Types of hydrogel-based products applied via different routes of drug administration [10, 59].
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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During pregnancy, the neuroendocrine system undergoes significant hormonal fluctuations determined by stimulatory and inhibitory inputs from the mother and fetus to maintain the internal environment (milieu). This process is regulated mainly by both the maternal brain and the placenta, acting through the maternal-placental-fetal unit (MPFU). It also serves as a protection system against stress and immune responses [1, 2].
Interestingly, the neuroendocrine responses generate a feedback circuit regulated by the placenta. This organ begins its development in days six-seven after conception. It has been considered a passive organ for many years, acting as a barrier between the mother and the fetus, provide nourishing and eliminate metabolism products such as urea, uric acid, and creatinine. However, the placenta is a neuroendocrine organ that can synthesize and release hormones, neuroactive factors, and other mediators, allowing the proper development of the fetus’s maternal tissues to ensure an optimal pregnancy, allowing the fetus to adapt and survive under conditions of stress, infections, hypoxia, and malnutrition [3, 4]. This neuroendocrine mechanism involves at least three different endocrine axes; the hypothalamus-pituitary-gonads axis (HPG), the hypothalamus-pituitary–adrenal gland axis (HPA), and the hypothalamus-pituitary-thyroid axis (HPT), to ensure optimal maternal-fetal development [1].
Specifically, the HPG axis, which is the central axis involved in regulating the reproductive function in vertebrates by a releasing pulsing of GnRH at the hypothalamus and placenta, has a decisive role in the different stages of pregnancy. In this sense, it plays a central role in regulating MPFU development through positive and negative regulation of sex hormones [1].
The GnRH is a hormone synthesized by the hypothalamic neurons. It travels through the portal-pituitary-system to bind to its receptors (GnRHR-I) in pituitary cells (gonadotrophs), activating the synthesis of FSH (Follicle-stimulating hormone) and LH (Luteinizing hormone). These hormones are released into the systemic circulation to act on sex organs regulating both oogenesis and spermatogenesis. Interestingly, GnRH isoforms (GnRH-I and GnRH-II) have also been identified in other tissues, including the testicles, prostate, mammary gland, endometrium, and placenta. In these organs, it has been shown that GnRH-II acts by binding to GnRHR-II receptors [5].
The functions associated with these isoforms are the production of the β-human chorionic gonadotropin (β-hCG) by the syncytiotrophoblast in the early stages of pregnancy. Here, β-hCG intervenes in at least two vital functions, avoiding luteolysis and ensuring Progesterone’s production (P4) until the placenta is implanted. Thus, specific conditions that interfere with this endocrine axis before weeks seven to nine of gestation would culminate in pregnancy loss [5].
Moreover, recent evidence indicates that GnRH is involved in the maternal-fetal environment’s remodeling (milieu) that allows the fetus’s correct implantation. This process is accompanied by increased proliferation of trophoblasts, which invade the decidua and form the outer and inner layers of syncytiotrophoblast, directly contacting maternal tissue. In this condition, the expression of specific metalloproteinases (MMP) is affected. Preclinical studies have shown that both isoforms (GnRH-I and GnRH-II) modify cellular matrix metalloproteinases’ expression. Two of them, MMP-2 and MMP-9, are the most directly involved in the migration and invasion of trophoblasts [5].
In addition to the above, it has been shown that both isoforms can produce proangiogenic cytokines, playing a central role in the rerouting of immune system cells involved in the restructuring of the arteries in the maternal-fetal interface [5]. Therefore, GnRH’s direct participation is vital for all physiological, hormonal, and structural changes that will culminate in the fetus’s correct implantation.
On the other hand, GnRH causes the stimulation of the pituitary hormone’s LH and FSH to regulate the sexual function. However, preclinical studies showed that both hormones are inhibited because of Progesterone and Estrogen increased production during pregnancy. Moreover, FSH and LH level rises on day ten after birth, which correlates to the decrease in sex hormones. In this sense, it has been established that the reduction of sex hormones after delivery performs negative feedback, which can achieve the complete reestablishment of reproductive function two months later after birth [6].
Interestingly, these data provide information valuable in understanding the positive and negative feedback mechanisms that play the sexual hormones during the pregnancy to maintain the MPFU.
Progesterone (P4) is considered the “pregnancy hormone” because it is critical for gestational maintenance [3]. During this stage, P4 is produced mainly by the ovary’s luteal body until the twelfth week of pregnancy. After that, its release is principally maintained by the placenta, reaching levels of up to 3 μg/g, while blood concentrations range from 100 to 500 nM, being four to six times its basal levels [7, 8]. These values rise significantly as gestational age progresses. It is involved in both the maintenance and development of the endometrium and inhibiting the uterus’ smooth muscle from preventing premature contractions (spontaneous abortion) [8].
Interestingly, the increase in this hormone’s levels seems to be regulated by an independent mechanism that generally restricts the synthesis of this hormone, being produced by the placental trophoblast cells in response to the stimuli produced in the uterine-fetal microenvironment [9]. At this level, its synthesis is carried out by converting the maternal cholesterol to the pro-hormone pregnenolone into the mitochondrial cytochrome P450. After that, by the action of 3-β-hydroxysteroid dehydrogenases (HSD), it is metabolized to Progesterone. Of the total synthesized Progesterone, 90% go into the maternal circulation, and the remaining 10% goes into fetal circulation [10].
Placental P4 plays an essential role in establishing a pregnancy, as it is responsible for inhibiting uterine contractions that occur at the myometrium’s smooth muscle. In this context, the deficiency of this hormone during the luteal phase has been widely related to infertility and loss of the pregnancy, presenting abortion, a situation that can occur at any stage of pregnancy [8, 9]. Besides, it is involved in the formation of decidua (a layer that coats the endometrium). In this sense, P4 is involved in the structural changes that the uterus undergoes during this period by increasing blood vessels’ permeability and endometrial density. Moreover, it has been suggested that the increase in decidual density is related to a lower likelihood of miscarriage. Also, P4 ensures the integrity of the fetus-maternal interface during the process of trophoblastic invasion and placenta formation [8, 11, 12]. What is more, P4 blocks the early production of T-cell lymphopoiesis protective role intrauterine environment’s immune system (milieu). For that reason, it has been suggested that Progesterone acts as an immunosteroid since a satisfactory pregnancy depends on maternal tolerance to the fetal ‘semi-allograft’ [8].
