1. Introduction
Hyperglycemia that leads to T2D appears to represent a persistent set of life-sustaining chemical conditions which is described by elevated blood sugar which manifests well as the inadequate and ineffective release of pancreatic hormone and affects a set of life-sustaining chemicals, such as glucose amino acids and fatty acids [1]. Data show that in 2015 more than 400 million adults globally were affected by this condition. These people were predominantly among the economically disadvantaged population, and T2D is projected to be the seventh leading cause of death by 2030 [1]. T2D in contrast to type 1 diabetes (T1D) does not completely rely on insulin. T2D is a metabolic condition largely described for its role in licking the cell membrane, low release of the pancreatic hormone-insulin, as well as the upsurge of blood sugar upon directly ingesting food [1,2].
In third world countries and globally, the predominance of T2D is ascribed to the modifications in lifestyle, including the transition from home prepared food high in phytonutrients (i.e., Polyphenols) to a more Westernized type of food which might be considered less nutritionally sound [3]. Such lifestyle changes have resulted in the increase of the prevalence of prolonged and deteriorating diseases.
The therapeutic benefits of customary foods have assumed significant place lately as a result of benefits connected to their phytonutrients [4,5]. Legumes as well as other food plants possess significant benefits in preventing as well as managing prolonged diseases [4]. Table 1 presents the characteristics of the most frequent drugs used for T2D.
Synthetic medications, e.g., acarbose, viglibose, and miglitol, are alfa-glucosidase inhibitors while others include biguanides, thiazolidinediones, sulphonylureas, and meglitinides, which display discomforting side effects, such as stomach pain, swelling, the release of ammonia gas from digestion, swelling of the stomach caused by dwelling gas, as well as the loss of fluid via the elementary canal [9]. Some of these discomforting symptoms are perhaps triggered by the production of ethanol as a result of the increased presence of bacteria; an end product from non-catabolized carbohydrates in the gastro intestinal (GI) track. Foods from plant sources generally comprise natural antioxidants such as phenolic compounds that can scavenge for ROS also referred to as free radicals [11,12,13,14,15,16,17].
With the use of new oral antidiabetics (OAD), such as gliptines, glucagon-like peptide-1 (GLP-1) analogues, gliflozines were approved for the treatment of T2D, demonstrating improved glycemic control, weight loss, and cardiovascular benefit [7]. The fruit content of plantain (Musa paradisiaca) is considered a major food product in Africa which provides a great source of energy for these people. Plantains are stated as an essential basis for pro-retinoids around continents (Asia, Africa, as well as Latin America).
Musa parasidiaca is rich in fat-soluble retinoids, water soluble B vitamins (thiamin, niacin, riboflavin and pyridoxine), and vitamin C. This food is discovered to be extremely rich in potassium but poor in sodium. Musa parasidiaca is an excellent source for vit A compared to other foods. Fat-soluble vit A (carotenoid) is considered to a safeguard against diabetes, heart disease, and cancer. The fat-soluble vitamin is among the best essential groups of phytonutrients which exhibit a vital role in the nutritious value of the plants. Plantain has been used in Nigeria to decrease blood sugar levels after a carbohydrate (CHO) meal. Plantain fits into the family of flowering plants eaten ripe or unripe using diverse methods of processing techniques, being cooked as well as fried. Additionally, products, such as flour and chips, have been made from plantain [10].
Bitter yam (Dioscorea dumetorum) is a food commonly used in tropical countries. This short (small) tuber fits into Dioscorea family. Collectively, it is referred to as bitter yam trifoliate (three–leaved) yam. It is believed to promote glucose balance for the diabetics and to be a therapeutic remedy for different diseases [18,19] Moreover, in the middle-belt region of Nigeria, the Tiv speaking tribe refers to it as ‘Anube’ used for consumption and medicinal purposes to treat illnesses [19].
Okra is unique as a flowering plant of the mallow family [13]. The okra fruit is eaten as a common plant in several nations (including Nigeria and Cyprus). It is rich in nutrients. Okra is known for its therapeutic importance, particularly in respect to lowering the blood glucose effect. While okra is usually seen as a plant that is beneficial to diabetic patients, a limited number of technical articles have acknowledged the therapeutic function that okra performs. Earlier research of Sabitha showed that okra oil extracts promoted hypoglycemic and low-fat beneficial effects, as well as improved the weight in Streptozotocin (STZ)-induced diabetic rats. Having a better anti oxidation capability, okra is known to reduce the oxidation of lipids, as well as raise the amount of Superoide Dismutase (SOD), Chloramphenicol acetyltransferase (CAT), as well as Glutathione (GSH). It is worth mentioning that decreased levels of GSH were found in the diabetic rats [9].
