**Qing Ni**

Qing Ni received an M.S. degree in mechanical and electrical engineering from the University of Electronic Science and Technology of China in 2019. In 2022, she submitted a Ph.D. thesis about machine condition monitoring from the University of Technology Sydney (UTS), Sydney, Australia. Her main research interests include fault diagnosis, machine learning, signal processing, and machine condition monitoring.


**4.2 Blood glucose estimation**

Plasma glucose estimation has high intraindividual biological variability (4– 14%). This is accounted for by method of sample collection and storage, lifestyle measures while preparing for sample collection like exercise, calorie restriction and difficulty in ensuring fasting state. About 3-8 mg/dl/hr. of glucose is lose in a sample kept at room temperature. Therefore, in interpreting blood glucose test result, the

need to be conversant with causes of intraindividual and interindividual variation of blood glucose is necessary. Such variability can be grouped as

**4.3 Specimen for glucose estimation**

*DOI: http://dx.doi.org/10.5772/intechopen.96549*

Glucose can be measured in whole blood, serum, or plasma, but plasma is recommended for diagnosis. It can also be measured in capillary, venous or arterial blood. It is essential that in a repeat sampling for confirmation of blood glucose result, the same type of sampling used previously must be use. The molality of glucose (i.e., amount of glucose per unit water mass) in whole blood and plasma is identical. Although red blood cells are essentially freely permeable to glucose, the concentration of water (kg/L) in plasma is 11% higher than that of whole blood depending on the haematocrit, increasing to 15% at a haematocrit of 0.55 and decreasing to 8% at a haematocrit of 0.30 [39]. Therefore, glucose concentrations in plasma are 11% higher than whole blood if the hematocrit is normal. Glucose concentrations in heparinized plasma are reported to be 5% lower than in serum [40]*.* This may be caused by water shifting from red blood cells to plasma sequel to effect of anticoagulants. In feed (OGTT) state capillary glucose is higher by about [mean of 1.7 mmol/L (30 mg/dL), equivalent to 20–25%*]* than in venous blood*, but*

*Oral Glucose Tolerance Test (OGTT): Undeniably the First Choice Investigation…*

*the* mean difference in fasting samples is only 0.1 mmol/L (2 mg/dL) [41]*.*

**4.4 Fasting plasma glucose (FPG): a tool in screening for dysglycaemia**

there is associated progressively greater risk of developing micro- and

In 2003, the ADA reviewed its diagnostic criteria when it found out that the FPG

stated in the earlier classifications does not give corresponding hyperglycaemic impact compared to the OGTT results. The threshold for IFG was lowered from 6.1 mmol/L to 5.6 mmol/L [44] dependent on ROC curve analysis indicating that a cut-point of 5.4–5.5 mmol/L gives the best combination of sensitivity and specificity for predicting future diabetes, and this consequently increased the overall prevalence of IFG approximately three- to four-fold, though WHO and IDF maintained this as FPG 6.1–6.9 mmol/L. To date the searching to finding the corresponding FPG

Although both IGT and IFG are associated with resistance to insulin and increased insulin secretion, they do not identify identical patient populations and are not equivalent in predicting development of T2DM or cardiovascular events [45]. People with isolated IFG predominantly have hepatic insulin resistance and normal muscle insulin sensitivity, whereas individuals with isolated IGT have

macrovascular complications.

**119**

to what is normal or IGT is still ongoing.

In 1997, ADA Expert Committee on the Diagnosis and Classification of Diabetes Mellitus [42] recommended universal use of FPG for screening and diagnosis of diabetes mellitus because of its ease of administration, convenience, acceptability to patients, and lower cost in comparison to the OGTT and also based on assumption that the measurement reproducibility would be better. Since the goal and premise of diabetes management is the prevention of diabetes-associated complications, and this goal is best achieved when the disease is diagnosed at an early stage, the committee lowered the diagnostic threshold of FPG from 7.8 mmol/L to 7.0 mmol/L and also created a new category, defined as individuals exhibiting FPG levels between 6.1 and 6..9 mmol/L, called impaired fasting glucose (IFG) to describe the zone between the upper limit of normal FPG and the lower limit of the diabetic FPG. The IFG was believed at that time to be analogous to the zone between the upper limit of a normal 2-hr plasma glucose and the lower limit of the diabetic 2-hr plasma glucose described by IGT and was adapted by WHO in 1999 [43]**.** The FPG of 6.1 mmol/L was adopted by both ADA [44] and WHO [43] as the upper limit of "normoglycaemia" because this is the level above which first-phase of insulin secretion is lost in response to intravenous glucose and is also the level at which

On the basis of biological variation, glucose analysis having analytical imprecision 3.3%, bias 2.5%, and total error 7.9%, may produce classification errors, although imprecision is usually low at the diagnostic decision limits. It is also believed generally that glucose assay is highly reproducible across laboratories, however, a recent survey conducted in 6,000 US laboratories clearly documented a significant bias in glucose assessment in as many as 41% of them, yielding a misclassification of glucose tolerance in 12% of subjects [27]**.** The coefficients of variation of A1c, FPG, and 2-h PG were demonstrated to be 3.6%, 5.7%, and 16.6% respectively [28]**,** reflecting both biological and analytical variability.

Preanalytical processing of blood samples can markedly affect the results of plasma glucose readings because ongoing glycolysis by erythrocytes and leukocytes prior to centrifugation lowers its concentration [29, 30]. A study reported 5–7% [0.6 mmol/L (10 mg/dl)] an average rate of glycolysis per hour [31]**.** This varies with the glucose concentration, temperature*,* white blood cell count and other factors [32]*, for example,* it has been estimated that pre-analytical variability of FPG is 5–10% and the within day-day variability is 12–15%. Glycolysis can be attenuated by inhibition of enolase with sodium fluoride (2.5 mg fluoride/ml of blood) or, less commonly, lithium iodoacetate (0.5 mg/ml of blood). A citrate tubes should be use if a delay in centrifugation is expected because citrate more rapidly inhibits glycolysis [30]**.** It should be noted that although fluoride maintains long-term glucose stability, the rates of decline of glucose in the first hour after sample collection in tubes with and without fluoride are virtually identical [31]**.** Currently, both WHO and ADA recommend that for preanalytical processing for plasma glucose measurements involves venous blood collection into sodium fluoride (NaF) tubes with placement in ice-water slurry prior to centrifugation within 30 min of sample collection [33, 34]. The benefit of this policy is demonstrated in the following studies: An observed increase rate of GDM from 11.6% to 20.6% on changing to a protocol of centrifuging blood collected into NaF tubes within 10 min of venipuncture compared to delayed centrifugation was noted [35]**.** A study in Ireland showed a 2.7-fold higher (38.1% compared with 14.2%) when the ADA preanalytic protocol was followed compared with the previous standard practice of collecting blood into NaF tubes, leaving them at room temperature, and centrifuging after collection of all three samples [36]**.** Similarly, the impact of long delays in centrifugation for OGTT samples collected in NaF tubes on GDM diagnosis in Western Australia was estimated to be an under diagnosis rate of 62% [37]. In HAPO, a reference study for GDM, blood samples for all glucose measurements were collected into NaF tubes, placed in ice-water slurry immediately after phlebotomy, and kept that way until they could be centrifuge and separated [38].