Similarly, it has been suggested that the increase in P4 levels induces changes in gene expression in the uterine endometrium, indirectly favoring embryo growth [12]. Furthermore, it is a crucial factor between the endocrine and immune system since it has been shown that this hormone is involved in the implantation of tissue, preventing it from being rejected by the mother, a mechanism that appears to be mediated by Th cells (helper T cells), as well as by the interleukins (IL) IL-3, IL-4, IL-5, and IL-10, in such a way, it has been suggested that through inhibition of Th 1 cells and increased production of interleukins, Progesterone is involved in the implantation of the fetus and its maintenance [7, 8].
On the other hand, P4 is involved in regulating the expression of uterine dendritic cells. These are known as antigen-presenting cells (APCs) involved in innate immune response and tolerance maintenance. However, in immature stages, these cells have a tolerogenic phenotype characterized by the low expression of co-stimulating molecules and pro-inflammatory cytokines. Thereby, it has been shown that in the early stages of pregnancy, Progesterone prevents dendritic cells’ maturation. All these previous actions contributed to the maintenance of pregnancy [8].
More interesting, it has been shown that P4 is also involved in reducing gestational stress. In this sense, it has been shown that it can over-express the mPRα gene, which encodes for a membrane receptor present in Cytolytic T lymphocytes CD8 + T cells, and whose increase has been linked to a protective effect against stress-induced abortion [7].
Finally, it is known that P4 levels decrease at the end of pregnancy, a phenomenon that is related to the onset of labor. Hence, an excellent regulatory mechanism of P4 (both at the endocrine and immunological level) from the beginning to the culmination of pregnancy, it is necessary to the implantation, maintenance, and completion of this [12, 13].
The androgenic hormones T, A4, and DHEA, plays a central role in regulating reproductive processes in many mammalian species. Besides, the presence of androgen receptors has also been demonstrated in different tissues such as the ovary, the myometrium, and placenta, where they are known to participate in implanting the fetus and placentation. In this sense, it has been shown that, once pregnancy occurs, androgen synthesis takes place in the small luteal cells (SLC) of the corpus luteum by stimulation of the human chorionic gonadotrophin (hCG) [3, 14]. In addition to the above, once the placenta has been established, it becomes an independent androgen production source [14]. In this aspect, placental syncytiotrophoblast uses the circulating DHEA, provided by the maternal and fetal adrenal glands, turning it into A4 and T. Which, in turn, as will be discussed later, can be converted to estrogens by different routes to regulate embryonic development [3, 15]. Interestingly, it has been suggested that myometrium could be another important source of androgens during pregnancy; a recent
Suppressively, these hormones are coordinated synthesized during pregnancy. Specifically, it has been shown that T levels increase in the first trimester of pregnancy, reaching a plateau in the second trimester, to later decrease slightly, rising considerably in the last month of pregnancy [14, 15]. Concerning A4, the study carried out by Satué et al. (2018) in mares shows that this hormone rises during gestation, from the second month of pregnancy, reaching a peak maximum in the first stage of pregnancy, and, in the second state, it reduces significantly, reaching its lowest levels in the last month of gestation. However, a clinical study conducted by Makieva et al. (2014) showed that A4 remains stable throughout pregnancy without significant fluctuations. About DHEA, it increases progressively from the first to the fifth month of pregnancy, reaches its highest levels, then begins to decrease between months 6 and 7, reaching its lowest levels in the last month of pregnancy in mares, which is agree with the observed in pregnant women, with levels up to 50% lower than those observed in non-pregnant women, an effect associated with negative E2 feedback to the maternal adrenal glands [14, 15].
The fluctuations in these hormones have specific functions during pregnancy. The significant increase observed in the first months of gestation is associated with the function of the corpus luteum, which uses T for estrogens’ production (analyzed in the next topic), regulating the implantation and decidualization. Later, the decrease observed in the middle of the gestation is related significantly to the development of the fetal gonads, providing the necessary substrates for the synthesis of placental estrogens. So, the primary site of estrogen synthesis at this stage could be the fetus. Finally, T’s elevation in the last stage of pregnancy, but not of A4 and DHEA, could be associated with the restructuring that the cervix must undergo to be prepared for the moment of delivery. At this stage, it has been shown that the cervix can convert T into another metabolite, Dihydrotestosterone (DHT), through the action of 5-alpha-reductase. This androgen is involved in restructuring the cervix’s extracellular matrix tissue, including the structural changes that allow the myometrium’s contractility [14, 15].
Therefore, these interesting data confirm the surprising interrelation and interdependence between estrogens and androgens produced by MPFU to protect and ensure pregnancy’s proper development.
Estrogens are a group of four different steroid hormones: Oestrone (E1), 17β-Oestradiol (E2), Oestriol (E3), and Oesterol (E4), cyclically synthesized in response to changes during the ovarian cycle, specifically during the pre-ovulation phase, favoring folliculogenesis. However, estrogens also play a central role in the growth of the uterus and mammary gland. It increases the blood flow indispensable for transporting nutrients between the uterus and the fetus [16]. During pregnancy and up to the time of delivery, significant amounts of estrogens are released by the maternal-fetus-placental unit, formed by the luteal body, placenta, and the fetal adrenal cortex [3], suffering significant adjustments between the weeks seven to nine of pregnancy, reaching its highest levels at the time of delivery [17, 18].
17β-Oestradiol (E2) is the most abundant hormone synthesized during pregnancy. In connection with this, until the third month of pregnancy, significant levels of E2 are released by the luteal body, a period from which the primary site of estrogen production is the placenta [3]. It should be noted that the placenta has no autonomic innervation, so these increases occur in response to close communication between the mother and the fetus, where the hormone acts in an autocrine-paracrine form in the development of the mammary gland and uterus, as well as in the development of sexual characteristics in the fetus. This connection allows the placenta and fetus to exchange and share steroid precursors, thus achieving their hormonal self-regulation [18].
Several studies have shown that the increase in estrogen levels is the result of a mutual exchange between the mother and placenta, in which the placenta uses the circulating androgen DHEA produced by the adrenal glands of the MPFU, where it is converted to Testosterone and Androstenedione and then metabolized to E1 and E2 with the help of the cytochrome cyp450 aromatase enzyme [3, 7]. In such a way, both the mother and the fetus contribute to the increase in estrogen synthesis, regulating their production. In addition to this, and due to the high maintenance of this hormone throughout pregnancy, there is sufficient evidence to suggest that regulation in levels of this hormone could also be at the neural level, where E2 could act as a trigger factor of the HPA gland axis. So, the adaptive changes that occur in the mother-fetus are regulated by a positive feedback mechanism, in which the binding of E2 to their receptors at the brain could be sending signals to the adrenal glands for producing a more significant amount of DHEA, thus maintaining their constant levels [19]. Therefore, it seems clear that estrogen levels regulation during pregnancy occurs both locally, by an interaction of the placental-fetal unit and in an autonomic way, with the direct participation of the Central Nervous System.
