Showing the first-trimester biochemical predictors of GDM.
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According to the International Alzheimer’s Association (2015), it is estimated that there are approximately 46.8 million people with dementia in the world, and it is believed that this number will double every 20 years, reaching 74.7 million in 2030 and to 131.5 million in 2050. Therefore, it is calculated that every 3.2 seconds, a new case of dementia is detected in the world and a prediction for 2050 is a new case every second [2].
Alzheimer’s disease (AD) is characterized by several factors, such as the loss of cholinergic neurons, the formation of intracellular fibrillar tangles of the hyperphosphorylated tau proteins, and due to the abnormal processing of amyloid precursor proteins that causes extracellular deposition of βA proteins [3, 4]. Therefore, it is known as a progressive neurodegenerative disorder that is related to the individual’s age and causes gradual physical and mental decline resulting in death [5, 6].
Memory impairment is not always the main symptom presented in patients with Alzheimer’s disease [7]. Some patients may experience significant disturbances in the visuospatial or language functions [8].
This hypothesis suggests that the characteristic neurodegeneration of AD occurs due to the accumulation of beta-amyloid (βA) protein in several brain areas, triggering the formation of senile plaques and a series of neuron injuries related processes, and formation of neurofibrillary clusters of the tau protein, which lead to neuronal dysfunction and cell death (Figure 1) [10, 11, 12].
β-amyloid (βA) formation [
The deposition of senile plaques is a result of an abnormal processing of amyloid β protein, induced by errors in the proteolytic cleavage of amyloid precursor protein by β and γ secretases. This process results in the production of different fragments, which are: the β amyloid protein 1–42, highly neurotoxic and prone to aggregation, found in the brains of patients with AD; β amyloid 1–40, a soluble and less neurotoxic protein that contributes to local plasticity and is found in healthy brains; and the β amyloid protein 1–43, presenting high amyloidogenic and neurotoxic potential, capable of depositing before the other fragments. In AD patients, the proportion of neurotoxic forms is significantly higher than β 1–40 amyloid [10, 11, 12] Thus, the excess of βA- protein formed in the brain can trigger the formation of senile plaques, lead to inflammation, oxidative stress, hyperphosphorylation of the tau protein and, consequently, cause dementia (Figure 2) [10, 11, 12].
Simplified schematic of the amyloid cascade. Source: Personal file.
The Tau protein is strongly associated to the responsibility of stabilizing and connecting the microtubes of the axions and dendrites. Conformational modifications in these structures and the accumulation of amyloid fragments appear to be responsible for the hyperphosphorylation of the tau protein (Figure 3) [14].
Characteristics of tau protein [
The hyperphosphorylation of tau in AD begins primarily in the intracellular process with the sequestration of regular tau and other proteins associated to the microtubes, causing a structural failure and thus compromising the neuronal and synaptic function [15].
The hyperphosphorylation hypothesis is due to the fact that, after the phosphorylation, an insoluble filamentous product is generated, which possibly causes the deregulation of the cytoplasmic cascade of phosphorylation and dephosphorylations. There is also a relation that the aggregations of β-amyloid may be the activating event of the protein hyperphosphorylation (Figure 4).
Representation of the structural failure of neuronal microtubules and formation of tau protein tangles. Source: Personal file.
The metal hypothesis is based on the precipitation of β-amyloid by zinc and copper radicalization, ionic zinc and copper are capable of accelerating the aggregation of Aβ, the main component of the deposition of β-amyloid [16, 17]. This hypothesis is related to the disturbance of endogenous metals in the brain, the ionic zinc and copper probably act on the cortical glutamatergic synapse, modulating the response of the inotropic receptor activated by the glutamic acid (NMDA), which can explain the vulnerability of β-amyloid to the abnormal interaction with the metallic ions on the synaptic region, leading to the aggregation and causing toxicity [16]. The metals in the synapses can also lead to the formation of Aβ oligomers that have the role of modulating the long-term potentiation, which controls synaptic levels of the NMDA receptor, and this excessive accumulation of Aβ oligomers on the synaptic cleft affect the synaptic neurotransmission (Figure 5) [17].
Simplified scheme of the metal hypothesis. Source: Personal file.
The βA is one of the main mechanisms associated to Alzheimer’s disease, and it has two main alloforms, Aβ 1–40 and Aβ 1–42, the last with more toxic oligomers [18, 19]. Studies show that the soluble oligomers, unlike the plaques, are the main cause of the synaptic disfunction and neurodegeneration. Oligomeric soluble Aβ interacts with several proteins, such as NMDA glutamatergic receptors and some proteins responsible for the maintenance of glutamate homeostasis, such as absorption and liberation [18].
It was discovered that βA oligomers were seen as intermediates in the path of disease-causing fibrils instead of impelling fully developed conditions. After that, oligomers were reported as a possible cause of Alzheimer’s disease and neuronal death [20].
In the 2000s it was possible to understand that the βA fibrils are weakly toxic, but induce the neuroinflammation and, when agglomerating, they become dense and tend to detach and turn into oligomers. It is believed that currently βA oligomers exert their harmful effects connecting directly to the neuron membranes or to other specific receptors such as the insulin and glutamate (NMDA) ones, which are necessary for the neuronal signaling (Figure 6) [20].
Simplified scheme of the oligomeric hypothesis. Source: Personal file.
The glutamatergic hypothesis refers to the biggest excitatory system of the central nervous system, the glutamatergic system. In AD, as well as in other acute and chronic neurodegenerative diseases, the loss of neurons may be due to an excessive synaptic excitation mediated by the glutamate amino acid, which explains the other denomination of the hypothesis as excito-toxic [11].
The glutamatergic system includes ionotropic and metabotropic receptors, both activated by glutamate, but in this hypothesis the ionotropic receptors stand out, such as NMDA, α-amino-3-hidroxi-5-metil-4-isoxazolepropionic acid (AMPA) and kainate, which contain ionic channels related to the neuronal polarization and depolarization processes [11, 21].
The NMDA receptors are responsible for the control of ion conductance, and when activated they determine mainly the entrance of Ca+2, which increases the intensity and duration of the depolarization of the post-synaptic neuron, characterizing the long-term potentiation (LTP), which strengthens and shapes synapses, influencing phenomena such as learning and memory [11].
The activation of these receptors is essential, but in excess it can create pathogenic mechanisms related to neurodegenerative processes due to the calcium homeostasis, for when it is in high amounts in the intercellular medium, it can operate in the process of neuron degeneration and death (Figure 7) [21].
Simplified scheme of the hypothesis of glutamatergic dysfunction. Source: Personal file.
The importance of acetylcholine (ACh) in the learning process and memory is known since the 70’s, when studies showed a reduction of choline acetyltransferase (enzyme that synthesizes ACh) in the cortex and hippocampus, and less cholinergic neurons on Meynert’s basal nucleus in subjects with AD [11, 22].
It was demonstrated that substances that inhibit acetylcholinesterase (enzyme that degrades ACh) cause positive effects on the learning and spatial learning performance, due to an indirect activation of the cholinergic system [22].
In addition to that, it is been reported that the blocking of muscarinic and nicotinic receptors leads to cognitive deterioration, indicating the importance of two kinds of receptors in the mechanism of memory and learning (Figure 8) [23].