*Oral Glucose Tolerance Test (OGTT): Undeniably the First Choice Investigation… DOI: http://dx.doi.org/10.5772/intechopen.96549*

### **4.3 Specimen for glucose estimation**

need to be conversant with causes of intraindividual and interindividual variation of

a. The biological variability is substantially greater than analytical variability

On the basis of biological variation, glucose analysis having analytical impreci-

sion 3.3%, bias 2.5%, and total error 7.9%, may produce classification errors, although imprecision is usually low at the diagnostic decision limits. It is also believed generally that glucose assay is highly reproducible across laboratories, however, a recent survey conducted in 6,000 US laboratories clearly documented a

significant bias in glucose assessment in as many as 41% of them, yielding a misclassification of glucose tolerance in 12% of subjects [27]**.** The coefficients of variation of A1c, FPG, and 2-h PG were demonstrated to be 3.6%, 5.7%, and 16.6%

Preanalytical processing of blood samples can markedly affect the results of plasma glucose readings because ongoing glycolysis by erythrocytes and leukocytes prior to centrifugation lowers its concentration [29, 30]. A study reported 5–7% [0.6 mmol/L (10 mg/dl)] an average rate of glycolysis per hour [31]**.** This varies with the glucose concentration, temperature*,* white blood cell count and other factors [32]*, for example,* it has been estimated that pre-analytical variability of FPG is 5–10% and the within day-day variability is 12–15%. Glycolysis can be attenuated by inhibition of enolase with sodium fluoride (2.5 mg fluoride/ml of blood) or, less commonly, lithium iodoacetate (0.5 mg/ml of blood). A citrate tubes should be use if a delay in centrifugation is expected because citrate more rapidly inhibits glycolysis [30]**.** It should be noted that although fluoride maintains long-term glucose stability, the rates of decline of glucose in the first hour after sample collection in tubes with and without fluoride are virtually identical [31]**.** Currently, both WHO and ADA recommend that for preanalytical processing for plasma glucose measurements involves venous blood collection into sodium fluoride (NaF) tubes with placement in ice-water slurry prior to centrifugation within 30 min of sample collection [33, 34]. The benefit of this policy is demonstrated in the following studies: An observed increase rate of GDM from 11.6% to 20.6% on changing to a protocol of centrifuging blood collected into NaF tubes within 10 min of venipuncture compared to delayed centrifugation was noted [35]**.** A study in Ireland showed a 2.7-fold higher (38.1% compared with 14.2%) when the ADA preanalytic protocol was followed compared with the previous standard practice of collecting blood into NaF tubes, leaving them at room temperature, and centrifuging after collection of all three samples [36]**.** Similarly, the impact of long delays in centrifugation for OGTT samples collected in NaF tubes on GDM diagnosis in Western Australia was estimated to be an under diagnosis rate of 62% [37]. In HAPO, a reference study for GDM, blood samples for all glucose measurements were collected into NaF tubes, placed in ice-water slurry immediately after phlebotomy, and kept that way until

respectively [28]**,** reflecting both biological and analytical variability.

they could be centrifuge and separated [38].

**118**

blood glucose is necessary. Such variability can be grouped as

*Type 2 Diabetes - From Pathophysiology to Cyber Systems*

b. Analytical imprecision <3.3%

c. Bias <2.5%

d. Total error < 7.9%

e. Glucose assay 4%

f. Biological CV 6.9%

Glucose can be measured in whole blood, serum, or plasma, but plasma is recommended for diagnosis. It can also be measured in capillary, venous or arterial blood. It is essential that in a repeat sampling for confirmation of blood glucose result, the same type of sampling used previously must be use. The molality of glucose (i.e., amount of glucose per unit water mass) in whole blood and plasma is identical. Although red blood cells are essentially freely permeable to glucose, the concentration of water (kg/L) in plasma is 11% higher than that of whole blood depending on the haematocrit, increasing to 15% at a haematocrit of 0.55 and decreasing to 8% at a haematocrit of 0.30 [39]. Therefore, glucose concentrations in plasma are 11% higher than whole blood if the hematocrit is normal. Glucose concentrations in heparinized plasma are reported to be 5% lower than in serum [40]*.* This may be caused by water shifting from red blood cells to plasma sequel to effect of anticoagulants. In feed (OGTT) state capillary glucose is higher by about [mean of 1.7 mmol/L (30 mg/dL), equivalent to 20–25%*]* than in venous blood*, but the* mean difference in fasting samples is only 0.1 mmol/L (2 mg/dL) [41]*.*

#### **4.4 Fasting plasma glucose (FPG): a tool in screening for dysglycaemia**

In 1997, ADA Expert Committee on the Diagnosis and Classification of Diabetes Mellitus [42] recommended universal use of FPG for screening and diagnosis of diabetes mellitus because of its ease of administration, convenience, acceptability to patients, and lower cost in comparison to the OGTT and also based on assumption that the measurement reproducibility would be better. Since the goal and premise of diabetes management is the prevention of diabetes-associated complications, and this goal is best achieved when the disease is diagnosed at an early stage, the committee lowered the diagnostic threshold of FPG from 7.8 mmol/L to 7.0 mmol/L and also created a new category, defined as individuals exhibiting FPG levels between 6.1 and 6..9 mmol/L, called impaired fasting glucose (IFG) to describe the zone between the upper limit of normal FPG and the lower limit of the diabetic FPG. The IFG was believed at that time to be analogous to the zone between the upper limit of a normal 2-hr plasma glucose and the lower limit of the diabetic 2-hr plasma glucose described by IGT and was adapted by WHO in 1999 [43]**.** The FPG of 6.1 mmol/L was adopted by both ADA [44] and WHO [43] as the upper limit of "normoglycaemia" because this is the level above which first-phase of insulin secretion is lost in response to intravenous glucose and is also the level at which there is associated progressively greater risk of developing micro- and macrovascular complications.

In 2003, the ADA reviewed its diagnostic criteria when it found out that the FPG stated in the earlier classifications does not give corresponding hyperglycaemic impact compared to the OGTT results. The threshold for IFG was lowered from 6.1 mmol/L to 5.6 mmol/L [44] dependent on ROC curve analysis indicating that a cut-point of 5.4–5.5 mmol/L gives the best combination of sensitivity and specificity for predicting future diabetes, and this consequently increased the overall prevalence of IFG approximately three- to four-fold, though WHO and IDF maintained this as FPG 6.1–6.9 mmol/L. To date the searching to finding the corresponding FPG to what is normal or IGT is still ongoing.

Although both IGT and IFG are associated with resistance to insulin and increased insulin secretion, they do not identify identical patient populations and are not equivalent in predicting development of T2DM or cardiovascular events [45]. People with isolated IFG predominantly have hepatic insulin resistance and normal muscle insulin sensitivity, whereas individuals with isolated IGT have

normal to slightly reduced hepatic insulin sensitivity and moderate to severe muscle insulin resistance [46]. Individuals with isolated IFG have reduction in both firstphase (0–10 min) during IVGT and early phase (first 30 min) during OGTT insulin secretion but maintained the late-phase (60–120 min) response during OGTT, while Isolated IGT apart from having defect in early-phase insulin secretion in response to OGTT also has a severe deficit in late-phase insulin secretion [47].