A useful food can be defined as food which delivers both nutritional and physiological supports to organisms or decreases the possibility of protracted ailments [16]. Okra fruit [17] has previously been shown to establish lower blood sugar as well as lower lipid actions, becoming a versatile and remarkable substitute to control hyperglycemia.
Nanoparticle production procedures can be easily performed as well as valid amidst wide variable medications. In these systems of delivering medication, polymeric nanoparticles have increased their significance, being eco-friendly, biocompatible, and due to their process of preparation much broadly obtainable. Hence, the variety of uses has been increasing to comprise a multiplicity of chemical medication groups and quantity systems [20,21]. Chitosan-based nanoparticles are mostly suitable and less toxic. Chitosan nanogel has been applied to manage production and the spreading of cell in the body, gastrointestinal tract disorders (GIT) disorder, heart disorder, and channeling medication reaching the central nervous system as well as eye impurities. New investigations in nanogel for oral medication (pills, capsules, syrups) have been centered around premises that increased acceptability of nanogel characteristics as well as techniques involving biochemical changes can be useful in specific nanogel therapeutic production as well as distribution structures. Chitosan is considered as one of the key derived products of chitin, made by eliminating the acetate part from chitin. It is a derivative of crustacean shells, such as those from prawns or crabs, and cell walls of organisms such as fungi. Its occurrence is natural as a polysaccharide. As a cation, extremely basic in nature, Chitin is obtained naturally, linked with peptides as well as elements that require detachment before the preparation of chitosan; hence, the methods of acidifying and alkalizing. After purification, acetyl groups are removed from chitin and substituted with amino group to produce chitosan. Nanogel acts in diffusing the openings of tight junctions of epithelium, enhancing the healing of wounds. Chitosan eases both the transport of therapies between and through cells. Chitosan relates with secretions which are negatively charged to bring about complex hydrophobic (water-hating) interrelationships. The acidic content in the primary amino group of nanogel is 6.5, similar to the amount of acetyl free linked amino group. Likewise, this class of acids aids the dissolving of nanogel hydrogen ion systems as well as the incomplete deactivation of primary amines, which could possibly elucidate the reason why chitosan has been described as concentrating acid from neutral to high hydrogen ion concentration [22]. Therefore, the user of nanoparticles is required to cautiously bring together the preferred chemical and physical characteristics of the chitosan, as well as the expected bio-system, using the chitosan treatment technique.
With this scientific evidence regarding the specified plant food (SFP), unripe plantain, bitter yam, and okra so far, the need to use them for the management of T2D has been limited to combining them alone [3,15,23,24,25] or in combination with NSFP [2,5,26,27,28], and those used separately or in combination are not cross-linked with chitosan [7,10,29]. However, where there is a cross-linkage with chitosan, those linkages are not with the SFP [30,31,32,33] (Table 2).
Chitosan acts by diffusing in the openings of tight junctions of epithelium, thereby enhancing the healing of wounds. The selected food plants (MFP-2 unripe plantain, bitter yam, and okra) acting in conjunction release plant insulin, which ultimately benefits diabetics most especially in complicated states of unhealing wounds on the limbs (the arms and legs). No scientific study so far has identified the combining or mixing effects of SFP with chitosan for the management of T2D. Hence, the present systematic and meta-analysis review aims to examine the relation of chitosan nanogel and MFP in T2D. MFP could improve the blood glucose level in association with antidiabetic drugs [10].
2. Methods
The systematic review was conducted in agreement with the 2009 PRISMA statement [43]. The review procedure was recorded with PROSPERO in March 2019 (CRD 42019129124).
2.1. Search Strategy
We searched for journal papers indexed in PubMed, Medline, Scopus, as well as Cochrane that were available from January 1990 to January 2021. The search was limited to T2D alone, generally available in the English language using the search terms: “unripe plantain, bitter yam, okra, chitosan with T2D.’’