Concerning its functions, estrogen has been shown to act through binding to nuclear receptors, participating in multiple processes to ensure the maintenance of pregnancy having different roles: in human endometrial explant cultures, they are involved in uterine vascular restructuring by binding to their nuclear receptors present in epithelial and stromal cells of the cervix and endometrium, acting regulating the expression of different genes that control intrauterine growth, maturation of vital organs such as mammary glands for breastfeeding and childbirth [16, 17, 18, 20]. Besides, it promotes the processes of angiogenesis and vasodilation that allow the transfer and exchange of nutrients and oxygen between the placenta and the fetus through uterine and fetal circulation, a process associated with an increase in endothelial production of nitric oxide [3, 21].
On the other hand, in the primary culture of endometrial-epithelial cells (ESC), it has been found that E2 plays an essential role at the beginning of pregnancy by acting in processes such as differentiation and cell proliferation through the secretion of insulin growth factor type 1 (IGF-1) [22]. Also, it increases the rate at which the fertilized egg travels through the fallopian tube, so low estrogen levels promote ectopic pregnancies because the egg stays longer in the fallopian tube [23].
In addition to the above, estrogens E1, E3, and E4, also, play a central role in pregnancy. E1 is the most abundant conjugated estrogen (estrone sulfate) during pregnancy; it increases from the first trimester of pregnancy, reaching its maximum peak in the 35th week of gestation; among its functions, the decrease of estrogenicity has been indicated in the time of delivery [24]. E3 (Oestriol) is also considered a derivative of estradiol, whose primary role during pregnancy is increased uteroplacental blood flow during pregnancy. However, a specific function has also been suggested in the induction of myometrial cells’ contractions through the increase of connexin-4, allowing the restructuring of the myometrium that will trigger the initiation of labor [3]. On the other hand, Oesterol (E4) has an uncertain function during pregnancy since it is produced exclusively by the fetal liver starting up from the ninth week of pregnancy, reaching its significantly elevated levels after week 30, with a peak at week 40. Although its function is unclear, preclinical studies have shown that it can bind to estrogen and progesterone receptors at the uterus, producing histological structural changes and biochemical fluctuations, essential during the differentiation of endometrial cells in pregnancy and delivery [25].
Therefore, during pregnancy, the hyperestrogenic state plays a significant role in maternal-fetal development, being a key piece in fetal growth. Hence, all these actions make the estrogen pleiotropic essential hormones in pregnancy.
Prolactin (PRL) is a protein hormone synthesized by the lactotroph cells of the anterior pituitary gland. Unlike other pituitary hormones, its release is inhibited by Dopamine (DA), a hypothalamic factor produced by dopaminergic neurons located in the arcuate nucleus, which has not only been shown to be able to regulate the release of PRL but can act at the lactotrophic cells, regulating their proliferation [1]. In addition, PRL can control its release, directly stimulating dopaminergic neurons and through direct and indirect mechanisms regulated by E2 [23].
In this sense, a preclinical rat model study showed that in the different reproductive stages, PRL intervenes in a coordinated manner with E2 and Dopamine in regulating the proliferative activity of lactotrophic cells. In this collaborative process, these cells’ activity is elevated in the estrus and delivery stages. But it is decreased during the early stages of pregnancy and lactation, even though PRL levels are increased in all these reproductive stages. In this context, it has been suggested that E2 participates in stimulating the release of PRL during the early stages of pregnancy and lactation by acting at the hypothalamic level regulating both the increase in prolactin levels and the activity of the lactotroph cells when DA is not present, play a dual role in the release of this hormone [23, 26].
Evermore, during pregnancy, essential adaptations occur to allow the release of significant amounts of this hormone by the stimulation caused by the mammary gland and the luteal body [27], with substantial elevations from the twentieth week of pregnancy, until after childbirth [26]. Specifically, PRL has been shown to play a vital role in regulating IL-10 and IL-12 interleukins (essential regulators of immune responses during inflammatory processes). On the one hand, IL-12 interleukin has a pro-inflammatory function, activating itself in response to situations such as stress. On the other hand, IL-10 is an anti-inflammatory cytokine, which intervenes in the regulation of the expression of IL-12. In this sense, it has been shown that, during pregnancy, PRL increases the concentration of IL-10, an effect suggested is associated with the proper maintenance of this [28].
At the clinical level, this hormone has been shown to provide luteotropic support to the luteal body by intervening in the biosynthesis of P4 for its maintenance in the first three months of pregnancy, having an indirect function in the implantation of fetus in the uterus, as well as in the induction of vascular factors necessary for the increase in the volume of the luteal body [1, 29]. On the other hand, it acts directly on the mammary gland, determining the growth and development of alveoli, promoting the expression of genes related to milk synthesis and lactopoiesis. It also helps maintain the luteal body’s integrity and decidual cell survival [30]. Moreover, it is involved in the synthesis of relaxin, a hormone responsible for dilating the cervix during labor, thus facilitating the fetus’s expulsion [27].
PRL, it has been shown to play an essential role in regulating leptins expression in the gestational stage [31]. Leptins are hormones produced mostly by adipocytes, whose central role is related to the regulation of body weight, appetite, and energy homeostasis. The increase in their plasma levels is associated with the rise in the amount of body fat. However, during the gestational stage, vast quantities of leptins are released by the ovary and placenta, remaining constant throughout pregnancy, intervening in the regulation of fetal weight and growth, and with the development of gestational diabetes [32]. In this sense, the increase in PRL levels has been suggested to inhibit the receptor to leptins (LepR), thus blocking the signaling pathways that regulate the development of gestational diabetes [31].
Finally, it has a central role in mother–child recognition by increasing the generation of neurons at the olfactory bulb level, which is essential for such recognition [29]. For that reason, PRL recognizes like a multifaceted hormone, with dual actions during and after delivery.
The human placental lactogen hormone (hPL), known as human Chorionic somatomammotropin, is a polypeptide hormone elevated during pregnancy and is produced exclusively by the placenta [3]. hPL levels are detected between the first and second weeks of placenta gestation. However, it is released into the maternal circulation between the third to sixth week of pregnancy, being possible its detection, which increases until reaching its constant levels with a significant increase at the end of pregnancy with substantial effects after delivery [3].