The change in the diagnostic procedure has brought a complex and variable effect on the prevalence of diabetes and on subjects diagnosed. Many studies have reported that FPG and 2-hr plasma glucose do not identify the same people as having diabetes. The difference between the prevalence of diabetes based on the FPG and 2-hr criteria varied from 4.0% to 13.2% in the 16 European survey in the DECODE study. In that study [56], of the 1517 people with newly diagnosed diabetes, 40% met only the FPG criterion, 31% met only the 2-hr criterion and 29% met both criteria. In the DECODA study [49], of 1215 subjects with diabetes by either criterion, only 449 (37%) met both criteria, of the 995 subjects with 2-hr ≥11.1 mmol/L, 546 (55%) had non-diabetes FPG value, and of the 669 subjects with FPG ≥7.0 mmol/L, 220 (33%) had nondiabetes 2-hr value. In the two studies the concordance rate ranges between 29–37%. In the NHANES study data cited in the 1997 ADA report showed 38% of subjects with newly diagnosed diabetes using only ADA criteria were missed when OGTT was carried out in the same population [42]. An even larger discrepancy was observed for the categories of IFG and IGT. In DECODA study, more than three quarter (≥3/4) of the subjects with IGT would be classified as normal if only the FPG criteria is used. Degree of hyperglycaemia, age, sex, BMI and ethnicity influence the concordance. The severer the hyperglycaemia the better the agreement between the two criteria. It might therefore be appropriate to use the FPG alone in subjects with clinical symptoms of diabetes to confirm. It is inappropriate to use it as the only test in the general population for epidemiological purposes, or in cohort with slightly higher glycaemia but without any symptoms because a large proportion of subjects diagnosed by 2-hr criteria would not be identified by the FPG particularly in Asians. In 1999, WHO recommended retaining the use of OGTT for epidemiological purposes, and this appears to be particularly important for the Asian population. The 2-hr criterion is more sensitive in the elderly and fasting criterion in the mid-aged. Barrett-Conner, et al. [57] reported that 70% of women and 48% of men aged 50–89 years had new diabetes diagnosed solely by elevated 2-hr plasma glucose. Similarly, in the Early Diabetes Intervention Program study [58], 24% and 50% of subjects with OGTTconfirmed diabetes had FPG levels between 5.5 and 6.0 and 6.1–6.9 mmol/L, respectively. Still in a further study, an isolated elevation of 2-hr glucose (2-hr glucose ≥11.1 mmol/L and FPG <7.0 mmol/L) identified as high as 65%(61/94) of those with newly diagnosed diabetes while 76%(644/845) who were normal by fasting blood glucose were identified with IGT and these individuals carry high risk of cardiovascular disease events [59]. A recent report showed that even if the concordance between the WHO and ADA criteria increased with this lower cutoff of IFG, 29% of patients with diabetes revealed by an OGTT and 57% with IGT would still have remained undiagnosed using FPG [59]**.** All individuals with IFG should have an OGTT, as a significant number (approximately 5%, but up to 20%, in some

*Oral Glucose Tolerance Test (OGTT): Undeniably the First Choice Investigation…*

*DOI: http://dx.doi.org/10.5772/intechopen.96549*

populations) will already have diabetes by 2-hr post challenge criteria [60]**,** so why

Impaired glucose tolerance (IGT), not diagnosed with FPG estimation, is associated with risk of cardiovascular events almost as high as in subjects with diabetes which is not similarly observed in people with IFG necessitating ADA to lowered the threshold for IFG from 6.1 mmol/L to 5.6 mmol/L in order to detect more subjects with pre-diabetes [61]. Consequently, with regards to the assessment of the risk of mortality and cardiovascular disease events, these discrepancies are crucially important. Therefore, in screening programs, clinical research, and populationbased epidemiological studies, where participants often lack diabetes symptoms or complications, an OGTT is commonly used to detect diabetes, thus adding to the diabetic "pool" an equal-sized group of subjects with unrecognized diabetes and it is

delaying diagnosis, why not start with OGTT in the first place.

misleading trying to assess glucose homeostasis without information on

post-prandial glucose metabolism.

**121**

The prevalences of IFG and IGT varies widely, varied considerably among different ethnic groups [48]**,** differ significantly in their age and sex distribution; and increase with advancing age. IGT is more frequent in women than in men [49]. A study of 1,245 Italian telephone company employees followed for 11.5 years found that, unlike baseline IGT, baseline IFG did not predict progression to DM, and the categories only overlapped 40% of the time [48]. The natural history of both IFG and IGT is variable, with approx 25% progressing to diabetes, 50% remaining in their abnormal glycaemic state, and 25% reverting to NGT over an observational period of 3-5 years [50, 51].

#### **4.5 Advantages of using FPG in screening for dysglycaemia**

American Diabetes Associated did not recommend OGTT to be used commonly in the diagnosis of type 1 and 2 diabetes because it was thought that if FPG is appropriately use it will identify almost the same number of dysglycaemia in the population as the OGTT, and that OGTT is not practicable in routine practice and in many studies OGTT is found to be poorly reproducible, with an estimated rate of only about 50–66% [52].

#### **4.6 Disadvantages of FPG in screening for dysglycaemia**

The fasting blood glucose testing in nondiabetic persons poorly identify early signs of dysglycaemia because high postprandial glucose marks the journey of first signs of abnormal glucose regulation and this best predict cardiovascular outcome. Fasting is not really the central issue and it seems to be overemphasized in diagnosing dysglycaemia.

One problem well known in the measurement of FPG in population studies is the difficulty in ensuring that all the participants have complied with the instructions about fasting [53]. Consequently, some participants with completely normal glucose homeostasis might have been misclassified into impaired fasting glucose category or, more rarely, even into a diabetes category. More so, FPG represents glucose handling during the moment of fasting period only (particularly so, of that moment of blood sampling), and this is affected easily by short-term lifestyle changes such as over activity, stress and drug ingestions. Therefore under these conditions subjects may be classified wrongly if only FPG is used. Knowledge of intraindividual variability of FPG concentrations is essential for meaningful interpretation of patient values. A study of healthy individuals [mean glucose, 4.9 mmol/L (88 mg/ dL)] exhibited within- and between-subject CVs of 4.8–6.1% and 7.5–7.8%, respectively [34]**.** Recent evidence revealed a diurnal variation in FPG, with mean FPG higher in the morning than in the afternoon, indicating that many cases of undiagnosed diabetes would have been missed in patients seen in the afternoon [54]**.** A study with repeated OGTT in 31 nondiabetic adults at 48-hr intervals, demonstrated FPG varied by 10% in 22 participants (77%) and by 20% in 30 participants (97%) [44]**.** Similarly, in population studies of subjects with newly diagnosed diabetes showed a wide distribution of FPG, ranging in one study from <5.0 mmol/1 to >30.0 mmol/L [55]. As a consequence, the sensitivity of the OGTT is naturally higher, given the current criteria.

*Oral Glucose Tolerance Test (OGTT): Undeniably the First Choice Investigation… DOI: http://dx.doi.org/10.5772/intechopen.96549*