2.2. Study Selection, Inclusion as Well as Exclusion Criteria
The review included only studies that examined unripe plantain, bitter yam, okra, and chitosan and their relation to type 2DM. Additionally, no human studies were included. Furthermore, we set a 28-year exploration boundary since therapeutic designs of over 30 years-old may change significantly from natural plant therapy to nutraceutical patterns [15]. Articles were searched and adjudicated. All searched articles were screened by titles and abstracts so as to retrieve useful journals deemed to be eligible. We revised journal paper completely according to standards set. Forms of differences were resolved by consensus-oriented discussion; where there was no resolution, a third party was consulted.
2.3. Information Extraction
Information on features involved in the revisions was taken out individually with the help of two critics. The first critic extracted textual data and the other graphical data (Figures). Authors were contacted where necessary through their e-mails or phone numbers published in their articles for additional or missing data. The data extracted were related to the number of experimental groups in the study design (i.e., the group which was induced and the one receiving intervention). Both species and sex of animal related to the characteristics of the animal model were extracted from the data. The intervention of interest, dosage, timing of dosage, and effectiveness of dosage on the animal’s data was extracted [44]. The primary outcome data support a reduction in hyperglycemia and the unit of measurement was milligrams per deciliter (mg/dL) or millimole per litre (mmol/L). All extracted data were in a continuous data pattern.
2.4. Assessing the Risk Bias
The method of assessing bias risk or assessing quality involved individually assessing risk associated with bias as well as studies included, which were evaluated by two external reviewers, one on text data and the other on graphical data (Figures). Disagreement was resolved by consensus-oriented discussions and where resolution was not reached, a third party was consulted. Studies were evaluated with the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool for assessing bias risk in animal studies [37]. We regarded individual areas to be at ‘low risk’, ‘unclear risk’ or ‘high risk’ of bias. We generally categorized the bias risk to be ‘low’ when the answer to the signaling questions for that domain was “Yes”, ‘high’ when the answer to the signaling questions was “No”, or as ‘unclear’ when there was insufficient information about that domain (Table 3).
2.5. Strategy for Information Investigation
Effects regarding outcome remained stated with statistical difference at 95%CI, considered from both end standards or modifying the starting point. Through studies, effects on blood glucose level remained constantly obtainable as milligram per deciliter or millimole per liter (mg/dL or mmol/L).
We synthesized approximations in statistical terms, employing prototypical unsystematic effects meta-analysis, founded on the postulation that comparable as well as procedural heterogeneity remained probable to occur as well as have consequence on the outcomes [45,46]. We employed regression on the moderator effect to evaluate differences among studies, as well as considered 95% CI employing moderator analysis (technique of moment estimation) (Figure 1).
Arithmetical irregularity remained calculated employing I2 value (Table 4 and Table 5).
We generated funnel plots (Figure 2) to examine the minor effect-change from studies (affinity about mediation properties projected in lower investigations varies since the ones projected in higher investigations may affect publication preferences, protocol, and comparable differences, among influences). Evaluations were directed employing meta-essentials software intended for meta-analyzing investigations and the result was a change in the statistics among free sets [45].
Hooijmans [37] reported that calculating the instant mark among separate investigations was not a good practice using the SYRCLE’s tool because an instant mark will involve allocating “loads” particular to known areas to tool, which will be problematic when justifying loads allocated. Moreover, loads could vary for every result and for every analysis.
2.6. Patients as Well as General Participation
While the investigation limited the enrollment of human participants, the evaluation was entirely focused on animals only. However, due to the nature of the research question, its result was extrapolated to patients and the public.
3. Outcomes (Results)
3.1. Explored Outcomes
The exploration of four automated records (Medline, Scopus, PubMed, and Cochrane) identified 405,919 collections through 454 journal papers left over once excluding replicas. Out of this number, 417 journal papers were disqualified as the titles and abstract were lacking our criteria, and those journal investigation reports were not of the standards set. Out of 37 selected journal papers, 19 investigational journal report papers were dropped due to not been a precise case investigation, in vivo as well as in vitro animal study, not SFP cross-linked with chitosan, not having modulator blockers or enzyme inhibitors, and not insulin stimulated or secreted on account of SFP as outcome. Thus, 18 studies were identified as eligible for inclusion in the review (Figure 3) [43].
3.2. Features of Involved Investigation as Well as Valuation of Intervention: T2D
The features of the involved investigations are presented in Table 6.