Simplified scheme of the cholinergic hypothesis. Source: Personal file.
Metabolically, the brain is one of the most active organs of the human body because it processes big amounts of carbohydrates to generate energy as ATP. The brain does not count with the possibility of turning different substrates into energy, therefore, there is a higher use of glucose, and in the event that this supply or the ability of metabolization are compromised, this organ tends to become unprotected, and synapses failures are likely to happen, resulting in cognitive alterations [24].
Insulin has an important role in memory processing, it is capable of crossing the hematoencephalic barrier and is also produced in the brain tissue. Patients with AD show reduced insulin concentration and a smaller number of its receptors. When this is corrected with pharmacological intervention, there is an improvement in the processes related to cognition [25].
Also, studies show that toxic effects of βA might cause resistance to insulin, and this process may lead to an accumulation of βA, which constitutes in a positive feedback associated to the progressive neurodegeneration process characteristic of AD (Figure 9) [25, 26].
Simplified scheme of the type 3 diabetes hypothesis. Source: Personal file.
Because there are only two classes of compounds commercially available for the AD treatment, and due to the failure of other approaches, several studies have been carried out in search of new therapies that are equally effective, safe, or better for treating the disease [10]. In this chapter, two forms of therapies that have been widely studied are discussed, namely: transcranial photobiomodulation (with LED) and treatment with antioxidants (Resveratrol).
The evaluation of clinical trials carried out on models of Alzheimer’s and/or dementia that were treated by Photobiomodulation using light emitting diodes (LEDs) and Resveratrol was performed.
It was carried out in accordance with the PRISMA recommendation, which consists of a checklist with 27 items and a flowchart in four stages that assist in the eligibility of the selected questionnaires and work development.
For the Transcranial Photobiomodulation approach, academic articles published between 2015 and 2020 will be selected in the following databases: Science Direct, PubMed PMC, Scopus, PubMed NCBI, SciELO, LILACS, MEDLINE e PEDro. The descriptors will be in the English language only: Alzheimer’s disease, light-emitting diode.
For treatments with Resveratrol, articles published between 2015 and 2020 will be selected and found in the following databases: Science Direct, PubMed PMC, Scopus, PubMed NCBI, SciELO, LILACS e MEDLINE. The descriptors will be in English: Resveratrol, Alzheimer’s, neuroprotection.
Eight and six articles were selected to Transcranial Photobiomodulation and Resveratrol, respectively, to elaborate the discussion of this work.
In a report of a series of cases on subjects with AD or mild to moderately severe dementia, Saltmarche et al. [27] investigated the effects of photobiomodulation by 810 nm LED. The sample was composed of 5 patients with moderate to severe AD. The therapeutic adopted was infrared photo-biomodulation by pulsed LED (810 nm, 10 Hz), the device placed transcranial and intranasally for 12 weeks. Were used Mini Mental State Examination (MMSE), Alzheimer’s Disease Assessment Scale (ADAS- cog) and statistical analysis, being investigated the effect of photobiomodulation on clinical dementia. The results suggested that significant improvement in dementia while presenting functional increase, improvement of sleep, and less outbreaks of anxiety as well as rage, and that this device can be used safely and that there were no adverse effects.
Chao [28] used 8 participants (mean age: 79.8 ± 5.8 years old) diagnosed with dementia. The patients were treated with intranasally photobiomodulation with the Vielight Neuro Gamma device three times a week for 12 weeks and analyzed by Alzheimer Disease Assessment Scale-cognitive subscale (ADAS-cog); Neuropsychiatric Inventory (NPI); Magnetic resonance. The results were based on cognitive and behavioral function, cerebral perfusion, and functional connectivity at rest. It was found that the therapy provided improvements in ADAS-cog and PNI, increased cerebral perfusion and the enhancement of the connectivity between the posterior cingulate cortex and the lateral parietal nodes in the network in a standard way. Furthermore, the therapy was well tolerated and not associated with any adverse effects, indicating potential use as a viable home treatment for patients with dementia and AD.
Purushothuman et al. [29] used 2 models of mice with AD, a tau model K369I (K3), containing 15 animals and the other βA model APPs/PSEN1dE9 (APP-PS1) containing 18 animals. The therapeutic adopted was light from the LED device (670 nm), cycles of 90s (4 J/cm2), 5 days a week, for 4 weeks, exposed 1 to 2 cm above the head. In relation the methods of analysis, they used histology by the Bielschowsky silver staining method, morphological analysis, histochemical analysis, and statistical analysis. Evaluating the effects on the cerebellar region, was observed that the positive effects of LED extend to the other brain regions; provoking a reduction of the neurodegenerative effects caused by AD in the cerebellum, such as the deposition of βA, neurofibrillary tangle formation and oxidative stress damage. So, in the findings of Purushothuman, LED was shown as an effective and safe alternative for treatment of neurodegenerative effects, being able to minimize and delay the pathological changes caused by dementia in different regions of the brain such as the hippocampus, neocortex and cerebellum.
Han et al. [30] used animal model APP/PSEN1, 30 female mice divided into 3 groups with 10 animals each: treatment group, positive control group, and negative control group. The therapeutic adopted was LED emitting infrared light for 6 minutes for a period of 40 days, and the animals were analyzed by the method of Morris Aquatic Labyrinth and the results by statistical analysis. The measured parameters were spatial memory and cognitive performance after treatment with LED. The results suggested that infrared therapy emitted by LED can improve the performance in spatial learning and memory capacity.
Han et al. [31] used animal model C57BL/6 J, being females divided into 3 groups: rats without irradiation (n = 10), rats with irradiation (n = 10), and normal rats without irradiation (n = 12). The therapeutic adopted was LED with wavelengths between 1040 nm and 1090 nm, power of 15 mW/cm2; 6 minutes a day, for 40 days, suspended for 28 days, and then starting the treatment again for another 15 days. The measured parameters were spatial memory and the presence of senile plaques after the LED treatment period. They found that LED is able of improving performance in spatial learning and moderately reduces senile plaques.
Eltchechem et al. [32] used 60 rats, 30 treated (GT group) and 30 in a control group (GC group). The treatment was with LED (627 nm 7 W/cm2, 70 mV) in the frontal region, one time every day for 100 s for 21 days. The methods of analysis were Morris Aquatic Labyrinth, Open field, histological analysis, immuno-histochemical analysis, and statistical analysis. The measured parameters were the βA deposits in the GT in relation to the GC with 7, 14 and 21 days after LED irradiation. The results found were better movement, exploration, and spatial memory of the GT in relation to the CG.
Yue et al. [33] used APP/PS1 AD model mice treated, APP/PS1 control mice and healthy C57BL/6 mice as a negative control. The treatment was with photobiomodulation by LED 630 nm with application of 40 minutes and light intensity of 0.55 mW/cm2 in the skull and abdomen 5 days a week for 2 months. The methods of analysis were Morris Aquatic Labyrinth, fluorescent microscopy; magnetic resonance; biochemical analysis and statistical analysis. It was observed destruction of βA plaques group and activation of the formaldehyde dehydrogenase enzyme, that degrades formaldehyde, which acts by accelerating the deposition of βA in the extracellular space and, consequently, attenuation of βA aggregation facilitated by formaldehyde. In addition, the light reduced βA deposition in the extracellular space, positively influenced the flow of interstitial fluids and recovered cognitive functions in AD mice.