The change in the diagnostic procedure has brought a complex and variable effect on the prevalence of diabetes and on subjects diagnosed. Many studies have reported that FPG and 2-hr plasma glucose do not identify the same people as having diabetes. The difference between the prevalence of diabetes based on the FPG and 2-hr criteria varied from 4.0% to 13.2% in the 16 European survey in the DECODE study. In that study [56], of the 1517 people with newly diagnosed diabetes, 40% met only the FPG criterion, 31% met only the 2-hr criterion and 29% met both criteria. In the DECODA study [49], of 1215 subjects with diabetes by either criterion, only 449 (37%) met both criteria, of the 995 subjects with 2-hr ≥11.1 mmol/L, 546 (55%) had non-diabetes FPG value, and of the 669 subjects with FPG ≥7.0 mmol/L, 220 (33%) had nondiabetes 2-hr value. In the two studies the concordance rate ranges between 29–37%. In the NHANES study data cited in the 1997 ADA report showed 38% of subjects with newly diagnosed diabetes using only ADA criteria were missed when OGTT was carried out in the same population [42]. An even larger discrepancy was observed for the categories of IFG and IGT. In DECODA study, more than three quarter (≥3/4) of the subjects with IGT would be classified as normal if only the FPG criteria is used. Degree of hyperglycaemia, age, sex, BMI and ethnicity influence the concordance. The severer the hyperglycaemia the better the agreement between the two criteria. It might therefore be appropriate to use the FPG alone in subjects with clinical symptoms of diabetes to confirm. It is inappropriate to use it as the only test in the general population for epidemiological purposes, or in cohort with slightly higher glycaemia but without any symptoms because a large proportion of subjects diagnosed by 2-hr criteria would not be identified by the FPG particularly in Asians. In 1999, WHO recommended retaining the use of OGTT for epidemiological purposes, and this appears to be particularly important for the Asian population. The 2-hr criterion is more sensitive in the elderly and fasting criterion in the mid-aged. Barrett-Conner, et al. [57] reported that 70% of women and 48% of men aged 50–89 years had new diabetes diagnosed solely by elevated 2-hr plasma glucose. Similarly, in the Early Diabetes Intervention Program study [58], 24% and 50% of subjects with OGTTconfirmed diabetes had FPG levels between 5.5 and 6.0 and 6.1–6.9 mmol/L, respectively. Still in a further study, an isolated elevation of 2-hr glucose (2-hr glucose ≥11.1 mmol/L and FPG <7.0 mmol/L) identified as high as 65%(61/94) of those with newly diagnosed diabetes while 76%(644/845) who were normal by fasting blood glucose were identified with IGT and these individuals carry high risk of cardiovascular disease events [59]. A recent report showed that even if the concordance between the WHO and ADA criteria increased with this lower cutoff of IFG, 29% of patients with diabetes revealed by an OGTT and 57% with IGT would still have remained undiagnosed using FPG [59]**.** All individuals with IFG should have an OGTT, as a significant number (approximately 5%, but up to 20%, in some populations) will already have diabetes by 2-hr post challenge criteria [60]**,** so why delaying diagnosis, why not start with OGTT in the first place.

Impaired glucose tolerance (IGT), not diagnosed with FPG estimation, is associated with risk of cardiovascular events almost as high as in subjects with diabetes which is not similarly observed in people with IFG necessitating ADA to lowered the threshold for IFG from 6.1 mmol/L to 5.6 mmol/L in order to detect more subjects with pre-diabetes [61]. Consequently, with regards to the assessment of the risk of mortality and cardiovascular disease events, these discrepancies are crucially important. Therefore, in screening programs, clinical research, and populationbased epidemiological studies, where participants often lack diabetes symptoms or complications, an OGTT is commonly used to detect diabetes, thus adding to the diabetic "pool" an equal-sized group of subjects with unrecognized diabetes and it is misleading trying to assess glucose homeostasis without information on post-prandial glucose metabolism.

normal to slightly reduced hepatic insulin sensitivity and moderate to severe muscle insulin resistance [46]. Individuals with isolated IFG have reduction in both firstphase (0–10 min) during IVGT and early phase (first 30 min) during OGTT insulin secretion but maintained the late-phase (60–120 min) response during OGTT, while Isolated IGT apart from having defect in early-phase insulin secretion in response to OGTT also has a severe deficit in late-phase insulin secretion [47]. The prevalences of IFG and IGT varies widely, varied considerably among different ethnic groups [48]**,** differ significantly in their age and sex distribution; and increase with advancing age. IGT is more frequent in women than in men [49]. A study of 1,245 Italian telephone company employees followed for 11.5 years found that, unlike baseline IGT, baseline IFG did not predict progression to DM, and the categories only overlapped 40% of the time [48]. The natural history of both IFG and IGT is variable, with approx 25% progressing to diabetes, 50% remaining in their abnormal glycaemic state, and 25% reverting to NGT over an observational

American Diabetes Associated did not recommend OGTT to be used commonly

The fasting blood glucose testing in nondiabetic persons poorly identify early signs of dysglycaemia because high postprandial glucose marks the journey of first signs of abnormal glucose regulation and this best predict cardiovascular outcome. Fasting is not really the central issue and it seems to be overemphasized in diagnos-

One problem well known in the measurement of FPG in population studies is the difficulty in ensuring that all the participants have complied with the instructions about fasting [53]. Consequently, some participants with completely normal glucose homeostasis might have been misclassified into impaired fasting glucose category or, more rarely, even into a diabetes category. More so, FPG represents glucose handling during the moment of fasting period only (particularly so, of that moment of blood sampling), and this is affected easily by short-term lifestyle changes such as over activity, stress and drug ingestions. Therefore under these conditions subjects may be classified wrongly if only FPG is used. Knowledge of intraindividual variability of FPG concentrations is essential for meaningful interpretation of patient values. A study of healthy individuals [mean glucose, 4.9 mmol/L (88 mg/ dL)] exhibited within- and between-subject CVs of 4.8–6.1% and 7.5–7.8%, respectively [34]**.** Recent evidence revealed a diurnal variation in FPG, with mean FPG higher in the morning than in the afternoon, indicating that many cases of undiagnosed diabetes would have been missed in patients seen in the afternoon [54]**.** A study with repeated OGTT in 31 nondiabetic adults at 48-hr intervals, demonstrated FPG varied by 10% in 22 participants (77%) and by 20% in 30 participants (97%) [44]**.** Similarly, in population studies of subjects with newly diagnosed diabetes showed a wide distribution of FPG, ranging in one study from <5.0 mmol/1 to >30.0 mmol/L [55]. As a consequence, the sensitivity of the OGTT

in the diagnosis of type 1 and 2 diabetes because it was thought that if FPG is appropriately use it will identify almost the same number of dysglycaemia in the population as the OGTT, and that OGTT is not practicable in routine practice and in many studies OGTT is found to be poorly reproducible, with an estimated rate of

period of 3-5 years [50, 51].

only about 50–66% [52].

ing dysglycaemia.

**120**

**4.5 Advantages of using FPG in screening for dysglycaemia**

*Type 2 Diabetes - From Pathophysiology to Cyber Systems*

**4.6 Disadvantages of FPG in screening for dysglycaemia**

is naturally higher, given the current criteria.

In conclusion, although in clinical practice the OGTT is often regarded as a cumbersome, time-consuming, and patient-unfriendly procedure, for a more detailed and sensitive assessment of the glucose dysmetabolism, the oral glucose tolerance test (OGTT) is the best.

reproducibility of the test (CV = 50%) for 2 h blood glucose. Some of these cause of variations can be minimized with adequate attention to physical activities, dietary preparation and taking care of sample collection at the 2-hr sample (sampling must be done within 5 minutes of 120 minute [66]. The WHO (1999) placed emphasis on the OGTT as the "gold standard", with both fasting and 120-min values being taken into consideration [67]**.** This is by no means a mistake. Only when an OGTT cannot be performed should the diagnosis rely on fasting levels. Other hormones and metabolites can be measured during OGTT, not just glucose and insulin, eg., the

OGTT is the only means of identifying people with IGT, and IGT is an essential diagnostic step, especially when FPG is within the normal range, as these subjects are at high risk not only for type 2 diabetes, but in particular for cardiovascular disease. The main clinical significance of IGT are [68]: (1) It is a risk factor for type