Although there is controversy regarding its participation during pregnancy, it has been suggested that its primary function is the regulation of maternal metabolism of lipids and carbohydrates, being crucial to maintaining energy homeostasis between mother and fetus. In this sense, at the preclinical level, it has been shown that it stimulates the production of the IGF-1 factor in maternal hepatocytes. It modulates intermediate metabolism by increasing food intake (orexigenic drive), which favors the increase in glucose available for transfer to the fetus and prevents the development of gestational diabetes caused by peripheral resistance, typical at this stage [1, 3].
Moreover, it has been suggested that it has a central role in intrauterine growth because more than 50% of neonates with stunted growth have shown a deficiency in hPL levels. It is also believed that, by stimulating the uptake of glucose, glycerol, and free fatty acids, it could significantly participate in fat deposits, serving as an energy-saving mechanism for the fetus [1, 3].
Furthermore, it is well documented that in a normal state of pregnancy, insulin sensitivity decreases with the advance of the gestational state, which allows the fetus to maintain energy, an effect caused by a joint inhibitory action of peptide hormones (C-reactive protein, leptins, and hPL) on insulin levels causing dysfunction of pancreatic β-cells, named “diabetogenic condition.” However, a clinical study conducted by Ngala et al. (2017) showed that, throughout pregnancy, important maternal factors could predict the development of gestational diabetes mellitus (GDM) in addition to the already known factors of obesity and family history. In this sense, the levels of glucose, insulin, glycosylated hemoglobin (GHb), and hPL, among others, are increased in pregestational pregnant women, an effect not observed in non-diabetic pregnant women. Interestingly, under this condition, E2 and P4 levels decreased in pre-diabetic women, while in healthy women, the levels of both hormones are increased. On the other hand, between weeks 24–28 of gestation, an increase in Progesterone, Estradiol, Leptins, GHb, and Fasting blood glucose (FBG) was observed in developing GMD, an effect associated with the increased insulin resistance. Controversially, although there is little information linking hPL with the development of GDM, it is believed that the decrease in the levels of this hormone after delivery is associated with the reduction in glucose resistance and with the increased risk of diabetes-prediabetes in nursing mothers [33, 34].
Interestingly, hPL participates in lactation by stimulating the breast epithelium, facilitating breast development during the gestational stage. In this process, both hormones (hPL and PRL) act in maternal behavior, suppressing stress responses in the last stage of pregnancy and lactation [1]. In this sense, it has been shown that dopaminergic neurons’ activity can be maintained by hPL [23].
All these results confirm the metabolic action of hPL in pregnancy and lactation, alone or together to other placental and maternal hormones.
HCG is considered one of the essential hormones during gestational development, having similarities with other members of the same family of glycoproteic proteins such as LH and pituitary FSH. Its synthesis is regulated by the luteal body and placenta, exercising a pleiotropic role during gestation by autocrine and paracrine mechanisms [3]. It is possible to detect significant levels from day eight after fertilization, reaching its maximum levels around the tenth week of development. After which, it maintains at constant levels when the placenta is fully developed. At this point, the luteal body’s secretions are no longer necessary [3].
It participates in the process of steroidogenesis and in the restoration-maintenance of the luteal body, where it acts as a relay system, whose purpose is to prevent menstruation by increasing the synthesis of P4, allowing that the embryo can be implanted in the uterine endometrium, ensuring pregnancy until placental production of Progesterone is well established [3].
The hCG has also been shown to have a structure like Thyroid stimulating hormone (TSH) to bind to the same receptors, having implications for regulating thyrotropic activity. Preclinical studies have shown that maternal TSH decreases at the end of the third trimester of pregnancy. This decrease correlates with increased placental hCG and fetal thyroxine-binding globulin (TGB) [1].
Moreover, clinical studies have shown that it is also involved in the differentiation of cytotrophoblast in syncytiotrophoblast, constituting an essential factor in the secretion of relaxing decidual production of PRL. On the other hand, it has androgenic properties. It can promote the synthesis of DHEA by the fetal adrenal cortex, regulating both testicular function and fetal male differentiation during the first weeks of gestation [35]. In addition, it has been suggested that it has participated in other functions; in the immune system, stimulates the production of the anti-inflammatory interleukins IL-8 and IL-10, and inhibits lymphocyte response, preventing rejection of the fetus, suggesting an immunosuppressive role of hCG during pregnancy; it stimulates testicular Leydig cells for testosterone production and provides nutrients and hormones for optimal maintenance of intrauterine microenvironment [3, 35]. So, the metabolic implications of this hormone suggested it like a metabolic hormone in pregnancy.
The secretion of cortisol levels during pregnancy is regulated by the placenta, which, by secreting the corticotropin-releasing hormone (CRH), produces an exponential increase in cortisol from the eighth week of gestation up to three times above systemic values [5, 36]. It is present in both the maternal and fetal phases but at different levels; under normal conditions, cortisol levels reach 200 ng/ml at the end of pregnancy, while fetal levels range from around 20 ng/ml [37]. These differences are due to the presence of a natural barrier that prevents maternal cortisol, whose molecular composition can cross the placenta, quickly reaches fetal space [38, 39].
This barrier corresponds to the uterus/fetus interface and is mainly composed of maternal decidua and fetal placenta chorion. Here the regulation of cortisol is carried out through placental glycoprotein P, as well as the enzyme 11-β-hydroxysteroid-dehydrogenase (11-β-HSD) type 2 of trophoblastic and fetal cells, which inactivates cortisol by converting it into cortisone to avoid exposure of the fetus to high levels of cortisol [37, 40]. However, because of its role in organ maturation and labor, fetal cortisol increases towards the end of pregnancy by several mechanisms: a) decrease of 11-β-HSD type 2 in fetal tissues, b) increased synthesis of cortisol by the fetal adrenal gland, and c) increased 11-β-HSD type 1 in fetal tissues, which converts cortisone, into active cortisol [41].
As for the functions of cortisol during pregnancy, glucocorticoids (GC) have been described as participating in the processes of implantation and formation of decidua, as well as in fetal development and maturation, and initiation of childbirth [17, 36, 42]. Elevated levels of GC present during pregnancy are involved in the suppression of inflammation of the uterus, placenta, and fetal membranes, which contributes to maintaining the homeostasis necessary for the maintenance of pregnancy [42]. Moreover, recent evidence suggests that significant increases in cortisol levels play a critical role in the baby’s growth in the postnatal stage [43]. In this sense, studies have shown that high concentrations of cortisol during the fetal phase positively correlated with weight gain within the first five years of postnatal growth, indicating that the higher increase in placental cortisol levels, the more significant weight gain can be observed in children during this stage, suggesting that hormonal changes within the maternal-fetal environment have repercussions in post-birth stages, a highly relevant endocrinological aspect [43].