Cho et al. [34] evaluated the effect of photobiomodulation using 610 nm LED on amyloid plaques, gliosis, and neuronal loss to prevent and/or recover cognitive functions and the ideal time to start therapy. 5XFAD AD model rats were used, divided into a group that started therapy at 2 months old, and another at 6 months old. The treatment consisted of the simultaneous application of light in two places (midpoint of the parietal bone and midline of the seventh cervical vertebra) for 20 minutes, 3 times a week, for 14 weeks. From behavioral tests, immunohistochemical analysis and Western blot, it was found in the initial stages the reduction of the accumulation of amyloid plaques, neuronal loss and microgliosis, and the relief of cognitive dysfunction.
Yin et al. [35] investigated if resveratrol could mitigate the early loss induced by βA in the neuron excitability in the hippocampus and the mechanism involved on it. The excitability and the potassium currents dependent on the pyramidal neuron CA1 voltage of rats were analyzed using the whole-cell patch-clamp technique. The authors discovered that resveratrol reverted the increase of βA peptide and the increase induced in the frequency of the repetitive shots, mitigated the decrease induced by βA in the transitory potassium channels, and rectified the delay on neuron potassium channels. Besides, it was shown that resveratrol decreased the levels of kinase A (PKA) and inhibited the activation of the signaling path PI3K/Akt.
Sarroca et al. [36] assessed the beginning and progression of the pathology of Alzheimer’s disease through a diet rich in fat (HFD) and the influence of resveratrol in this situation. Many evidences suggest that HFD increases the risk of Alzheimer’s disease (AD), but the molecular mechanisms through which the HFD causes its negative effects on the brain and the pathophysiology of AD are still widely unknown. The authors used wild mice (WT) and AD 5XFAD transgenic (5XFAD mice represent an aggressive model of AD due to the exposure to intraneuronal β-amyloid-42 in 1,5 months, extracellular amyloid plaques in 2 months, gliosis in 2 months, memory deficits in 4 months and neuronal loss in 9 months) treated with a control diet of HFD (60% kcal of fat) or HFD supplemented with 0,1% of resveratrol for 16 weeks. From the analysis of behavioral tests, glucose intolerance tests, preparation of tissue samples, coloring with Thioflavin-S, Western Blotting, and proteasome activity test, it was possible to observe that the results showed the resveratrol reduced the amyloid load aggravated by HFD in 5XFAD model (model of Alzheimer’s disease with a pathology of low tau protein), the analysis by Western Blotting showed thar the cortex tissue did not show modification in the levels of tau protein. However, HFD was responsible for inducing a significant increase in the levels of pTau in both WT and 5XFAD mice, and resveratrol indicated the ability to normalize the levels of pTau in both groups fed with HFD. Resveratrol also inhibited the amyloidogenic processing enhanced by HFD.
Ma et al. [37] reported that AD and diabetes mellitus (DM) usually coexist in patients because one increases the incidence of the other. In this context, the authors studied the neuroprotection induced by resveratrol in mice with DM and AD caused by the injection of streptozocin (intraperitoneal) and β-amyloid 1–40 (hippocampus). Through biochemical and immunological analysis it was demonstrated that resveratrol increased SIRT1 expression, inhibited memory damage, increased the levels of acetylcholinesterase (responsible for the hydrolysis of acetylcholine in cholinergic synapses), malondialdehyde (marker of oxidative stress), interleukin-1β and interleukin 6 (interleukin-1β acts in the hypothalamus stimulating the release of corticotrophin by the posterior pituitary gland and the corticotrophin acts on the anterior pituitary gland, releasing adrenocorticotrophic hormone, and interleukin 6 is responsible for the influence on the immunological responses, mediating the acute stage of the inflammation), and showed decreased levels of choline acetyltransferase (mediator of the synthesis of acetylcholine), superoxide dismutase (responsible for catalyzing the dismutation of the superoxide in oxygen and hydrogen peroxide, an important antioxidant defense), and glutathione (causes several antioxidants, neutralizes free radicals).
Corpas et al. [38] evaluated the neuroprotection effects of resveratrol in two groups of mice: non-transgenic control (NoTg) and AD transgenic model (3xTg-AD). Both groups were fed with a supplemented diet of 100 mg/kg from 2 months of age for 10 months. Using Western Blotting, behavior and cognitive tests and proteasome activity test, it was possible to analyze how resveratrol induced complete protection against memory loss and brain pathology in 3xTg-AD mice and induced a cognitive increase in healthy NoTg mice. It also reduced anxiety in both strains, reducing the presence of hippocampal βA and tau protein in 3xTg-AD. As for the proteostases analysis, an increase of the levels of the enzyme neprisilin was observed, being responsible for the degradation of β-amyloid, reduction of amyloidogenic secretase BACE1, increase of the levels of proteasome protein in both mice groups, vital role in the increasing of the adenosine kinase activated by monophosphate (AMPK) and the positive regulation of the SITR1 path.
Chen et al. [39] evaluated the levels of resveratrol in Tg6799 mice (transgenic model with five family mutations on Alzheimer’s disease). The mice were divided in a group treated with resveratrol (solution 0.5%, 60 mg/kg) and a control group (treated with saline solution). The treatment was administered orally, daily, for 60 days. To interpret the results, the tests performed were the open field test, Y maze test, Morris aquatic labyrinth test, coloring with Thioflavin-S, ELISA Aβ40 and Aβ42 and finally Western Blotting, demonstrating that resveratrol reduced the disposition of the amyloid plaques, β-amyloid levels of −42 and β-secretase levels. Resveratrol also reduced the expression of the amyloid precursor protein and its cleavage products. Besides, there was a behavioral improvement related to the spatial working memory, according to the Y maze test, and improvement on the spatial memory deficits, evaluated by the Morris aquatic labyrinth test. However, resveratrol did not influence the motor function.
Wang et al. [40] used AD model rats (by hippocampal injection of β-amyloid 1–42) to investigate the possible effects of resveratrol on the behavior of spatial learning, memory and synaptic plasticity, as well as changes on the expression and phosphorylation of SIRT1 of the protein connecting to the response element of cyclic AMP (CREB). In addition to the already accepted analysis, protein extraction and Western Blotting were also done, and it was shown that resveratrol reverted the spatial learning memory damage evaluated by the Morris aquatic labyrinth, and to investigate the underlying mechanisms of the neuroprotector effects of resveratrol on the memory and learning, the long-term potentiation (LTP) was registered in the CA1 area of the hippocampus. So, it was demonstrated that the Aβ1–42 hippocampal injection did not affect significatively the basal excitatory post-synaptic potential (fEPSP), while Aβ1–42 suppressed the induction of hippocampal LTP. In addition to that, resveratrol avoided reductions on the expression of SIRT1 and phosphorylation of the cyclic AMP response element connecting protein (CREB).