The invesstigations consisted of seven involving unripe plantain [2,5,11,26,35,36,47], one involving bitter yam [25], two involving okra [15,24], and eight involving chitosan [7,10,29,30,31,32,33,48] respectively. Almost all the included studies were in vivo case-controlled studies which were induced with diabetes using streptozotocin (STZ) and four others with alloxan monohydrate [2,5,30,35]. The major intervention from the studies was Type 2 diabetes with few other interventions in some studies, such as enzyme inhibition, weight change, lipid decrease/insulin resistance, sustained release time, and neuropathy. In all these interventions, SFP were used either in combination with other (NSFP) or used alone without cross-linking them with chitosan. As such, chitosan was used alone to encapsulate either insulin or other active compounds to aid their release over a sustained time. The main outcome measure in all the included studies was a decrease of blood glucose level in the animals.
3.3. The Bias Risk across Investigations
Complete information of the risk bias investigation of animal studies is presented in Table 7.
Amongst 18 case precise studies, bias risk was shared among the included studies between high risk of bias and low risk of bias for items present for the SYRCLE tool [44]. This high or great bias risk was due to the allocation concealment, unsystematic housing, blinding, and incomplete outcome data. This is a common practice in animal studies as the current design of protocols and reporting of animal studies are very poor [37].
3.4. Decrease in Blood Glucose Level
Hypoglycemic measures were examined in six studies [3,5,15,36,40,42]. Each of the studies were further examined by separating them into experimental groups: negative diabetic control at baseline and diabetic intervention group (the former was given no intervention-SFP or NSFP); subgroups were involved in meta-analysis as well as practical statistically significant positive effect on the studies (Figure 4). Therefore, the combined effect sizes of the studies were (mean difference 4.0 mg/dL, 95% CI −0.33–8.40 as well as the difference in mean of 4.4 mg/dL, 95% CI −0.82–9.66) as shown in the Forest plot (Figure 4 and Figure 5 respectively.
Due to the large proportion of I2 value (98%) in the studies (Table 4), we explored both the subgroup (Figure 4) and moderator (Figure 5) analyses, which proved that the investigations for meta-analysis came from a heterogeneous population. Hence, the extent of heterogeneity was examined. The random effect model was used to assume that there was heterogeneity in the subgroups. Consequently, the combined effect sizes in the subgroups (AA and BB) were not used. Instead, the prediction interval was used (mean difference 4.4 mg/dL, 95% prediction interval (PI) −6.65 to 15.50 and mean difference 3.4 mg/dL, 95% prediction interval −23.65 to 30.50) [45,49].
Due to the large proportion of I2 value (98%) in the studies (Table 4), we explored both the subgroup (Figure 4) and moderator (Figure 5) analyses, which proved that the investigations for meta-analysis came from a heterogeneous population. Hence, the extent of heterogeneity was examined [45,49]. The random effect model was used to assume that there was heterogeneity in the subgroups. Consequently, the combined effect sizes in the subgroups (AA and BB) were not used. Instead, the prediction interval (PI) was used (mean difference 4.4 mg/dL, 95% (PI) −6.65 to 15.50 and mean difference 3.4 mg/dL, 95% PI −23.65 to 30.50) rather than the estimate of its confidence interval (best vital result of ‘random outcomes’ representative; once the situation needs to be presumed ‘true’, outcome dimensions differ)
Regarding regression on moderator effect size (Figure 4), there was an observable strong correlation among moderator as well as detected influence dimensions. These were long-established with significant outcomes in the importance test of regression load p < 0.05 (Table 8).
This proved the value effect of the study sizes on the intervention. Furthermore, Figure 5 presents the funnel plot for the random effect meta-analysis on the mean difference in the decrease of blood glucose (mg/dL) based on the intervention or negative diabetic control, indicating asymmetry in the distribution of the effect sizes. Therefore, studies of this effect (X→Y) have been conducted in the following populations. The following weight change and enzyme inhibition population have not been studied. Observed effects range from −0.33 to 8.40. Effects in subgroup A “Diabetic intervention” range from −0.82 to 9.66. (Table 8) [45].
4. Discussion
This systematic review of case-controlled animal studies examining the decrease of blood glucose level in diabetic animals found evidence to support the notion that chitosan nanogel can relate to mixed unripe plantain, bitter yam, and okra in controlling T2D. The results remained similar when subgroup analysis was performed. The review questions the single use of the SFP, the use in combination with NSFP, and without cross-linking them with chitosan controlling T2D.