10 years; (2) It predisposes individual to cardiovascular disease (CVD); and (3) It is a component of the metabolic syndrome and its consequences. IGT when identified and subsequently managed will prevent or delayed progression to type 2 diabetes mellitus. It has been indicated by recent studies [69–71] that persons classified with IGT using WHO criteria have increased risk of cardiovascular disease, however many of these subjects do not have impaired fasting glucose (IFG) by the new ADA criteria. Furthermore, the OGTT by WHO criteria identifies diabetes in 2% more individuals than does FPG using ADA criteria [70], although diabetic individuals who are identified by both abnormal FPG and 2-h OGTT have a higher risk of premature death than those with only an increased FPG concentration [71]. More so, fasting plasma glucose alone fails to diagnose in about 30% of cases of diabetes diagnosed by OGTT. OGTT establishes whether an IFG subjects has normal 2hPG and only the simultaneous information obtained from 2hPG (OGTT) allows the screening to become effective. An important matter here is that people with IGT who cannot be identified by either FPG or A1c have ≈40% increased mortality compared with normoglycaemic subjects and lifestyle intervention in these individuals can prevents progression to type 2 diabetes and may reduce their mortality risk to the level observed among normoglycaemic population. These prevention benefits do not exist for A1c or FPG, and this evidences should not be forgotten when deciding the approaches to identify intermediate dysglycaemia. We should therefore make OGTT a priority in an attempt to diagnose hyperglycaemia as early

Thus, using solely FPG, would deceitfully reassure a large proportion of individuals as having NGT, without warning them on the benefits of preventive treatment. Epidemiological studies showed that A1c and plasma glucose (FPG and/or 2-hr OGTT) identify partially different groups of diabetic subjects. While A1c ≥6.5% identifies only ≈30–40% newly diagnosed patients with diabetes [72], a larger percentage was detected by FPG (≈50%), and more so by 2-hr PG(≈90%). These findings are based on several recent studies, including the 2003–2006 NHANES study demonstrating only 30% of diabetic individuals were detected by A1c ≥6.5%, 46% by PFG ≥126 mg/dl, and the IRAS demonstrated 32%, 45%, and 87%, respectively) [73] indicating OGTT is superior. However, the pivotal issue on OGTT is its low reproducibility which is significantly represented by physiologic contexts of the test. The plasma glucose during OGTT are influenced by both insulin sensitivity and secretion, however, impact of other factors particularly incretins, neural responses to nutrient ingestion, gastrointestinal motility and gastric emptying are also important. These factors differ significantly between individuals and are part of non-modifiable factors that govern post-load glucose metabolism and plasma glucose concentration, and are difficult to measure in every

OGTT is the primary test used for the diagnosis of GH hypersecretion.

*Oral Glucose Tolerance Test (OGTT): Undeniably the First Choice Investigation…*

*DOI: http://dx.doi.org/10.5772/intechopen.96549*

2 diabetes, about 20–50% of subjects with IGT develop type 2 diabetes over

as possible.

**123**


**1. Introduction**

Diabetes mellitus (DM), a very complex and heterogeneous chronic disease, is associated with chronic complications generated by alteration of the endothelium at all arterial vascular territory levels. The micro-and macrovascular complications affect the entire body; their pathogenic mechanisms are intricate and involve multiple pathways and risk factors. The main risk factors are insulin resistance/hyperinsulinemia, hyperglycemia, dyslipidemia, hypercholesterolemia, hypertension, smoking, obesity/overweight, all of which cause endothelial dysfunction. Consequently, they appear vasoconstriction, oxidative stress, subclinical inflammation, vascular calcification and thrombosis, essential pathogenic elements in the process of atherogenesis/macroangiopathy and microangiopathy [1].

Cardiovascular disease is considered a major cause of morbidity and mortality among people with diabetes, with a significantly increased prevalence compare with people without diabetes. The risk increases with the level of glycaemia, the duration of diabetes and the number of risk factors. People with T2DM have much earlier and more extensive process of accelerated atherosclerosis, more vulnerable and larger volume atherosclerotic plaques and coronary artery lumen with a smaller diameter, compared to people without DM. The pathogenic complex is influenced by genetic factors, age, personal history and a pro-risk lifestyle (unhealthy eating, sedentary lifestyle, smoking, sleep disorders, psychosocial stress and depression) [1].

The macrovascular complications mainly refer to the atherosclerotic cardiovascular disease, represented by coronary artery disease (acute and chronic coronary syndrome) (CAD), chronic peripheral artery disease (PAD) and cerebrovascular disease (CBV). A particular complication is heart failure (HF). The pathogenic mechanisms of micro-and macro-angiopathy are extremely complex, with multiple interactions at the molecular-cellular and vascular-organic level.

Although all complications declined in the last decades, the most significant decreases in diabetes-related complications occurred for heart attack and stroke, especially for people aged 75 years and older. The CVD risk and mortality rate has declined in both the general population [2] and the people with diabetes [3]. However, diabetes, mainly T2DM, continues to be an important generator of cardiovascular disease. As the number of patients with diabetes is predicted to increase, reaching 700 million in 2045 [4], it is expected that the number of people with CVD will also increase. Thus, these major diabetes complications continue to place a heavy burden on health care systems.


*3.4. Immunosuppressive Activity*

Immunosuppressants are drugs that prohibit body immunity and are principally utilized in organ transplantation to overcome rejection and in auto-immune illnesses [57]. Currently, many immunosuppressive agents act by prohibiting T-cell proliferation; however, there is no new, safe, and efficient immune-suppressive agent that prohibits B-cell proliferation [58].

Dai et al. separated eighteen bergamotane sesquiterpenoids from the EtOAc extract of *Craterellus ordoratus*: craterodoratins A–R (**7**–**11**, **29**–**33**, **53**, **55**, **56**, **63**–**65**, and **71**) and a new victoxinine derivative, craterodoratin S (**42**), along with the previously isolated **5**, **61**, **77**, and **88** by SiO2/RP-18/Sephadex LH-20/preparative HPLC (Figure 6) [30].

**Figure 6.** Structures of tricyclic bergamotane sesquiterpenoids (**56**–**63**).

Their structures with absolute configurations were established by spectral, X-ray diffraction, and ECD analyses and NMR calculations. Compounds **29** and **71** possess a rare skeleton, where the C-14methyl in **71** showed a further 1,2-migration. On the other hand, compounds **7**–**11**, **53**, **55**, **56,** and **63**–**65** belong to β-pinene derivatives that produced **30**–**33** through an alkyl migration (Figure 7). Compounds **7**–**10**, **30**, **42**, **55**, **61**, and **88** demonstrated potent inhibitory potential versus LPS-caused B lymphocyte cell proliferation (IC50s ranged from 0.67 to 22.68 μM) in BALB/c mice compared with cyclosporin A (IC50 of 0.47 μM), where compound **61** (IC50 0.67 μM) had the most potent effectiveness. Moreover, compounds **11** and **61** possessed inhibition (IC50s of 31.50 and 0.98 μM, respectively) on T lymphocyte cells proliferation induced by ConA (concanavalin A) compared with cyclosporin A (IC50 0.04 μM). Structurally, it was noted that the *α*,*β*-unsaturated-carboxylic acid unit could be the key functional group for the immunosuppressive potential of these metabolites. Furthermore, compounds **61** and **7**–**10** with a *β*-pinene main core had a wider range of bioactivities [30].