LED is a radiation of varying wavelength, not coherent and which is standing out in the field of medical treatment and phototherapy for being an alternative to the high cost of laser therapy [41]. The use of light with Low-intensity Laser Therapy or by Light-emitting Diode is called photobiomodulation [42] and among its functions, it is the stimulation of neural activity, that occurs through interaction with cytochrome c oxidase (unit IV of the mitochondrial electrons transport chain), which through a series of reactions, stimulates the ATP synthase enzyme to produce more ATP, improving brain function [27]. LED, however, emerged as an innovation in the field because it does not give off heat, is portable, is easy to apply, and is more durable when compared to other methods such as laser therapy (Figure 10) [27].
Simplified scheme of the action mechanism of photobiomodulation. Source: Personal file.
Recent advances in optogenetics and the development of microscale LED platforms have elevated the viability of phototherapy for use on target brain cells [43]. The method in the treatment of neurodegenerative diseases is under development, and studies show that this therapy can act on amyloid aggregates [44, 45].
Although biological effects of the light emitted by the LED have been reported for a wide spectrum of wavelengths, the research related to the effects on the Alzheimer disease has focused on the wavelengths in the region of the nearby infrared. This approach involves the tissue irradiation with a low intensity light and promotes protective effects on the central nervous system [46].
In this approach, the primary photoreceptors are the mitochondria, and there is evidence that the action is responsible for preserving and restoring the function of the neurons by their action on the mitochondrial cytochrome
Thus, both in animal models and in human patient trials, the treatment promotes satisfactory results. As for the studies described in the results and referring to those that used animal models, the photobiomodulation, with the different protocols tested, brought together some results. Results described in
Regarding the application places and treatment time in animal models, most of the studies focused on the transcranial application, except for the research by Yue et al. [33] who performed transcranial and abdominal application.
About treatment time, in general, irradiation protocols between 21 and 40 days were used, except in the study by Cho et al. [34] in which the treatment (both early and late) was carried out for 14 weeks, and represented a longer irradiation protocol, which differs from those established by other authors.
In relation to human patients, the effects were mostly focused and described on mental and cognitive performance states. It was observed that the therapy provided a significant improvement in dementia, and presented cognitive functional increase, sleep improvement and fewer anxiety and anger outbreaks [27, 28]. It has also provided an increase in cerebral perfusion between the posterior cingulate cortex and the lateral parietal nodules in the network in a standard way [28].
The locations of application and time of treatment in clinical research were similar. Both studies that involved human models reported the use of transcranial and intranasal photobiomodulation. The treatment time did not differ either. A twelve-week protocol was adopted, which the only difference was in the post-treatment follow-up, with a period of four weeks without treatment being observed in the research by Saltmarche [27].
As for safety in the human model, the treatment was described as well tolerated and did not induce any adverse effects. These results support the therapeutic potential for viable treatment (including home treatment) of patients with dementias. However, larger, and more controlled studies are still necessary. It is indispensable, for consolidating the therapy, to clarify the ideal irradiation parameters such as application time, active treatment, and follow-up, as well as the general efficacy and safety profile [27, 28].
Regarding considerations for future research, they should be carried out by following longer and not discontinued treatment protocols. As according to Saltmarche [27] a period of four weeks without treatment, after initiation, resulted in deterioration of the positive effects achieved with twelve weeks of active treatment, and it caused difficulties for patients and caregivers. Furthermore, the author describes that the movement of patients to the clinic for LED applications caused stress. Therefore, for future work, home treatment is expected, which is possible considering the facility and viability of the application if it is properly oriented and performed.
Finally, it is interesting to use standardized cognitive assessments that consider different aspects, such as quality sleep, communication and social interaction, reduction of anxiety, depression, and disturbing behaviors to cover most of the effects induced by photobiomodulation.
The importance of oxidative stress in AD has been increasingly recognized. Several studies have shown evidence that oxidative stress may contribute to the pathogenesis of AD through the formation of oxygen free radicals. Thus, the therapeutic focus has also been directed towards the use of antioxidants in the treatment of AD [10, 48].
Although antioxidants do not provide objective improvement in cognition, they can delay the natural evolution of the disease due to their supposed neuroprotective effect [48]. Polyphenols from food consumption plants have already been confirmed as neuroprotective compounds, including by a reduction on the aggregation of β-amyloid protein, such is the case of the trans-3,5,4′-trihydroxystylbene, Resveratrol [12].
Resveratrol is widely found in grapes used to produce red wine and in cereals and has been tested in different models of the disease (
Among its different proven forms of action, the following stand out: (a) competition with coenzyme Q to reduce the oxidative complex, the site of production of reactive oxygen species (ROS); (b) neutralization of oxygen free radicals formed; and (c) inhibition of lipid peroxidation induced by Fenton reaction products, in the mitochondria (Figure 11) [49].
Effects of resveratrol already proven. Source: Personal file.
In view of its ability to modulate potassium channels, Resveratrol plays a promising activity to attenuate neural impairments induced by β-amyloid. However, as the antioxidant has shown a variety of neuroprotective actions, it is also possible that other signals are involved, such as other ion channels, e.g., calcium and sodium channels, which can be exploited in the future to elucidate the effects achieved by Resveratrol due to the relationship with certain central nervous systems disorders [35].
Regarding the in vivo studies, the effects of resveratrol were already expressed and described in different ways, and among them the ones of note are reduction of amyloid load and inhibition of the amyloidogenic processing [37, 38, 39], neuroprotection of memory loss, cognitive improvement and acetylcholinesterase inhibition [38, 39], anxiety reduction, increase on the AMPK levels [36, 39], positive regulation of the SIRT1 path [37, 38, 39, 40] and reversion of the damage on spatial memory [39, 41].
As a future perspective, based on the neuroprotectant activities observed in vitro and in vivo, it is expected that clinical trials are done with long term treatments and low formulations with improved pharmacokinetic properties (due to the low availability shown) to sustain the possibility of a therapeutic alternative for the treatment of AD, as well as the clarification of its mechanisms of action, safety and efficiency.
Thus, it is concluded that both the treatment with Transcranial Photobiomodulation using LEDs as light sources, and the treatment with Resveratrol have numerous benefits that can be useful in the treatment of AD. However, there is a need for new research that covers interventions with greater specificity and control, so that the ideal doses and treatment protocols are defined.
Norman Freinkel once told that “No single period in human development, provides a greater potential (than pregnancy) for long – range ‘pay – off’ via a relatively short – range period of enlightened metabolic manipulation”.
During pregnancy, the body systems of the woman, must support nutrient and oxygen supply for the proper growth and development of the foetus and subsequently during lactation. Inability to adopt the changes in maternal physiology may lead to complications, such as gestational diabetes mellitus (GDM). The International Association of Diabetes and Pregnancy Study Groups (IADPSG) shows that, GDM may complicate 15–20% pregnancies, and has increased in the last 20 years in all ethnic groups as much as 27% [1].
GDM originates from interplay of factors like specific gene mutations, dysregulation of placental hormones and β-cell injury, favored by advanced age, gynecological alterations and diabetogenic factors. GDM mostly develop after the 2nd trimester of pregnancy, between the 24th and the 28th week of gestation. GDM may precipitate serious and long-term complications for foetal and maternal health, in particular, metabolism and cardiovascular in nature [2].