4.1. Principal Findings
Meta-analysis of the diabetic intervention subgroup demonstrated decreased hyperglycemia against blood sugar negative regulator [11,15,36,40,42,47]. However, studies from subgroup AA (diabetic intervention) influenced much of the bases for the overall decrease in blood glucose level as these studies were studies which had as primary outcome measure the decrease of blood glucose and secondary outcome measures including increase of body weight, inhibition ofα-amylase and α-glucosidase, as well as neuropathy [11,36,47,49].
Studies of the subgroup included in the meta-analysis gave results that agreed with the different analysis proving heterogeneity of the six studies formed the I2 value (Forest plot, subgroup analysis, moderator analysis and publication bias analysis [45]). As a consequence of this development, the overall combined effect sizes from the meta-analysis (Forest plot) were not useful due to the non-homogeneous studies included (not from a single population of population samples) [45,49].
4.2. Quality of Evidence
We reflected on the value of evidence which was reasonably low due to the following explanations: involved investigation remained at 50% high risk of bias and 50% at low risk of bias; with the high-risk bias coming from the designed protocol [44]. We also saw a high level of heterogeneity among the involved investigations (diabetic intervention). This heterogeneity could reflect the different populations being examined. For instance, the populations of the diabetic interventions that also had weight change, enzyme inhibition, and neuropathy were different from the population of diabetic intervention by a sustained release-time [4,31,41,47].
Ten out of the eighteen studies included in the systematic review were studies based on the SFP and NSFP (coco- yam, soya bean cake, cassava fibre and rice bran) [2,5,47,50], while eight studies used only chitosan to encapsulate active bio-compounds [16,30,33,39,40,41,42].
Furthermore, investigation involved in the review lasted between three and 84 days (three days [10,29]; five days [30]; eight days [30]; 10 days [42]; 14 days [3,32,42]; 21 days [36]; 28 days [3,4,5,24,33,35,51]; 31 days [50], and 84 days [15]). This proved the potency and efficacy of the intervention over both short and long durations. This meant that there was strong effect in the intervention given to the animals.
4.3. Limitation
This review had limitations. Our search strategy could have omitted abstracts and full text articles that were published in other languages besides English. This omission could have affected the number of studies included in the meta-analysis and the nature of the result with respect to a more homogeneous population [14,17].
5. Conclusions and Future Implication
As the quality of the included studies was moderately low in percentage (50%), which means that the overall risk of bias was unclear risk (50% low risk of bias and 50% high risk of bias), there was insufficient information provided by the study authors in their protocol, and final outcomes ought to be inferred cautiously. However, current evidence available does support the relation of chitosan to mixed unripe plantain, bitter yam, and okra for the management of T2D. We recommend that high quality case-controlled animal studies are carried out to substantiate whether chitosan nanogel should indeed be cross-linked with the SFP for the management of T2D.
Furthermore, research efforts could be geared towards extracting the phytonutrients contained in these food plants, concentrate and fractionate (partitioned) alike, so that extract fractions obtained can be used to test the efficacy of these food plants either through in vitro or in vivo experimentations.
Conceptualization, M.A. and E.A.; methodology, M.A. and E.A.; software, M.A. and E.A.; validation, K.N.F., C.P. and D.P.; formal analysis, MA.; investigation, E.A., K.N.F. and C.P.; resources, M.A. and E.A.; data curation, M.A. and E.A.; writing—original draft preparation, M.A.; writing—review and editing, M.A. and E.A.; visualization, M.A., E.A., K.N.F., C.P. and D.P.; supervision, E.A., K.N.F. and C.P.; project administration, E.A.; funding acquisition, E.A., K.N.F., C.P. and D.P. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Figure 1. Moderator analysis showing strong correlation between moderator and effect size for the included studies in meta-analysis.
Figure 2. Funnel plot showing random effect meta-analysis of mean difference in decrease of blood glucose level (mg/dL) based on diabetic intervention or negative diabetic control.
Figure 4. Forest Plot showing random effect meta-analysis of the mean difference in control of blood sugar level (mg/dL), based on diabetic intervention and negative diabetic control. Data for studies 1, 2, 3, and 4 are based primarily on control of blood sugar level whereas data for studies 5 and 6 are based on control of blood sugar level in sustained release-time.
Figure 5. Showing random effect meta-analysis of the mean different in total subgroup analysis for the decrease in blood sugar level (mg/dL).
Showing characteristics of common antidiabetic drugs used for T2D treatment.