Conversely, cortisol is also involved in developing pregnancy complications, being responsible for the so-called “Hypothalamic Stress Amenorrhea,” whose consequence is the generation of miscarriages [8, 44]. On the one hand, it has been shown that low maternal cortisol levels compromise the placenta’s structure. In contrast, elevated levels can lead to miscarriages, uterine contractions from placental CRH deregulation, the elevation of fetal cortisol levels, and obstetric alterations by activation of the HPA gland axis [14, 36, 38, 45]. In this sense, two main axes, the HPA, and the sympathetic nervous system-adrenal medulla exerts a negative effect on the reproductive system when activated in stressful situations. In this feedback mechanism, the CRH that is produced at the pituitary can act, in a short negative feedback mechanism, directly inhibiting GnRH at the hypothalamus.
Even more, cortisol act at the pituitary to inhibit the release of LH and FSH, and, consequently, inhibits steroidal ovarian hormones, Estrogen, and P4, resulting in abortion. It has been confirmed in preclinical and clinical studies, where exposure to stressors, such as noise, has been verified to induce miscarriages, with a significant decrease in P4 levels [8, 44]. More interesting, stress increases the excitability of the sympathetic nervous system, resulting in a decrease in blood flow supply to the placenta caused placental hypoxia and increased generation of reactive oxygen species, causing damage to trophoblasts; the outer layer of the blastocyst, responsible for providing nourishing to the embryo [44].
Finally, it has also been suggested that high cortisol levels could mediate a disbalance in T helper cells Th 1 and Th 2, with a specific impact in the decrease of adaptative immune system responses that allow the fetus’s maintenance. However, more studies are needed to confirm this [44]. So, it is evident that cortisol is not just a “stress hormone”; it has several functions supporting the MPFU.
During pregnancy, high estrogens and corticosteroids induce an increase in TGB levels in the liver, which is significant from week twenty of gestation, reaching its maximum level from week twenty to twenty-four. The rise in TGB during the first half of pregnancy is related to further deiodination of the inner ring of the hormones T4 (Thyroxine) and T3 (Triiodothyronine) at the placenta, which is responsible for the physiological effect attributed to them [46, 47].
As far as the fetus is concerned, it has been shown that there are at least two mechanisms for it to contribute to thyroid hormones: the development of the fetal thyroid gland and the maternal thyroid gland. More interesting, the increase in concentrations of T4 in the first half of pregnancy and the expression of receptors to thyroid hormones in the brain, suggesting its participation in the development of brain structures of the fetus. Moreover, from weeks twelve-fourteen, in which the fetal thyroid begins to synthesize T4, its levels increase progressively, until reaching its maximum levels between week thirty-four to thirty-six, remaining elevated until the delivery time [46].
About iodine levels begin to be detected from ten to eleven weeks of gestation, a stage in which the fetal thyroid can concentrate. Around the twelfth week, the pituitary starts to produce and synthesize TSH and TRH (Thyrotropin-releasing hormone) by the hypothalamic neurons [46].
Before the fetal thyroid develops, the placenta has a particular involvement in maternal-fetal thyroid regulation. It is responsible for exchanging thyroid hormones to the fetus, suggesting an essential role in early fetal growth. Among the functions attributed to thyroid hormones are the brain’s development and the acceleration of fetal pulmonary maturation. The effect has been demonstrated in preclinical and clinical models in which fetal pulmonary growth has been shown to increase after intraamniotic injection of T3 or T4. On the other hand, the effect at the brain level has been demonstrated in intrauterine hypothyroidism conditions. It is related to irreversible damage to the brain and mental disability in children born under these conditions [46, 47].
Interestingly, clinical studies conducted in children whose mothers suffered from hypothyroidism, a condition that occurs in 0.05–0.02% during pregnancy, have shown that these irreversible changes specifically affect neurodevelopment. In this sense, it has been demonstrated that any situation that leads to the development of clinical hypothyroidism (generally associated with Graves’ disease) and hypothyroxinemia (associated with overtreatment of antithyroid drugs) that can occur during the first trimester of pregnancy can lead to a cognitive delay in children, learning disorders, maturational delay, encephalopathy, and seizures among other conditions [48].
Significantly, the increase in TSH, T3, and T4 during pregnancy could have protective effects against fetal anemia because it has been suggested that they may have cardiotonic effects by direct activation of the sympathetic-adrenal nervous system, in addition to being shown to stimulate the production of erythropoietin, which is involved in the production of red blood cells and therefore in the release of oxygen to tissues [47].
In this sense, it is fascinating to understand that sex hormones regulate the release of thyroid hormones and the vital functions involved, like brain development, being crucial during pregnancy and childhood.
Pregnancy is a physiological state characterized by critical hormonal changes. Collective participation of the endocrine system is necessary to carry out adequate development and maintenance of both the mother and the fetus. This system is responsible for generating an optimal environment that provides an adequate microenvironment of communication between the maternal-placental-fetal unit, facilitating the exchange of nutrients, hormones, and oxygen, essential throughout the gestational period. These neuroendocrine processes are produced thanks to the synchronous and fluctuating production of sex hormones regulated by endocrine, paracrine, and autocrine mechanisms. Their function is essential before, during, and after the gestational period to ensure the fetus’s correct development and growth.
The author thanks the National Council of Science and Technology (CONACyT) for the supporting founding.
The author declares no conflicts of interest.
Maternal-placental-fetal unit Hypothalamus-pituitary-gonads axis Hypothalamus-pituitary–adrenal gland axis Hypothalamus-pituitary-thyroid axis Gonadotropin-releasing hormone Gonadotropin-releasing hormone receptors I and II Follicle-stimulating hormone Luteinizing hormone β-Human chorionic gonadotropin Progesterone Metalloproteinases 3-β-hydroxysteroid-dehydrogenases 11-β-hydroxysteroid-dehydrogenase Helper T cells Interleukins Antigen-presenting cells Testosterone Androstenedione Dehydroepiandrosterone Oestrone 17β-Oestradiol Oestriol Oesterol Endometrial-epithelial cells Insulin growth factor type 1 Prolactin Dopamine Leptin receptors Human placental lactogen hormone Thyroid Stimulating Hormone Thyroxine-binding globulin Vascular-endothelial growth factor Corticotropin-releasing hormone Glucocorticoids Thyroxine Triiodothyronine Thyrotropin-releasing hormone Small luteal cells Gestational diabetes mellitus Glycosylated Hemoglobin Fasting blood glucose
Hydrogels are three-dimensional polymeric networks that are utilized in various medical applications due to their unique properties: hydrophilicity, biodegradability, non-toxicity, and their controllable mechanical properties to mimic the mechanics of biological tissues [1, 2]. Furthermore, their structural properties exhibit similarities with biological extracellular matrix components which makes them ideal for cell culture and growth [3].