Currently, in most cases, the diagnosis of Gestational Diabetes Mellitus (GDM) is done around the late phase of second trimester, which may expose the foetus to the hazards of intrauterine metabolic alterations and also epigenetic changes for the period of exposure. Many documented evidences indicate that the metabolic alterations may subject the new born vulnerable to many long-term pathologies. Detection and management of GDM in pregnancy, can reduce the frequency of adverse pregnancy outcome. Hence, we need to predict and identify GDM earlier in pregnancy even if possible before the pregnancy, in order to limit the exposure to impaired glucose metabolism.
American Diabetes Association (ADA) recommends initial screening for GDM at 24–28 weeks [3]. But Seshiah V et al. from India has detected 62.1% cases of GDM before 24 weeks. Moreover, if we do not test before 24 weeks, we will miss earliest intervention for all the cases of undetected diabetes existing before pregnancy [4].
The aim of this review was to find out the useful and possible markers or guides to detect GDM early in pregnancy before rise of blood sugar and if possible, even before pregnancy to avoid all complication for mother and child arising from effects of GDM on gestation.
References for this review were identified by searching PubMed, Embase for articles in English with no language restrictions for articles published mainly from 2000 to 2021. The search terms used were GDM biomarkers, GDM pathogenesis, GDM prevention and epigenetics of GDM. The final reference list was prepared based on this search, supplemented with references from the authors’ own dataset.
GDM develops when beta cell dysfunction coexists, and is complicated by further abnormalities in adipokine and cytokine profiles, increased free fatty acids (FFA), triglycerides (TG), low vitamin D and endothelial dysfunction. The identification of early biomarkers in pregnancy, who may develop GDM, may lead to an improved understanding of pathogenesis of GDM. Combination of biomarkers and different risk factors into a predictive model, may help in early prediction of GDM. This may also find out effective prevention strategies and finally can limit different complications related with GDM. The first-trimester biochemical predictors of GDM are shown in Table 1.
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Showing the first-trimester biochemical predictors of GDM.
Metabolic alterations like impaired glucose control during the phase of foetal development, may result in functional and structural alterations in the developing foetus, and may result in a predispose to the development of chronic metabolic diseases in future life. These alterations are actually the ‘foetal programming’ and may trigger epigenetic changes [5]. The epigenetic changes are considered as different changes in the biochemical structure of DNA, which alters the gene expression in pregnancy as shown in Table 2.
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Showing the epigenetic changes in pregnancy.
Maternal insulin resistance can also cause insulin resistance in the foetus [6]. Multiple studies have correlated maternal GDM, with the development of obesity and T2DM in children who are eight times more prone to develop T2DM than non-GDM children [7, 8]. This raises the strong need for early detection of GDM preceding the hyperglycaemia which might avoid subsequent harm.
Now a days, more and more women are becoming pregnant, being either overweight or obese. The obese women show a three-fold risk for developing GDM. The global increase in GDM at present time is largely due to the on-going pandemic of obesity. Obesity is related to an altered production of proinflammatory cytokines from the adipocytes, which may lead to a state of chronic low-grade inflammation. It acts upon the expression and production of different proinflammatory cytokines e.g., TNF-alpha and IL-6 and also many anti-inflammatory cytokines. This also produces adipokines e.g., adiponectin, visfatin and leptin etc. Adipokines can modify insulin secretion & sensitivity, appetite, energy control and inflammation. Sound relationship is evident between obesity, chronic low-grade inflammation and development of T2DM. The normal pregnancy shows a balance between the productions of pro-inflammatory and anti-inflammatory cytokines.
Pregnancies in obese women, further may aggravate the proinflammatory markers and may lead to an imbalance and possible complications. It is now accepted that inflammation is also an associated feature of GDM [9]. During GDM, the increased production of proinflammatory cytokines disturbs the insulin signaling [10]. A down regulation of adiponectin and anti-inflammatory markers such as IL-4 and IL-10 and an enhanced production of proinflammatory cytokines such as IL-6 and TNF-α are usually observed in GDM [11].
Adiponectin is actually an adipocyte protein and consists of anti-atherogenic, anti-inflammatory and also insulin-sensitizing effects [12]. Adiponectin is inversely correlated with the clinical conditions like hypertension, dyslipidaemia, obesity and also coronary artery disease. Diminished level of adiponectin are usually seen with an increased risk of T2DM [13]. During the normal pregnancies, adiponectin decrease progressively also, probably from a decrease in insulin sensitivity [14]. Many studies have indicated that reduced adiponectin levels during 24–28 weeks in GDM compared to non GDM women, probably corelate low levels of adiponectin with onset of insulin resistance and diminished beta cell function [15, 16]. In one study, adiponectin concentrations in 560 GDM patients and 781 controls revealed a significantly decreased adiponectin level in GDM patients vs. controls [17].
Adiponectin, an adipokine having anti-inflammatory, anti-atherosclerotic and insulin-sensitizing proprieties in another study, was constantly lower along the 1st–3rd trimester of GDM gestations [18]. Hypoadiponectinemia increases the risk of developing GDM by 4.6 times [19], and is inversely correlated with the insulin resistance, BMI and leptin [20]. The ratio of plasma adiponectin and leptin (< 0.33) is also considered as predictor of GDM as early as the period of 6th to 14th week of pregnancy [21]. But probably the assessment of the high molecular weight oligomeric-adiponectin may give better results [22].
Recent prospective studies have addressed the role of adiponectin as a possible early predictor of GDM. Lower levels of adiponectin in the first trimester of pregnancy are associated with a greater risk for developing GDM. This suggests that a down regulation of adiponectin may be a predictor of GDM [23]. In a systematic review and meta-analysis, adiponectin had a moderate effect for predicting future GDM [24]. Again, a case–control study found revealed that low adiponectin levels in pre-pregnancy period is associated with an increased risk of 5.0-fold for developing GDM [25].
This association was significant even when adjustment of known risk factors for GDM was done. This is important as it can identify a group of high-risk women, who might be not detected by conventional tests. Therapy with adiponectin in animal models of obesity improves glycaemia and also can reduce hyperinsulinaemia without any changes in body weight [26].
To summarize, a lower level of adiponectin is seen with type 2 diabetes, obesity and GDM. Adiponectin may influence the pathophysiology of GDM and also be a promising predictive biomarker for identifying GDM. Subsequent research for lifestyle interventions or adiponectin therapy should be done to finalize the role of adiponectin and diagnostic ability in cases of GDM particularly during the first trimester of GDM. Serum adiponectin in GDM, when is below <8.9 μg/ml shows an odds ratio of 3.3.
Mean value of 1,5 Alfa anhydroglucitrol level is significantly lower in those destined to develop GDM. In the first trimester, higher SHBG levels are indicating the risk of GDM but this was no longer statistically significant when BMI, ethnicity and family history were considered. A measurement of CRP in the first trimester is not a useful marker of GDM [27].
Leptin is an adipocyte-derived hormone, mostly produced by adipocytes but is also produced in ovaries and the placenta. It regulates energy balance through hypothalamic pathways. Increased leptin is associated with weight gain, obesity and hyperinsulinaemia.