Class of Antidiabetic Drug | Specific Mechanism of Action | Adverse Effect | Reference |
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Acabose—Used for treating T2D | Acarbose works by slowing down the action of certain chemicals that break down food to release glucose into the blood; slow food digestion helps to keep blood glucose from rising high after any meal. | Hyperglycemia, Shaking, Dizziness, Sweating, Irritability, Mood change, Headache, Numbness, Weakness, Pale skin, Hunger, Clumsy, Confusion, Seizures, Loss of consciousness, Extreme thirst, Frequent urination, Blurred vision, Dry mouth, Stomach upset, Vomiting, Shortness of breath, Breath that smells fruity and decreased consciousness. | [ |
Voglibose—Used as an α-glucosidase inhibitor that manages postprandial blood sugar in T2D. | α-glucosidase inhibitor; the saccharides, acting as competitive inhibitor of enzymes needed to digest carbohydrate specifically the α–glucosidases enzymes present in brush border of small intestine. | Seen in about 25% of users. Adverse effects include: Soft stool, Diarrhoea, Flatulence, Bloating, Abdominal pain or fullness and nausea. | [ |
Glyset (Miglitol)—A drug employed to treat symptoms of T2D. It can be used alone or in combination with this class of drugs. It belongs to a class of drugs referred to as Antidiabetics, α-glucosidase inhibitors. | Unlike Sulonylureas, Glyset (Miglitol) does not enhance insulin secretion. Antihyperglycemia action of Miglitol results from a reversible inhibition of membrane-bound intestinal α-glucosidase hydrolase enzymes. | Hives, Difficulty breathing, swelling of the face, Lips, Tongue, or throat, Severe diarrhea, Constipation, Bloody or tarry stools, rectal bleeding and diarrhea that contains blood or mucus. | [ |
Biguanides—This refers to a group of oral diabetes drugs that work by preventing the production of sugar in the liver, improving the body sensitivity towards insulin and reducing the amount of sugar absorbed by the intestines. | It works by preventing the liver from converting fat and amino acids into sugar. They also activate an enzyme which helps cells respond more effectively to insulin and takes in sugar from the blood. It is used by obese people as it promotes weight loss. | Hypoglycemia results very rarely, weight gain and digestive adverse reactions. | [ |
Thiazolidinedione (TZDs)—These are insulin sensitizers that act on intercellular metabolic pathways to enhance insulin action and increase sensitivity in critical tissues. | TZDs act by activating peroxisome proliferator-activated receptors. They are also agonist. The endogenous ligands for those receptors which are fatty acids and eicosanoids. This binds DNA when receptors activated. | Increase hepatitis and possible liver failure, Edema, Heart failure, Coronary Heart Disease (CHD), Plaque progression, Myocardia | [ |
Sulfonylureas—Stimulates the release of insulin from pancreatic Beta-cells and have a number of extra-pancreatic effects | Induces sugar independent-insulin release from Beta-cells by inhibiting potassium flux through Adenosine Triphosphate (ATP) dependent potassium channels. | Hypoglycemia, Induces hyponatremia, Edema, Induces alcohol flushing. | [ |
Meglitinides—these are oral drugs used for T2D. They work by triggering production of insulin. | Meglitinide (Rpaglinide)—This is an insulin secretagogue meaning that it binds to receptors on pancreatic beta-cells and stimulates insulin release. Repaglinide binds to an ATP-dependent potassium channel on beta-cells. | Hypoglycemia (low blood sugar) is associated with increased mortality and weight gain | [ |
Food plants and chitosan used for their therapeutic and benefit in T2D.
Food Plant and Chitosan | Therapeutic Use | Benefits/Nutritional Value | Reference |
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Unripe plantain (Musa paradisiaca) |
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[ |
Unripe plantain (Musa paradisiaca); soya bean cake and cassava fibre. |
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Unripe plantain (Musa paradisiaca) and (Dioscorea rotundata) |
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[ |
Unripe plantain (Musa paradisiaca) |
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Unripe plantain (Musa paradisiaca L.); cocoyam (Colocasia esculenta L.). |
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Unripe plantain (Musa paradisiaca L.); soya bean cake and rice bran. |
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Unripe plantain (Musa paradisiaca L.), Ginger (Zingber officinale). |
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Bitter yam (Dioscorea batatas) |
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[ |
Okra (Abelmoschus esculentus) |
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Okra (Abelmoschus esculentus) |
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[ |
Chitosan |
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Chitosan |
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[ |
Chitosan |
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[ |
Chitosan |
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[ |
Chitosan |
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[ |
Chitosan |
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[ |
Chitosan |
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[ |
Chitosan |
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[ |
Use of SYRCLE’s tool for assessing risk of bias.