From the mechanical perspective, the concentration of the polymer network in hydrogels controls, to large extent, their mechanical strength allowing them to mimic the mechanics of physiologically loaded tissues [4]. Consequently, due to their availability and relatively low cost, hydrogels have become an attractive option when developing quantitative techniques that measure the mechanics of biological tissues [5, 6, 7, 8].
On structural level, hydrogels can be produced by chemical or physical cross-linking. In chemical (permanent) hydrogels, the network is crosslinked with strong covalent bonds that connect the molecular chains [9]. In physical (reversable) hydrogels, the gel’s molecular chains are connected with weaker forces such as hydrogen-bonding and ionic forces, thus, they can be easily dissolved by altering their environmental conditions (e.g., temperature, ionic strength, or pH of the gels [10]). These crosslinking methods allow the synthesis of multi-network hydrogels. For instance, hydrogels can be fabricated to have highly crosslinked rigid chains that are entangled with weakly crosslinked chains to provide a functional network system used in synthesizing biomaterials for several medical applications [11, 12].
One of the medical applications the hydrogels used in is contact lenses, mainly due to their unique physical properties and ease of processing; for example, Bauman et al. [13] developed Silicone Hydrogel lenses with nano-textured surface that mimics the surface of human cornea. Hydrogel lenses are also known for their wettability, a property necessary to avoid tear deposits [10], thanks to plasma treatment during the synthesis process [14]. Gas permeability is also a key characteristic of contact lenses to provide the cornea with efficient supply of oxygen at sufficient rates. Hydrogel lenses can be designed to meet this requirement thanks to their hydrated polymer matrix [10]. Hydrogels are also commonly used in wound dressing; they have been used in combination with other materials to form composite products efficient for different dressing applications; for example, a gauze impregnated with thermoplastic hydrogels allows for absorbing wound exudate while maintaining relative slimy consistency, as a result, it prevents adherence to the wound that normally results in pain during gauze changes [15]. Moreover, flexibility and transparency of hydrogels also made them an attractive option in wound dressing. While flexibility facilitates easy removal of the dressing products, transparency allows for continuous observation of the wound healing process [16].
Nowadays, delivery and release of drug molecules is receiving significant attention in many fields of medicine in which therapeutic drugs are loaded in polymer-based-carriers. These carriers transport the drugs to the targeted location [17, 18]. The efficacy of gels as drug-carriers relies in their adjustable porosity through controlling the crosslinking density of their matrix. Their porous structure allows for drug loading and releasing with high efficiency [19, 20]. Numerous studies have been published on the potential applications of hydrogels in drug delivery focusing on their mechanism, shape of the gel-carriers, and types of transported drugs. Therefore, this chapter, will discuss different drug loading and releasing mechanisms with respect to their corresponding medical application. Furthermore, the drug dosage is dependent on the design of the hydrogel systems, which in turn depend on the route of the drug administration (e.g., rectal, ocular, peroral, etc.), thus, this chapter will shed the light on the types of hydrogel-based carriers applied via different routes of drug administration. Lastly, this chapter will cover different classifications of the delivered drugs using gel-based delivery systems including small molecular weight drugs; therapeutic proteins and peptides; and vaccines.
Drug loading is an important property of a drug delivery system, and it is defined as the process of incorporating a drug into a carrier. The therapeutic agents can be introduced into gel-carriers by ionic interaction, dipole interaction, hydrogen bonding, physical encapsulation, covalent bonding, precipitation, or surface absorption. It’s common that more than a loading mechanism is used in drug delivery systems, and the ideal loading strategies are determined based on the compatibility between the physicochemical properties of the drug and the carrier.
The drug-loading process can take place during the formation of the carriers, or by incubating carriers into a concentrated drug solution to allow the loading through adsorption on their surface area [21]. However, this method has limited loading capacity, and the incubation time can influence the drug loading efficacy [22, 23]. In general, the entrapment and loading of drug molecules into polymer carriers depend on several characteristics: polymer and crosslinker concentrations, molecular weight of the polymer, and drug-polymer interactions [24, 25, 26]. The higher the polymer concentration the more efficient the drug entrapment is; at a high concentration, the polymer viscosity is increased, which delays the drug diffusion within the polymer particles [27]. Similarly, the high concentration of the crosslinker yields tangible increase in the loading efficiency [28]. Conversely, Fu et al., 2004 reported that the encapsulation efficiency decreases when the molecular weight of the polymer increases [29]. In protein based drugs, the interaction between the polymer and the drug molecules contribute to the entrapment efficiency; it increases if the protein molecules are entrapped into hydrophobic polymers, moreover, ionic interaction between the molecules and the polymer particles increase the efficiency of encapsulation, specifically, in polymers that belongs to carboxylic end groups [30].
The delivery of therapeutics by nanocarriers can be passive: transport of drug-carrying nanoparticles through permeable vessels due to the enhanced permeability and retention (EPR) effect; or active: based on molecular recognition in which peripherally targeting moieties that interact with specific cell receptors [31].
In localized cancer therapy, the mechanism of passive targeting relies heavily on the tumor characteristics; tumor hypoxia causes rapid growth of leaky vessels, which increases the permeation of nano-delivery systems into the tumor, the lack of lymphatic filtration allows for the retention of these systems on the tumor’s interstitial space [32]. Moreover, this targeting strategy also depends on the carriers’ size; delivery systems larger than 50 kDa permeate through leaky vessels and retained in the tumor, smaller molecules are washed out quickly (very short circulation time) from the tumor [33]. The charge and the surface chemistry affect the circulation time of carriers; mononuclear phagocyte system (MPS) cells tend to opsonize largely hydrophobic and charged systems. Thus, water-soluble and neutral (or slightly anionic) compounds (e.g., Polyethylene Glycol) are used to coat the nanocarriers surface [31, 32, 34]. Active targeting also depends on the EPR effect to accumulate the delivery nanocarriers in the tumor region, however, the efficacy of this strategy capitalize on equipping the nanocarriers’ surface with ligands that bind to specific receptors of cancer cells, thus, enhancing the penetration and efficiency of the chemical therapeutics. Figure 1 illustrates passive and active targeting strategies.
