rules of herbaria. Plant materials were identified

*\* Least cited plants.*

#### **Table 1.**

*Medicinal plant species collected from the survey area with their medicinal values.*

and authenticated by a plant taxonomist in person of Dr. Yusuf Nuhu, from the Department of Plant Biology, Bayero University Kano, Nigeria. All identified plants specimens were given vouchers number as outline in (**Table 1**).