Leptin is a proinflammatory adipokine and participate in immune responses. It also affects glucose metabolism by antagonistic action on appetite and insulin action. In addition, it can stimulate oxidative stress, atherogenesis and arterial stiffness [28]. Leptin levels is detected to be significantly higher in the 2nd half of pregnancy in both normal and overweight women with later diagnosis of GDM [29]. Menon M et al. did a prospective observational study with three study groups, with two-time points-first and second trimester to detect gestational diabetes mellitus as follows: [30]
Normal glucose tolerance (NGT)
Gestational diabetes mellitus 1 (GDM1), OGCT done at 1st trimester patients diagnosed as GDM in 1st trimester
Gestational diabetes mellitus 2 (GDM2), Repeat OGCT done at 2nd trimester patients diagnosed as GDM in 2nd trimester.
They found that found that out of the adipokines, leptin was found to be elevated in GDM2 compared to GDM1 and NGT group with a p value (0.11), adiponectin was reduced only in GDM1 group with p value (0.33), TNFα is almost the same in all the 3 study groups but IL-6 is elevated in first and second trimester GDM group.
Maternal leptin levels increase 2 to 3 times in pregnancy, as a placental secretion. Increased levels of leptin have been seen in GDM.
Inflammatory markers like IL-6 and TNF-α also are involved in the pathophysiology of GDM by promoting both the chronic low-grade inflammation and also leptin concentrations. A prospective study detected elevated values of leptin before 16 weeks of conception, regardless of presence of adiposity and this was accompanied by an increased risk of GDM [31]. In another study leptin was increased in all pregnant women, but with highest concentrations in obese GDM patients [32]. But due to confounding effects of the measures of adiposity, current evidence is limited. Leptin is probably involved in the pathophysiology of GDM but is a poor predictor of GDM.
Visfatin an adipokine mostly secreted from visceral fat. It possesses both endocrine, paracrine and autocrine effects. Increased level of visfatin is noted in obesity, metabolic syndrome and T2DM. During pregnancy, visfatin levels increase up to the 2nd trimester, then they decrease and persist in lowest concentrations in the third trimester. During GDM, studies on visfatin levels are is inconsistent, as both decreased and increased levels have been reported [33].
In addition to its insulin-like properties to bind to the insulin receptor-1 and promotion of hypoglycaemic effects, visfatin can activate NFκB signaling and chemotaxis and lead to the development of insulin resistance. In fact, visfatin was found increased at the late 1st trimester [34], but differentially expressed at the 3rd trimester of GDM [35].
One study observed, visfatin was better in the prediction of GDM in the first trimester than CRP, IL-6, adiponectin and leptin [36]. One case–control study found that, visfatin in the 1st trimester was higher in GDM, but when it was added to the other maternal risk factors, the GDM detection rate had no improvement [37]. At present, findings indicate that visfatin is a potential biomarker for GDM, but we need further prospective studies to further asses the relationship between visfatin and GDM.
Resistin represents an adipose-derived hormone and is expressed from monocytes, macrophages and adipocytes. It is corelated with high LDL-c and pro-inflammatory molecules and is also positively associated with adiposity. It increases during pregnancy, probably from weight gain. A potential link might exist between resistin, adiposity and insulin resistance during pregnancy, but till now, remains inconclusive as because of conflicting reports from case–control studies [38]. Resistin, is found to be reduced or unchanged during GDM [39, 40].
But, nested case–control studies, investigating resistin levels in early pregnancy, found no differences in resistin levels between GDM and controls (adjusted for BMI) [41]. Currently, there is no solid evidence that resistin is involved in the pathophysiology or prediction of GDM.
Omentin-1, is an adipokine produced in non-fat cells from the adipose tissues (stromal vascular cells). It is involved in vascular tone relaxation due to the production of endothelial nitric oxide and lowering of both hs-CRP and TNFα signaling [42]. Omentin-1 was lower at the 2nd trimester of GDM similar to adiponectin, and in contrast to IL-6 [43].
Hungarian study reported that fasting serum ghrelin levels were lower in women with GDM compared to non-pregnant healthy controls and pregnant controls without GDM in the 1st trimester and 3rd trimester [44].
TNFα a proinflammatory cytokine produced by monocytes and macrophages affects insulin sensitivity and secretion. These occurs from impairment of B-cell function and insulin signaling and results in insulin resistance and possibly GDM [45]. Multiple studies showed increased maternal TNFα levels in GDM, predominantly during late pregnancy [46]. Increased TNF-α levels in GDM than controls have been shown. Subgroup analysis detected this relationship to remain significant when they are compared with BMI-matched controls [47].
These increased levels are due to increased oxidative stress and inflammation arising from impaired glucose metabolism [48]. A small case–control study 0f 14 cases and 14 controls to address the predictive value of TNFα found no differences between women with GDM and without [49]. In one study of GDM and controls, TNFα levels measured pre-gravid, at 12–14 weeks and 34–36 weeks were increased at 34–36 weeks of gestation. These were inversely correlated with the insulin sensitivity [50]. We need more prospective studies to assess the predictive value of TNFα during GDM, with due adjustment for measures of adiposity.
IL-6 is one of the proinflammatory cytokines and is increased in obesity and associated with indices of adiposity and insulin resistance, such as body mass index (BMI). The relationship between IL-6 and insulin action appears to be regulated via adiposity. However, in a case–control study, plasma IL-6 levels were elevated when adjusted for BMI in women with GDM [51].
Wolf and co-workers had found that the first-trimester CRP levels were significantly raised among them who later on developed GDM than the control subjects (3.1 vs. 2.1 mg/L, P < 0.01) [52]. After the adjustment for age, race/ethnicity, blood pressure smoking, parity, and age at gestation at CRP sampling, the increased risk of developing GDM among women was seen in the highest tertile than the lowest tertile and was 3.6 times higher (95% CI: 1.2–11.4). But when adjusted for BMI, this relation was not seen anymore. But Berggren and co-workers examined whether first-trimester hs CRP could predict the third-trimester impaired glucose tolerance (IGT). The hs CRP was positively correlated to (hs)CRP and GDM appears to be partly mediated by BMI.
Another study found that elevated plasma insulin and reduced adiponectin levels during first trimester may improve GDM identification rates than by clinical factors alone [53]. Maternal risk factors alone offer a prediction rate of 61% for GDM, but addition of adiponectin and SHBG, improved detection rates to 74% [54].
O’Malley E G et al. found that, both the serum insulin and C-peptide levels in the third tertile were correlated with GDM development (p < 0.001 if adjusted for maternal obesity). Higher values of ghrelin were showing a lower odd of development of GDM, even after adjustment for maternal obesity. The conclusion of the study was though 3 of the 10 biomarkers were statistically indicating an increased risk of GDM, but the presence of large overlap in values between women with normal and abnormal glucose tolerance reflect that the biomarkers (alone or in combination) were not clinically helpfull [55].
Li et al. compared 379 women in the first trimester who developed GDM subsequently with 2166 healthy women. They found that lipid profile was different between the groups. The GDM patients had higher concentrations of Triglyceride, LDL-Cholesterol and total cholesterol but lower concentrations of HDL [58]. The lipid values at first trimester in the cohort of Correa et al. was altered even when glycaemia and glycated hemoglobin were normal. The first trimester insulin concentration was seen to be also higher in women who developed GDM. Both theses indicate that there is a role of lipid metabolism in the pathogenesis of the disease [59].