#### *3.5. Antimicrobial Activity*

From *Podospora decipiens*, two new tetracyclic sesquiterpenoids, decipienolides A (**74**) and B (**75**), were separated from the EtOAc extract by SiO2 CC and HPLC analyses. They were obtained as a mixture of inseparable epimers, having a 3-hydroxy-2,2-dimethylbutyric acid sidechain as elucidated by an NMR analysis (Figure 8). The **74**/**75** mixture had an antibacterial influence versus *B. subtilis* (inhibition zone diameter of 9–10 mm, concentration of 200 μg/disk). Neither of them demonstrated capacity versus *Ascobolus furfuraceus* NRRL6460, *Sordaria fimicola* NRRL6459, and *C. albicans* ATCC90029 [24]. Donacinolides A (**82**) and B (**76**) (concentration of 50 μg/mL) revealed weak inhibition versus *Salmonella enterica* subsp. *enterica* (inhibition rates of 24.3, 23.9, and 26.2%) in the microdilution assay [32]. Furthermore, there were no observed antibacterial activity for purpurolides B (**83**) and C (**84**) (concentration of 50 μM) versus *E. coli* ATCC25922, *M. smegmatis* mc2155 ATCC70084, *S. aureus* ATCC25923, and *S. epidermidis* ATCC12228 [47].

**Figure 7.** Structures of tricyclic bergamotane sesquiterpenoids (**64**–**71**)**.**

**Figure 8.** Structures of tetracyclic bergamotane sesquiterpenoids (**72**–**79**).


**8. Lipid composition of sperm plasma membrane**

The lipid compositions of the plasma membrane of the mammalian spermatozoa are markedly different from those of somatic cells. In general, the sperm plasma membrane contains approximately 70% phospholipids, 25% neutral lipids, and 5 % glycolipids (Flesch and Gadella, 2000). All lipid components located in the sperm membranes responsible for the fluidity of membrane lipid bilayers, regulation of sperm maturation, spermatogenesis, capacitation, acrosome reaction and membrane fusion (Parks and Hammerstedt, 1985; Martinez and Morros, 1996; Sanocka and Kurpisz, 2004).

Sperm plasma membrane are made up of a phospholipids bilayer, with the major phospholipids were choline phosphoglycerides (CP), ethanolamine phosphoglycerides (EP) and sphingomyelin which their proportions differed between species. These phospholipids contain a high proportion of long chain, polyunsaturated docosapentanoyl (22:5) and

from inner to outer leaflet of cell plasma membrane which is the hallmark of apoptosis during the degradation phase. Following manufacturer instructions, sperm cells are washed twice with PBS (pH 7.4) by centrifugation at 400 g for 5 min. Sperm pellet are resuspended with HEPES buffer (10mM HEPES/NaOH, pH7.4, 150mM NaCl, 5mM KCl, 1mM MgCl2, 1.8mM CaCl2, 2x106 sperm/ml). One hundred l of sperm suspension are mixed well with 5 l annexinV-FITC conjugate and 3 l of Propidium iodide (PI;20g/ml) and incubated for 15 min at room temperature in the dark. Two hundred spermatozoa are assessed under fluorescent microscope at 400x magnification. The apoptotic sperm cells will fluorescence green while necrotic sperm cells fluorescence red. Alternatively, flow cytometry analysis can

Fig. 5. FCS/SCC two-dimensional histogram, flow cytometry analysis of frozen-thawed boar spermatozoa (supplemented with L-cysteine) stained with Annexin-V/PI: Q3 represent

The lipid compositions of the plasma membrane of the mammalian spermatozoa are markedly different from those of somatic cells. In general, the sperm plasma membrane contains approximately 70% phospholipids, 25% neutral lipids, and 5 % glycolipids (Flesch and Gadella, 2000). All lipid components located in the sperm membranes responsible for the fluidity of membrane lipid bilayers, regulation of sperm maturation, spermatogenesis, capacitation, acrosome reaction and membrane fusion (Parks and Hammerstedt, 1985;

Sperm plasma membrane are made up of a phospholipids bilayer, with the major phospholipids were choline phosphoglycerides (CP), ethanolamine phosphoglycerides (EP) and sphingomyelin which their proportions differed between species. These phospholipids contain a high proportion of long chain, polyunsaturated docosapentanoyl (22:5) and

the viable spermatozoa with intact plasma membrane, while Q2 represent dead

also be used instead of fluorescent microscope (Fig. 5).

spermatozoa with non-intact plasma membrane

**8. Lipid composition of sperm plasma membrane**

Martinez and Morros, 1996; Sanocka and Kurpisz, 2004).

docosahexanoyl (22:6) groups which both lipids represent approximately 50 to 60 % of total phospholipids in boar and bull spermatozoa (Pursel and Graham, 1967; Johnson et al., 1969; Parks and Lynch, 1992). Cholesterol was the major sterol in sperm lipids of all species. Cholesterol to phospholipid molar ratios were 0.26, 0.30, 0.36, and 0.45 for sperm plasma membrane of the boar, rooster, stallion, and bull, respectively (Parks and Lynch, 1992).Glycolipids represented less than 10% of total polar lipids for all species.

The susceptibility of spermatozoa to cold shock differ among species because of the differences of lipid composition of the sperm plasma membrane among species (Flesch and Gadella, 2000).The resistance of the mammalian spermatozoa to cold shock was high in species in which the cholesterol to phospholipids molar ratio and the phospholipids saturation is high (Darin-Bennett and White, 1977). The avian spermatozoa have a high level of cold shock resistant and have a higher level of saturated phospholipids compared to mammalian sperm (Parks and Lynch, 1992). The plasma membrane of the boar spermatozoa is characterized by a high protein, low cholesterol and high proportion of EP compared to other species (Parks and Lynch, 1992; Nikolopoulou et al., 1985). In contrast, the protein content and EP proportion of rooster sperm plasma membrane is low while the cholesterol content is intermediate (Parks and Lynch, 1992).

As mentioned above the sperm plasma membrane has a very high amounts of polyunsaturated fatty acids (PUFAs) especially docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) (Johnson et al., 1969; Parks and Lynch, 1992). It has been suggested that the proportion of unsaturated fatty acid influence the properties of sperm plasma membrane (Miller et al., 2005). High levels of long chain PUFAs, DPA and DHA, are associated with an increased membrane fluidity (Quinn, 1985). During cryopreservation, the fluidity of the plasma membrane from boar spermatozoa is significantly decreased when compared to fresh spermatozoa which tend to restrict the post-thawed sperm quality (Buhr et al., 1994). In human, sperm with a high level of membrane fluidity had a higher postthawed motility compared to sperm with a low level of membrane fluidity after cryopreservation (Giraud et al., 2000).


2.2.3. Calibration of DEM Parameters of Peat

Based on the significant parameters selected by the Plackett–Burman test, the steepest climbing test was designed to further narrow the range of significant parameters. In the simulation test, the non-significant parameter was set to the middle value of the range, and the significant parameter was gradually increased, according to the designed step

length. The relative error between the simulation and the physical measured value of the stacking angle was taken as the evaluation index. Based on the results of the steepest climbing test, the Box–Behnken test was designed by the response surface methodology (RSM). The significant parameters were set with high, medium, and low levels. The set of non-significant parameters was the same as the steepest climbing test.