Item | Type of Bias | Domain | Description of Domain | Review Author’s Judgement |
---|---|---|---|---|
1 | Selection bias | Sequence generation | There is direct evidence that cases and controls were similar, recruited within the same time frame, and controls are described as having no history of the outcome. | Yes * |
2 | Selection bias | Baseline characteristics | There is direct evidence that appropriate adjustments were made for covariates and confounders in the final analyses through the use of statistical models to reduce research-specific bias including standardization, matching of cases and controls, adjustment in multivariate model, stratification, propensity scoring, or other methods were appropriately justified. | Yes |
3 | Selection bias | Allocation concealment | There is insufficient information on concealment in the allocation of the animals into groups and subgroups. | No * |
4 | Performance bias | Random housing | There is direct evidence that the housing of animals was not random as they were kept in cages in the animal house. | No |
5 | Performance bias | Blinding | There is direct evidence that caregivers and researchers were not blinded or information was not provided. | No |
6 | Detection bias | Random outcome assessment | There is indirect evidence that it was possible for outcome assessors to infer the exposure level prior to reporting outcomes. | No |
7 | Detection bias | Blinding | Investigators also served as outcome assessors. There is direct evidence that exposure was consistently assessed using well-established methods that directly measure exposure like the blood glucose levels. | Yes |
8 | Attrition bias | Incomplete outcome data | There is no information provided on subject removal or exclusion from the study. | No * |
9 | Reporting bias | Selective outcome reporting | There is direct evidence that all of the study’s criteria were measured in the protocol, such as methods, abstract and introduction have been reported. | Yes * |
10 | Others | Other sources of bias | There is direct evidence that the other bias like “Units” was reported. Appropriate units such as mg/dL and mmol/L were assigned. | Yes * |
* Items in agreement with the items in the Cochrane Risk of Bias tool, Yes = Low Risk of Bias, No = High Risk of Bias.
Subgroup meta-analysis showing effect size, I2 and PI values for AA and BB.
# | Study Name/Subgroup Name | Effect Size | CI Lower Limit | CI Upper Limit | Weight | Q | PQ | I 2 | T2 | T | PI Lower Limit | PI Upper Limit |
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1 | Shodehinde et al., 2015 [ |
13.02 | 10.98 | 15.06 | 21.82% | |||||||
2 | Eleazu and Okafor; 2015 [ |
3.17 | 2.56 | 3.78 | 25.94% | |||||||
3 | Eleazu et al., 2013 [ |
2.06 | 1.51 | 2.60 | 26.03% | |||||||
4 | Huang et al., 2017 [ |
0.86 | 0.47 | 1.25 | 26.22% | |||||||
5 | AA | 4.42 | −0.82 | 9.66 | 17.78% | 162.77 | 0.000 | 98.16% | 5.01 | 2.24 | −6.65 | 15.50 |
6 | Lopes et al., 2017 [ |
2.18 | 1.62 | 2.74 | 49.87% | |||||||
7 | Raafat and Samy, 2014 [ |
4.66 | 4.17 | 5.15 | 50.13% | |||||||
8 | BB | 3.43 | 0.99 | 5.86 | 82.22% | 43.54 | 0.000 | 97.70% | 3.00 | 1.73 | −23.65 | 30.50 |
9 | Combined Effect Size | 3.60 | 1.03 | 6.17 | 258.29 | 0.000 | 98.06% | 4.07 | 2.02 | 1.03 | 6.17 |
N.B, AA = Diabetic intervention group, BB = Negative diabetic control group.
Publication bias analysis confirming effect sizes and I2 values.
Combined Effect Size | Observed | Heterogeneity | |
---|---|---|---|
Effect Size | 4.03 | Q | 258.29 |
Standard error | 1.70 | PQ | 0.000 |
CI Lower limit | −0.33 | I 2 | 98.06% |
CI Upper limit | 8.40 | T2 | 4.07 |
PI Lower limit | −2.75 | T | 2.02 |
PI Upper limit | 10.82 | ||
Combined effect size | Adjusted | Trim and Fill | On |
Effect Size | 4.03 | Estimator for missing studies | Leftmost Run/Rightmost run |
Standard error | 1.70 | Search from mean | Left |
CI Lower limit | −0.33 | Number of missing studies | 0 |
CI Upper limit | 8.40 | ||
PI Lower limit | −2.75 | ||
PI Upper limit | 10.82 |
General characteristics of included studies Baseline characteristics of rats or cell lines.