Placenta-Related Factors such as sex hormone-binding globulin, afamin, fetuin-A, fibroblast growth factors-21/23, ficolin-3 and follistatin, or specific micro- RNAs may be involved in GDM progression and may help in its recognition [60].
In GDM, some adipose-derived factors such as TNFα, visfatin, omentin and FABP4 may be also expressed and expressed from placenta, resulting to their elevated plasma levels [10]. The sex hormone binding globulin (SHBG) from placenta acting as a regulator of sex steroid hormones had been linked with inversely insulin resistance, metabolic syndrome, obesity and T2DM [61]. A lower level of plasma SHBG in the 1st trimester was a true biomarker for GDM [62, 63].
Nanda et al. showed reduced SHBG in parallel to adiponectin in GDM during 11–13th week of pregnancy, in presence of previous macrosomia, BMI > 30 kg/m2, and family history of DM [63, 64]. Similarly, an hepatokine promoter of insulin resistance, known as fetuin-B, is raised at the 3rd trimester of GDM, but returns after delivery [65]. Again, at the late 1st trimester, a reduction of plasma fetuin-A levels (and elevated hs-CRP) is also noted [66].
FGF-21, responsible for browning of white adipose tissue and an upstream effector of adiponectin, was increased in GDM at the 24th week of gestation [67]. Afamin, a glycoprotein member of the albumin family found in liver and placenta, may be a first trimester biomarker for pathological glucose and lipid metabolism [68].
The decreased levels of ficolin-3 (an activator of the lectin pathway of the complement system expressed in liver and placenta) and the increased ratio of ficolin-3/adiponectin are predictive of GDM at the 16–18th week of gestation [18]. Follistatin, a gonadal regulator of follicular-stimulant hormone and activin-A, having angiogenic, anti-inflammatory and cardioprotective properties, were lower in the 3rd trimester of GDM pregnancy [69].
The non-coding RNAs such as micro-RNAs (miR) can be released from placenta to maternal circulation as early as the 6th week of gestation and may be involved in placenta development, insulin signaling and cardiovascular homeostasis [70]. These miR can regulate trophoblasts proliferation, apoptosis, migration and invasion, and angiogenesis [71].
A significant downregulation of miR-29a, miR-132 and miR-222 had been reported in plasma at the 16th week of pregnant women who developed GDM [72]. Similarly, during the 7th–23rd week of gestation, elevated plasma levels of miR-21-3p were seen with GDM [73].
SHBG a glycoprotein regulates the transport of sex hormones. In vitro, this is a marker in insulin resistance as insulin and insulin-like growth factor inhibit SHBG secretion. Indeed, a relation of low levels of SHBG and T2DM has been observed [74]. A study found its concentrations to be significantly lower in GDM [75]. Moreover, women treated with insulin showed even lower SHBG levels. Probably SHBG may help to differentiate or predict who will require insulin therapy or not.
A prospective study evaluated several biomarkers before 15 weeks of gestation and observed that low levels of SHBG were indicating an increased risk of GDM. Adding hs-CRP increases the specificity to 75.46% [76]. However another prospective cross-sectional study, revealed that low levels of SHBG assessed between 13 and 16 weeks of gestation were positively associated with the development of GDM (n = 30) (P < 0.01) [77]. A case–control study also found that SHBG in the non-fasting state in first trimester had a consistent association with an increased GDM risk [78].
AFABP or Adipocyte fatty acid-binding protein may be one of the risk predictors for cardiovascular disease, metabolic syndrome and T2DM [79]. Two studies have established its increased levels in GDM. Gestational diabetes mellitus causes changes in the concentrations of adipocyte fatty acid-binding protein and other adipo-cytokines in cord blood [80, 81]. Studies investigating the predictive value of AFABP in GDM have not been performed to date, however.
The fatty acid-binding protein 4 (FABP4) correlates with obesity markers e.g., fat mass and high BMI. FABP4 act on lipid and glucose metabolism via fatty acid transport and uptake [82]. The retinol-binding protein 4 (RBP4) is one of the circulating retinol transporters and id correlated with cardiometabolic markers in inflammatory chronic diseases like T2DM, metabolic syndrome obesity, and atherosclerosis process [83]. Higher levels of FABP4 can predict GDM from the 1st and 3rd trimester of [84, 85]. Upregulated values of plasma RBP4 in the 1st and 2nd trimester may modestly indicate GDM risk, especially among women with obesity and advanced age [18, 86].
Growing evidence suggests the use of SNPs, DNA methylation, and miRNAs as biomarkers that could help in the early detection of GDM. In presence of their potential, these molecular biomarkers pose several challenges that need to be addressed before they can become clinically applicable [87].
Decreased levels of first trimester pregnancy-associated plasma protein A (PAPP-A) and increased levels of second trimester unconjugated estriol (uE3) and dimeric inhibin A (INH) were associated with GDM [88].
Lower levels of vitamin D have been seen in both obesity and type 2 diabetes and also in pregnancy very often. Low levels of Vitamin D levels during first trimester also carry a higher risk for GDM as seen in recent meta-analyses [89]. As the mentioned studies all were not randomized controlled studies, we need future RCTs to confirm the predictive role of vitamin D [90].
Zhao et al. studied maternal blood prospectively from pregnant women at 12–16 weeks of pregnancy. Among these, 30 women were subsequently diagnosed with GDM at 24 to 28 weeks and were selected as case studies along with 30 normoglycemic women as controls. They found that, four proteins, apolipoprotein E, coagulation factor IX, fibrinogen alpha chain, and insulin-like growth factor-binding protein 5, with a high sensitivity and specificity, may provide effective early screening for GDM. The panel of four candidate proteins could distinguish women subsequently developed with GDM from controls with high sensitivity and specificity [91].
For the first time, Ding M et al. detected 8 variants to be associated with GDM, They are rs7957197 (HNF1A), rs3802177 (SLC30A8), rs10814916 (GLIS3), rs34872471 (TCF7L2), rs9379084 (RREB1), rs7903146 (TCF7L2), rs11787792 (GPSM1) and also rs7041847 (GLIS3). They also confirmed 3 other variants e.g., rs1387153 (MTNR1B), rs10830963 (MTNR1B), and rs4506565 (TCF7L2), which had been earlier identified by them or significant association with GDM risk [92].
The study of urine metabolome profile in GDM during the 3rd trimester found relation of 14 metabolites with the steroid hormone biosynthesis and tryptophan metabolism, which were significantly high. They are l-urobilinogen, l-tryptophan, 21-deoxycortisol, cucurbitacin-C, ceramide (d18:0/23:0) and aspartame [93]. Upregulation of these pathways could aggravate insulin resistance and respond to oxidative stress and inflammation during GDM. Earliest at 12th–26th week of pregnancy, augmented levels of AHBA, 3-hydroxybutanoic acid (BHBA), valine, alanine, serotonin and related metabolites like l-tryptophan levels were observed in urine (and plasma) from GDM mothers [94].
Clinical risk prediction models’ wave has been investigated in GDM. For example, the development of GDM can be predicted from the ethnicity, family history, history of GDM and body mass index. One large prospective study (n = 7929), found that, based on BMI, ethnicity, family history of diabetes and past history of GDM, there was a sensitivity, specificity and AUC of 73% [66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], 81% [80, 81, 82] and 0.824 (0.793–0.855), respectively, for the identification of GDM patients who required insulin therapy [95].