*3.2. Isotherms Study*

The most important step in the adsorption study is the fitting of adsorption isotherm models to adsorption data in order to describe how interaction occurs between adsorbent and dye. A number of adsorption isotherms are available and have been successfully applied by the earlier researcher to analyze the adsorption data [71]. In this study, four adsorption isotherms models, namely Freundlich, Tempkin, Langmuir and Dubinin–Radushkevich (D–R) were tested. Adsorption parameters so calculated have been summarized in Table 2. The correlation factor *R*2, indicates that Freundlich adsorption isotherm equation fit more closely to the adsorption data. The linearized form of Freundlich adsorption equation is expressed in Equation (2);

$$\text{llnq}\_{\text{e}} = \text{lnk}\_{\text{f}} + \frac{1}{\text{n}} \text{lnc}\_{\text{e}} \tag{2}$$

where qe (mg g−1) and Ce (mg L−1) are the solid and liquid phase equilibrium concentration of dye. Kf is constant, and is known as the Freundlich constant and 1/*n* is the slope obtained by plotting lnqe vs. Ce shown in Figure 6A. The values of 1/*n* vary due to heterogeneity of the adsorbing materials. The values of 1/*n* shows favorable (0 < 1/*n* < 1), unfavorable (1/*n* > 1) or irreversible (1/*n* = 0) adsorption. However, if its value is unity, the system is at equilibrium and will show heterogeneity [72]. In the present work, the values of 1/*n* calculated from Freundlich for Fe3O4, PANI and PANI/Fe3O4 composites are 0.126, 0.504 and 0.723 respectively showing favorable physical adsorption [73].

**Table 2.** Summary of parameters calculated from adsorption isotherms models.

**Figure 6.** The Isotherm plots (**a**) Freundlich, (**b**) Langmuir, (**c**) Separation factor, (**d**) Tempkin and (**e**) D–R of adsorption of AB40 on Fe3O4, PANI and PANI/Fe3O4 composite.

The data were also fitted in the Langmuir adsorption isotherm equation (Equation (3)) as shown below;

$$\frac{\mathbf{c\_e}}{\mathbf{q\_e}} = \frac{1}{\mathbf{q\_{max}}\mathbf{k\_L}} + \frac{1}{\mathbf{q\_{max}}}\mathbf{c\_e} \tag{3}$$

where Ce (mg L −1) and qe (mg g−1) indicates the concentration of dye and amount of dye adsorbed per gram of adsorbent at equilibrium, respectively. Similarly, KL (mg L−1) represent the Langmuir constant related to adsorption energy and qmax (mg g−1) is the maximum adsorption capacity of adsorbing materials which can be calculated from the slope. The maximum adsorption capacity of AB40 onto Fe3O4, PANI and PANI/Fe3O4 composites are 130.5, 264.9 and 216.9 mg g−1, respectively, as compared in Table 3A. The dimensionless constant (RL) also called separation factor, expresses essential features of the Langmuir isotherm and is represented by Equation (3a).

$$\mathbf{R\_L} = \frac{1}{(1 + \mathbf{K\_L C\_l})} \tag{3a}$$

where Ci (mg L−1) is the initial concentration of AB40. Values of RL indicate that isotherm is either favorable (1 > RL > 0), linear (RL = 1), irreversible (RL = 0) or unfavorable (1 < RL) [74]. In the present study, the values of RL range from 0.00525 to 0.34988 as depicted in Figure 6c, which shows that adsorption of AB40 onto Fe3O4, PANI and PANI/Fe3O4 composites is favorable at low concentration [75].

**Table 3.** Kinetics parameters for adsorption of AB40 on Fe3O4, PANI and PANI/Fe3O4 composite based on pseudo-first-order and pseudo-second-order equations.

The Tempkin isotherm is also an important isotherm model and has been used by researchers to analyze their adsorption data [76,77]. The Tempkin isotherm assumes that due to interactions of the dye with the adsorbent, the adsorption decreases linearly and is characterized by binding energies. It is represented by the following equation (Equation (4));

$$\mathbf{q}\_{\mathbf{e}} = \beta \text{ln}\mathbf{k}\_{\mathbf{T}} + \beta \text{lnc}\_{\mathbf{e}} \tag{4}$$

where Ce (mg L−1), qe (mg g−1) and KT (L g−1) are equilibrium concentration, equilibrium adsorption and binding constant at equilibrium. It is obtained by plotting qe vs. lnCe (Figure 6d). The constant β, considers the interaction between adsorbent and dye (Equation (4a)).

$$
\beta\_- = \frac{\text{RT}}{\text{b}} \tag{4a}
$$

where b is the Tempkin isotherm constant of binding energy (J mol−1K−1). The correlation factors (*R*2) given in Table 2 show that the Tempkin isotherm also fit the adsorption data. The values of KT show that there is strong interaction between AB40 and PANI as compared to Fe3O4 and PANI/Fe3O4 composites (Table 2).

Dubinin–Radushkevich (D–R) as expressed in Equation (5) was also fitted to the adsorption data.

$$\text{Inq}\_{\text{c}} = \text{Inq}\_{\text{s}} - \beta \,\varepsilon^2 \tag{5}$$

where qe is the amount of dye in mg adsorbed per gram of adsorbent (mg g−1), β (mol2 K−1J−2) is the activity coefficient useful in obtaining the mean adsorption energy Ead (kJ mol−1), qs is the adsorption maximum, and ε is Polanyi potential. ε and Ead are expressed by Equations (5a) and (5b) respectively.

$$
\varepsilon = \text{RTln}(1 + \frac{1}{\mathbf{c}\_{\mathbf{e}}}) \tag{5a}
$$

$$E\_{\rm ad} = \frac{1}{\sqrt{1 - 2\beta}}\tag{5b}$$

where R is the gas constant which has a value of 8.314 (J mol−1 K−1) and T is the kelvin temperature.

D–R adsorption model is a unique model used to di fferentiate between the chemical and physical adsorption on the basis of adsorption energy. In early research, it has been demonstrated that if the value of adsorption energy is less than 40 kJ mol−1, the adsorption is physical [78]. In the present work, the values of Ead, calculated by the Equation (5b) are less than 40 kJ mol−1 for adsorption of AB40 and PANI as compared to Fe3O4 and PANI/Fe3O4 composites showing physical adsorption as shown in Table 2.

### *3.3. E*ff*ect of Contact Time and Temperature on Adsorption*

The contact time between adsorbent and dye is of great interest in the adsorption process. The optimum time of equilibrium was determined by adding 0.0340 ± 0.0001 g of each Fe3O4, PANI and PANI/Fe3O4 composite to 20 mL of AB40 (50 mg L−1) in a series of experiments and was shacked at 150 rpm at 30 ◦C. The adsorption data so obtained was plotted as a function of time (Figure 7a). The graph shows that adsorption is very fast in the initial 10–15 min. The initial fast adsorption is due to a strong interaction between active sites of adsorbents and dye molecules. After 40–50 min, adsorption rate of dye become constant due to filling of active sites on the surface of adsorbents. This time period is defined as the dynamic equilibrium time. At the equilibrium time, rate of adsorption and desorption occurs simultaneously with the same speed [79]. Maximum adsorption of AB40 on Fe3O4, PANI and PANI/Fe3O4 composite is observed at 30 ◦C indicating exothermic nature (Figure 7b).

**Figure 7.** Effect of (**a**) time and (**b**) temperature on adsorption of AB40 onto Fe3O4, PANI and PANI/Fe3O4 composite.

### *3.4. E*ff*ect of pH on Adsorption*

The pH of the dye solution plays a unique role in adsorption process. In the present work, the e ffect of pH on adsorption was investigated between 2–12. Results so obtained are plotted as adsorption versus pH (Figure 8). The plot indicates that adsorption of AB40 is high in acidic medium on all three adsorbents. When at a low pH, the backbone of adsorbents is positively charged and the active sites like Fe–O and –C=N are protonated. These positively charged sites have a strong interaction with the negatively charged sites of AB40 dye and hence enhance the adsorption. On the other hand, in a basic medium, the deprotonation of Fe–O–H and –C–N–H will create a negative charge in these groups which will repel the negatively charged sites of dye electrostatically, thus adsorption reduces [80].