Schematic illustration of active and passive delivery of drug molecules.
Biodegradation of the nanocarriers is essential for the release of the drug molecules over extended periods of time (days or weeks). It is also crucial for the removal of delivery systems from the body [35]. The carrier size has an effect on the efficacy of the releasing process; drug molecules loaded at or in proximity to the surface of small particles are released at a fast rate due to the large surface-to-volume ratio. On the other hand, slower release rates are associated with larger particles, nevertheless, more drug molecules can be loaded. Modulation of the drug release can also be controlled by the molecular weight of the gel composition; higher molecular weight tends to exhibit slower release rates [36, 37]. In general, the mechanism of releasing drugs is dependent on three main parameters: drug diffusion and dissolution, gel matrix design, and interaction between the drug and the gel matrix.
The transport of the therapeutic molecules out of the gel matrix is a complex process that depends on the dissolution and diffusion of the drug [38]. Several studies have been conducted to develop mathematical models that describe this process [39, 40, 41]. The basic equation of the dissolution rate as a function of diffusion can be described as [42].
Where dM/dt is the rate of dissolution, A is the surface area of solid in contact with the dissolution milieu, D is the diffusion coefficient,
There are several mechanisms to release the drug, most common strategies are diffusion and swelling controlled. In diffusion-controlled delivery systems, drug molecules diffuse from a region of high drug concentration (reservoir) through the gel matrix or membrane. The design of these systems is commonly available as spheres, cylinders, slabs, or capsules. These systems can have a constant rate of release as described by Eq. (1), or their release rate can be proportional to the square root of time. In the latter case, the drug is usually dispersed or dissolved uniformly through the matrix of the hydrogel [10]. In swelling controlled systems, the drug is dispersed within carriers made of a glassy gel, and upon contact with biofluids, they swell beyond their boundary which results in the diffusion of the drug during the relaxation of the gel chains, this process is known as anomalous transport [10, 44]. Illustrations of the two releasing mechanisms provided in Figure 2. The structure of the nanocarriers’ controls the release of the drugs; using hydrogels alone in synthesizing the nanocarriers can result into fast premature release of drugs and poor tunability [45]. Therefore, using additives can enhance the control of the drug delivery process; using Polydopamine (PDA) as an additive to the hydrogel materials in making the nanocarriers provides an on-demand capability to release the drug. In high glutathione (GSH) and acidic condition, the bond between the drugs and PDA experience weakening. This is a useful property to release the drugs in inflammatory areas or tumor cites where pH levels are low. While at neutral pH levels such as in normal tissues, the bond between the PDA and the therapeutic dugs is not affected [46, 47, 48, 49, 50]. Furthermore, PDA generates heat upon exposure to near infrared (NIR) laser, which makes it ideal for NIR triggered drug delivery [51].
Schemes of drug release systems: (a) from a reservoir system; (b) from a matrix system.
Besides long-term stability and release properties, passing the toxicity screening is essential for hydrogel formulations to be used in drug delivery. This is mainly due to the rise of inflammatory reactions that occur as a result of the degradation of synthetic polymers [52]. Therefore, achieving biocompatibility is necessary to use hydrogels in an environment of living organisms. Most in-vivo tests are conducted on animal models to provide reliable biomedical mimicry. As a result, several hydrogel-based drug delivery systems have been developed and approved for clinical use through different administration routes. Currently, the common accessible routes of these systems are Oral [53], rectal [54], subcutaneous [55], transdermal [56], ocular [57], and intraperitoneal [58]. These administration routes are illustrated in Figure 3. Table 1 provides examples of gel-based products used in drug delivery through different administration routes.
In-vivo hydrogel-based drug delivery in most common routes of administration. The schematic illustration is reproduced from [
Route of administration | Shape | Typical dimensions | References |
---|---|---|---|
Oral | Spherical beads; Discs; Nanoparticles | 1 μm–1 mm Diameters of 8 mm and thickness of 1 mm 10–1000 nm | [35, 60, 61] |
Rectal | Suppositories | Conventional adult suppositories dimensions (32 mm in length) with central cavity of 7 mm and wall thickness of 1.5 mm | [62] |
Transdermal | Dressing | Variable | [63] |
Subcutaneous | Injection (hydrogel spacers in prostate cancer therapy) | N/A | [64, 65] |
Intraperitoneal | Injection (hyaluronic acid hydrogel loaded with chemotherapeutics) | N/A | [66] |
Oral administration currently is the most common and convenient for hydrogel drug delivery systems, thanks to their bioavailability and nontoxicity they provide [67, 68]. However, such systems have limitations due to the metabolic effect these systems have on the living organism including but not limited to denaturation and reduction of epithelial membrane permeability [52]. Delivery systems in this strategy are usually made from caprolactone, MPEG, itaconic acid pH-sensitive hydrogels as they were reported to have no signs of toxicity [68].
This route provides an alternative to intravenous and subcutaneous medication delivery. It has faster absorption of the medication through rectum’s blood vessels, which makes it ideal for therapeutics that have high bioavailability and shorter duration [69, 70]. Moreover, it provides a stable environment in which the drugs are released since this administration strategy bypasses the gastrointestinal tract. As a result, minimal alterations occur to the drug concentration when it reaches the circulation system [71]. Hydrogel-based delivery systems such as catechol-chitosan gels have shown excellent biocompatibility and were reported to have no toxicity in-vitro and in-vivo [54, 72].
This route is very common in studies that involve animal models when developing gel-based injectable biomaterials such as alginate [73], gelatin [74], poly-acrylamide [75], ellagic acid [76], and pectin [77]. While these biomaterials have shown no toxic response when deployed in-vivo into the animal model, the majority of the studies have reported inflammatory effect due to the vascularized nature of the subcutaneous region that is associated with reactions against foreign moieties [78].
In topical delivery, the therapeutics reach the circulation system through penetrating the skin layers; the drug passes through the startum corneum to deeper epidermis and dermis until it is absorbed by the dermal microcirculation [79, 80]. The hydrophilic nature of hydrogels allows them to hold considerable amounts of fluid content that ranges between 10% to 1000 times gels’ dry weight [81], which makes them ideal for carrying drugs such as insulin, theophylline, sodium fluoride, and progesterone and heparin. Transdermal hydrogel patches can provide a controlled rate of drug delivery in addition to providing a cooling effect at the location where they are applied [81]. Hydrogels can also be combined with bio-adhesives to prolong the therapeutic effect of the delivered drug when applied topically [82].