The introduction of biomarkers if added to a set of clinical risk factors are supposed to increase the predication rates of GDM. In particular, low HDL cholesterol and tissue plasminogen activator (t-PA) appeared as independent significant predictors of GDM. The addition of these 2 biomarkers to a group of clinical and demographic risk factors enhances the ROC (area under the curve) from 0.824 to 0.861 [96]. The t-PA not only is a predictor of GDM, it is also associated with a higher risk of T2DM [97].
Addition of maternal adiponectin and visfatin to a bunch of maternal risk factors, reached a detection rate of 68% [98]. The clinical implementation of these multi-parametric prediction models is determined by factors like practical acceptability, significant reduction in adverse pregnancy outcomes and cost-effectiveness. But these models need prospective validation studies and also further identification of predictive threshold values for the said biomarkers.
In one study, women with GDM (n = 96) were matched to women with NGT (n = 96) by age, BMI, gravidity and parity and the levels of 91 metabolites measured. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were found to have significantly different levels between the two groups in conditional logistic regression analyses (p < 0.05). Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM [99].
Endogenous galanin as a novel biomarker to predict gestational diabetes mellitus is also observed [100]. The higher level of galanin observed in GDM may represent an adaptation to the rise of glucose, weight, GGT associated with GDMs thriving for clinically useful thresholds [101].
Mean 1,5 AG levels are significantly lower in those that go on to develop GDM. Hs-CRP and SHBG are important early predictors of GDM. Adding SHBG to hs-CRP improves specificity and serves good overall accuracy. Uric acid, creatinine and albumin have no role in GDM prediction [102].
Bivariate logistic regression analysis had shown that both adiponectin and insulin highlight future development of gestational diabetes. Both of them measured at 11 weeks, may predict oncoming GDM. But we need further studies to assess the reliability of these biomarkers [103].
Placental growth factor (PLGF), a vascular endothelial growth factor-like protein, is highly expressed in the placenta. About three studies suggest that higher early pregnancy PLGF levels are associated with GDM [104, 105, 106]. Recently, ALT, a liver enzyme, a marker of hepatocellular damage, has been examined as a first-trimester predictor of GDM [107].
One moderate-sized study (N = 182) showed that glycosylated fibronectin measured in the first trimester could predict GDM with high accuracy [108]. Watanabe et al. assessed the soluble (pro)renin receptor levels in 716 Japanese women at less than 14 weeks of gestation and found increased levels in women who developed subsequent GDM [109]. In a case–control study of 1000 women from the UK, Syngelaki et al. found that maternal serum TNF-alpha measured at 11–13 weeks gestation was associated with subsequent GDM [110].
Donovan et al. in their study, indicated that women diagnosed with GDM have lower first trimester levels of both pregnancies associated free β-hCG and plasma protein-A (PAPP-A) than normoglycemic pregnant women. These two markers may indicate the presence of abnormal glucose metabolism at the beginning of pregnancy and may help for identification of future development of GDM [111].
Tenenbaum-Gavish et al. in a cohort of GDM group found that, compared to the normal group BMI and insulin (P = 0.003) were higher (both P < 0.003). The soluble (s)CD163 and multiples of median values of uterine artery pulsatility index (UtAPI) were high (p for both <0.01) but, pregnancy associated plasma protein A, tumor-necrosis factor alpha and placental protein 130, were low (p for all <0.005). There was no significant difference between the groups in placental growth factor, leptin, interleukin 6, soluble mannose receptor or peptide YY. For screening GDM in obese pregnancy a combination of high BMI, TNFα, insulin and sCD163 reached an AUC of 0.95, and the detection rate of 89% with a 10% false positive rate. For nonobese pregnancy, the combination of TNFα, PP13,sCD163 and PAPP-A showed an AUC of 0.94 and the detection rate was 83% at 10% false positive rate [112].
By blood sugar estimation when GDM is diagnosed, adverse foetal changes have already set in. So, we will have to attempt to diagnose GDM, before the foetal changes take place. It would be more rewarding if we can diagnose impending GDM and alert the person even when she plans for pregnancy.
Different biomarkers e.g., glycemic, insulin resistance, inflammatory, adipocyte and placenta-derived, had been evaluated as the first-trimester predictors of GDM. The majority of these studies are smaller in size and was based on case–control designs. But some large studies of glycemic markers indicated that hemoglobin A1C and/or fasting glucose help in detecting women without diagnosis of previous diabetes and they may be benefited from early detection and treatment of GDM, though these observations should be confirmed by interventional studies.
The improvement of GDM development and outcomes is possible by earlier and more specific identification of GDM accompanied by metabolic and cardiovascular risks. In line with these, first or second trimester-related biomarkers seen in maternal plasma like adipose tissue-derived factors like adiponectin, omentin-1, visfatin, fatty retinol binding-protein-4 and acid-binding protein-4 reflect correlations with development of GDM. In addition, placenta-related factors e.g., sex hormone-binding globulin, afamin, fetuin-A, ficolin-3 and follistatin, fibroblast growth factors-21/23 and specific micro-RNAs may be important in detecting progression of GDM and its recognition. Finally, urinary metabolites related to non-polar amino-acids and ketone bodies, serotonin system, may help in completing a predictive or early diagnostic group of GDM biomarkers.
To transform the observations obtained from observational studies into clinical practice, we need also more clinical trials or cost-effectiveness analyses of screening and treatment c.onsidering the first-trimester biochemical GDM predictors. Further studies should examine the first-trimester biochemical markers for adverse outcomes in GDM by prospective trials to find its prevention or early treatment.
GDM involves a significant proportion of pregnant women and is becoming more prevalent as rates of obesity rise globally. Its development and complications could be arrested if accurately predicted in early pregnancy even if possible before conception and effective interventions initiated. Many Several biomarkers have been studied to understand pathogenesis of GDM, but till date none are showing adequate robustness to be used for clinical algorithms for prediction of GDM.
Application of the high methodologies gives novel insights about the role of genetic variants, metabolomics and epigenetics regarding the pathogenesis of GDM. This option for using a predictive model during the subclinical phase of GDM appears to be promising as an important arena of future research and development. These modern technologies are off course complex and not applicable to mass level screening. There are also issues related to validity across populations, reproducibility, and selectivity. We will have to find out methods with cost-effectiveness and universal access, otherwise the present complex biomarkers are likely to prove invaluable in the diagnosis of GDM.
The emerging evidences suggest that the assessment at eleven and thirteen weeks of gestation, should be the platform towards a new approach in antenatal care. The data from the maternal history should be added to the results of biochemical and biophysical tests to examine the patient-specific risk related to a wide variety of pregnancy complications. Ideal GDM biomarkers appears to be a combination of several molecular biomarkers to balance the lack of sensitivity and specificity of individual factors. But targeted rapid technological advances will overcome these challenges and develop a quick, cost-effective point-of-care test that can accurately identify women at high risk for GDM during early pregnancy even if before conception.
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\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
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\n\nIntechOpen requires:
\n\nCONFLICT OF INTEREST - AUTHOR
\n\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
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\n\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"4",type:"subseries",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. 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