**Figure 8.** The effect of solution pH on adsorption of AB40 on PANI, Fe3O4 and PANI/Fe3O4 composite.

### *3.5. E*ff*ect of Ionic Strength on Adsorption*

The effluent of industrial water also contains several ions. Therefore, the presence of these ions will also affect the adsorption process. In the present study, ionic strength effect of sodium sulfate and calcium chloride on adsorption has been studied in the pH between 5–6. The adsorption data so obtained are plotted against ionic strength (Figure 9). The plots (Figure 9a,b) show that adsorption of AB40 on PANI, Fe3O4 and PANI/Fe3O4 composite increases with an increase in ionic strength. This can be attributed to the fact that when both dye and adsorbent have similar charges, an increase in ionic strength will increase adsorption. This effect is more prominent in the adsorption of AB40 on PANI/Fe3O4 composite as compared to pristine PANI, because PANI/Fe3O4 composite contains a greater number of sites with a lone pair of electrons which behave as negatively charged groups [81]. Moreover, the significant increase in the adsorption of AB40 by increasing the ionic strength can be attributed to the dimerization of dye. A number of intermolecular forces like dipole-dipole, ion-dipole and Van der Waals forces have been suggested as the cause of the dimerization. Alberghina and co-workers have observed such type of dimerization while studying salts and temperature effect on adsorption of reactive dyes onto activated carbon [51].

**Figure 9.** The effect of ionic strength of (**a**) Na2SO4.7H2O and (**b**) CaCl2.2H2O on adsorption of AB40 onto Fe3O4, PANI and PANI/Fe3O4 composite.

### *3.6. E*ff*ect of Adsorbent Dosage on Adsorption*

To investigate the effect of adsorbent dosage on adsorption, 0.034, 0.045, 0.075 and 0.1 g of each Fe3O4, PANI and PANI/Fe3O4 composite were added to 100 mg L−1 of AB40 separately and shook at 150 rpm at 30 ◦C and the amount adsorbed was noted (Figure 10). An increase in the adsorption of dye was observed by increasing the adsorbent dose. Initially the rate of adsorption is fast due to greater number of active site and splitting effect of the flux between adsorbents and dye [82].

**Figure 10.** Effect of adsorbent dosage on adsorption of AB40 onto Fe3O4, PANI and PANI/Fe3O4 composite.


**7. Other factors affecting NMDA receptor function**

**5. NMDA receptor dysregulation and hypofunction in schizophrenia**

phenotypes of the disorder.

6 Schizophrenia Treatment - The New Facets

locomotor activity [27].

disorder [31, 32].

**6. High‐risk genes implicated in schizophrenia**

A major finding discovered by functional imaging studies was reduced activity in the dorsolateral prefrontal cortex (dlPFC) in patients with schizophrenia. The overall reduc‐ tion in neuronal activity in the dlPFC could explain the cognitive deficits and negative symptoms. There is consensus that NMDA receptor hypofunction is strongly associated with the pathophysiology of schizophrenia. In human studies, single‐photon emission computed tomography (SPECT) shows "hypofrontality" patients suffering from schizo‐ phrenia [22]. Furthermore, there are genetic implications that show single‐nucleotide polymorphisms (SNPs) and a reduction in NR1 protein and mRNA in the dorsolateral prefrontal cortex in postmortem subjects of schizophrenia [9, 23]. Additionally, exome sequencing of patients with schizophrenia also displays disruptive mutations in genes that encode NMDAR subunits and NMDA receptor‐associate scaffolding proteins, such as PSD‐95 and SAP102 [24, 25]. These findings would suggest a lack of and/or function at the postsynaptic membrane of excitatory synapses that could be responsible for the cellular

Noncompetitive NMDA receptor antagonists such as PCP, MK‐801, and ketamine have been extensively used to study the symptoms associated with schizophrenia in both human sub‐ jects and animal models [26]. Indeed, these studies have shown to mimic the effects of schizo‐ phrenia, corroborating the glutamatergic hypofunction hypothesis. Individually, PCP induces psychotic symptoms in healthy humans that resemble schizophrenic‐like behavior; MK‐801 elicits positive and negative symptoms; and lastly ketamine administration was shown to imitate the positive, negative, and cognitive deficits seen in schizophrenia [11]. In rats, NMDA receptor antagonists cause deficits in working memory, executive functions, and enhanced

High‐risk genes associated with schizophrenia such as DISC1, dysbindin, neuregulin, COMT, and G72/G30 genes, responsible for neurodevelopment, neuronal growth, and migration, have all shown to be involved in NMDA dysfunction leading to schizophre‐ nia [15]. The most prominent of the genes is *D*isrupted in *schizophrenia* 1 (DISC1), which acts as a scaffolding protein involved in the formation of protein complexes important in neurodevelopment, microtubule network dynamics and axonal elongation [28, 29]. Despite the controversy and debate [16, 30], evidence shows that schizophrenic patients contain DISC1‐SNPs that cause a decrease in DISC1‐interacting protein expression levels, such as NMDA receptors. In DISC1 animal models, mice with point mutations in the gene or truncated forms of DISC1 display molecular, cellular, and behavioral phenotypes that are analogous to schizophrenia. DISC1 is especially susceptible to mutations due to envi‐ ronmental stressors during neurodevelopment that may lead to the pathogenesis of the Environmental factors during development, such as infection, drug use, parental age, prena‐ tal and early postnatal or childhood stress, have all been linked to the emergence of schizo‐ phrenia [33]. In addition, NMDA receptor function is susceptible to the latter environmental risk factors during adolescence, potentially contributing to the onset of the disorder [6, 33, 34]. This could be due to an alteration in NMDA receptor gene expression, as major transcrip‐ tional factors such as the cAMP response element binding protein (CREB) are extremely sen‐ sitive to environmental stimuli [35]. Previous studies describe that neurodevelopment in the prefrontal cortex is altered in patients with schizophrenia due to a substantial increase in synaptic elimination of glutamatergic excitatory synapses [36].

NMDA receptors are also influenced by posttranslational modifications such as ubiquitina‐ tion, palmitoylation, and phosphorylation [34]. NMDA receptor phosphorylation is respon‐ sible for regulating receptor trafficking, stabilization, kinetics of the channel, and kinase activation. These processes are important for synaptic plasticity during neurodevelopment and if dysregulated could be highly responsible for the pathologies of schizophrenia [7]. NMDA receptor subunits are phosphorylated at serine/threonine and tyrosine residues, providing substrate sites for kinases such as Src family of kinases (SFK), casein kinase 2 (CK2), cAMP‐dependent protein kinase A (PKA), cyclin‐dependent kinase 5 (Cdk5), pro‐ tein kinase C (PKC), and Ca2+/calmodulin‐dependent protein kinase II (CaMKII) [37–40].

Other modification processes such as palmitoylation and ubiquitination have also been directly linked to schizophrenia [41]. There is evidence of NMDA receptor dysregulation due to anomalous modifications that could potentially lead to neuropsychiatric disorders. Palmitoylation is a process that allows the covalent attachment of palmitate group to the cys‐ teine residues of proteins that are facilitated via thioester bonds. Recently, it has shown to be involved in regulating NR2 subunit trafficking during neurodevelopment and synaptic plasticity [42] and is altered in a mouse model of 22q11.2 deletion syndrome. Ubiquitination is a process involved in the targeting and removal of proteins and is responsible for regulating NMDA receptors degradation during development. Specifically, subunits such as NR1 and NR2B undergo polyubiquitination at the synapse [41]. Nonetheless, palmitoylation and ubiq‐ uitination require further investigation in its role in NMDA receptor regulation and potential implication in schizophrenia.