Intraperitoneal injections of hydrogel systems are considered a successful delivery strategy for various therapeutic agents. The injected hydrogels compounds can achieve efficient drug delivery while exhibiting anti-adhesiveness properties on the peritoneum [83]. Although intraperitoneal hydrogels were reported to be non-toxic [84], their hydrophilicity can compromise the concentration of the delivered pharmaceutical agents [58].
Budhian et al. [85] categorized the release of this class of drugs into three stages; (i) initial burst, during which the drugs immediately released into the medium; (ii) induction, in which the release of drugs is gradual; and (iii) slow release, in which the release reaches a steady slow rate [85]. These stages are controlled by three unique properties of the gel in use to synthesize the delivery systems: hydrophobicity, surface coating, and particle size [35]. The lower the hydrophobicity the higher the release of drugs during the burst stage; for example, the percentage of released drugs after 1 day is 45% for 220 nm strongly hydrophobic PLA particles, on the other hand, the release percentage is 70% for the same size of the moderately hydrophobic PLGA particles. The release stages are also affected by the surface coating of the nanoparticles; coating PLGA particles reduces the number of drugs released by 40%. The rate of release and the initial burst are affected by the size of the particles; increasing the size decreases the total surface area which reduces the burst period, furthermore, the larger the size, the longer the pathways the drug molecules take during the diffusion which increases the induction period [85].
Among several peptides- and proteins-based therapeutics that are used in drug delivery, enzymes are the most studied class of drugs [86]; examples of such enzymes include L-asparaginase, cysteine desulfatase, cysteine oxidase, arginase, and arginine decarboxylase [87]. Currently, only a few protein- and peptide-based drugs have been used in medicinal setting. The clinical use of this class of drugs is hindered by several factors: enzymatic degradation, renal filtration, inefficient cell entry, accumulation in nontargeted organs, immune system response that causes allergic reaction, and protein inactivation due to intrinsic properties such as low stability in an environment of physiological pH and temperature [88].
A simple approach to overcome the elimination of this class of drugs is introducing it via injection to the targeted organ. However, this strategy has its own limitations such as difficulty or delocation of the targeted site, drug toxicity, and long-term hospital setting administration [88]. Other delivery strategies were proposed such as microfabricated chips and implantable devices [89, 90]. While these strategies have shown promising results, their deployment and extraction require surgical intervention. To overcome these challenges and to stabilize the therapeutic proteins and peptides in the physiological environment, they are encapsulated into nanocarriers. This technique protects the enzymes from the degradation parameters imposed by the physiological environment while delivering different types of protein-based drugs [88].
Shimizu et al. [91] developed nanocarriers that efficiently encapsulates bone morphogenic proteins (BMPs), which have significant capability to convince bone formation. When BMPs are encapsulated by the developed nanocarriers, they provided sustained delivery of the BMPs over a time period of 14 days. In cancer therapy, polymersomes are used to deliver therapeutics; Danafar et al., 2016 investigated the delivery of drug molecules encapsulated into mPEG-PCL hydrogel nanocarriers in treating breast cancer. Their mPEG-PCL carriers provided suitable pH-dependent delivery of therapeutics to breast cancer cells [92].
Establishing an immunological memory and provoking sufficient immune response are the two primary factors that determine the efficacy of a vaccine delivery system [93, 94]. The main administration routes of vaccine delivery systems are parenteral and non-parenteral. The first is administered using hypodermic needles inserted through subcutaneous, intramuscular, and intradermal routes [95, 96]. On the other hand, non-parenteral delivery systems capitalize on needle-free devices such as jet injectors, liquid, powder, and polymeric (including hydrogel) systems [97]. In hydrogel-based systems, gel particles encapsulate the vaccine molecules and deliver it through intramuscular, oral, and transcutaneous routes [98, 99]. In recent years, different hydrogel delivery systems were developed to increase the efficiency of the vaccine delivery, Table 2 summarizes these systems and their applications.
Hydrogel based system | Applications | References |
---|---|---|
Thermo-sensitive | H5N1 Influenza vaccination; Ebolavirus glycoprotein antigen; prevention of ovine brucellosis | [100, 101, 102] |
Capsules | Oligopeptide antigen delivery | [103] |
Bio bullets | Bacterial vaccines (Brucella Abortus strain RB51 live vaccine) | [104] |
Injections | Swine H1N1 influenza killed vaccine; fibroblast growth factor (bFGF); codelivery of immune check point inhibitor and tumor vaccine | [105, 106, 107] |
Nanogels and peptides | Adjuvant for the vaccine delivery systems for West Nile and respiratory syndrome viruses | [108, 109] |
Micro-scale particles | Oral delivery of bovine serum protein; intramuscular delivery of “transmission blocking malaria” vaccine | [110, 111] |
Gel patches | Tetanus and diphtheria vaccination | [112, 113] |
Micro-needles | Influenza vaccine; DNA vaccine against hepatitis B; Japanese encephalitis vaccine; and rabies vaccine | [114, 115] |
Hydrogel-based delivery systems and their applications.
Drug carriers are revolutionary delivery systems in the field of medicine. While there have been several studies that reported different types of polymers that has been used to synthesize the carriers, hydrogel-based systems seem to be very promising due to their affordability, production simplicity, and their unique ability to load different types of drugs. Although several gel-based systems have been investigated, designed and IP-protected, it seems only limited number of these product has actually reached the market, which indicates the need for further investigations on improving the performance of current products and develop new ones. This chapter addressed different hydrogel-based drug delivery systems from different perspectives including mechanisms (loading, releasing, and targeting), design (shape and route of administration), and the classes of delivery drugs. These elements are essential when designing and investigating state-of-the-art hydrogel-based delivery systems.
The author acknowledges the support of BK21 FOUR Program through the National Research Foundation of Korea (NRF), the Ministry of Education.
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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}}]}},subseries:{item:{id:"92",type:"subseries",title:"Health and Wellbeing",keywords:"Ecology, Ecological, Nature, Health, Wellbeing, Health production",scope:"\r\n\tSustainable approaches to health and wellbeing in our COVID 19 recovery needs to focus on ecological approaches that prioritize our relationships with each other, and include engagement with nature, the arts and our heritage. This will ensure that we discover ways to live in our world that allows us and other beings to flourish. We can no longer rely on medicalized approaches to health that wait for people to become ill before attempting to treat them. We need to live in harmony with nature and rediscover the beauty and balance in our everyday lives and surroundings, which contribute to our well-being and that of all other creatures on the planet. This topic will provide insights and knowledge into how to achieve this change in health care that is based on ecologically sustainable practices.
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