Stydy/Country | N, |
Study Duration | FP or Material and Family/BM/T | Reagent for Induction of Diabetes/SL(Average) Post Induction | Description of the Study | Outcome Measures with the Use of FP |
---|---|---|---|---|---|---|
Shodehinde, S.A. et al. Life Sci. 2015 [ |
42 male rats (in vivo), |
|
|
Streptozotocin/≥250 mg/dL | The effect of the diets on the blood glucose level, pancreatic α-amylase, intestinal and α-glucosidase content of the unripe plantain products was determined. |
|
Famakin, O. et al. J. Food Sci. Technol. 2016 [ |
60 Wistar albino, |
|
|
|
|
Blood glucose change from 355 ± 43 to 103 ± 14 mg/dL (p < 0.05). Weight change noted |
Ajiboye, B.O. et al., Food Sci Nutr. 2018 [ |
48 Albino rat, |
|
|
|
|
Blood glucose change from 350 to 100 mg/dL (p < 0.05). Physique heaviness as well as hyperglycemia was measured |
Eleazu, C.O.; Okafor, P. Interv. Med. Appl. Sci. 2015 [ |
48 male albino, |
|
|
|
|
|
Eleazu, C.O.; et al. J. Diabetes Res. 2013 [ |
40 male albino, |
|
|
|
|
Hyperglycemia as well as heaviness change
|
Sukanya, C. et al. Glyset (Miglitol). Bull Environ Contam Toxicol. 2016 [ |
35 Wistar albino, |
|
|
|
|
|
Iroaganachi, M.; et al., Biochem. J. 2015 [ |
30 male albino, |
|
|
|
|
|
Hooijmans, C.R.;et al., ILAR J. (2014), [ |
|
|
|
|
Suspended crude yam powder-treated diabetic; water extract of yam-treated diabetic and allantoin-treated diabetic group normal control, STZ-induced diabetic control |
|
Nguekouo, P.T.;et al., J. Food Biochem. 2018 [ |
|
|
|
|
|
Blood glucose change from 333 ± 20 to 119 ± 18 mg/dl (p < 0.05) |
Huang, C.; et al., PLoS One. 2017 [ |
|
|
|
|
|
Blood Glucose change from 500 to 120 mg/dL
|
Lee, J.; et al., J. Control Release. 2012 [ |
48 male db/db mice, |
|
|
|
|
Blood Glucose change from 150 to 57 mg/dL (p < 0.05)
|
Raafat, K.; et al., Evid. Based Compl. Alt. 2014 [ |
112 Swiss webster mice, |
|
|
|
|
|
112 Swiss, webster mice, |
|
|
Alloxan monohydrate, 200 mg/dL |
|
|
|
Ahn, S.; et al., J. Control Release, 2013 [ |
Mouse, |
|
|
|
|
|
Lopes, M.;et al.; Eur. J. Pharm. Biopharma. 2017 [ |
36 male wistar, |
|
|
Streptozotocin, ≥14 mM Subcutaneous (S.C.)
|
|
|
|
|
|
|
|
Sustained drug-release time |
|
Lee, C; et al., Acta Biomater. 2014 [ |
Murine, melanoma B16F10 cell lines (20,000 cells seeded), |
|
|
|
Blank DA-GC hydrogels were also administered as controls.
|
|
Song, L.; et al., Int. J. Nanomedicine. 2014 [ |
30 male mice, |
|
|
|
|
Blood glucose change from 60 to 20 mMolL (p < 0.05) and sustained drug release dosage. |
Jo, S.; et al., Int. J. Mol. Sci. 2013 [ |
30 male Sprague Dawley (SD), |
|
|
|
|
Blood Glucose change From193 to 152 mg/dL (p < 0.5), α-amylase and α-glucosidase inhibition at sustained time. |
Szekalska, M.; et al., 2017 [ |
30 male Sprague Dawley (SD), |
|
|
|
|
|
Grp—Group; Wt—Weight; Rts—Rats; FP—Foof Plant; BM—Bioactive Molecules; T—Toxicity; STZ—Streptozotocin; SL—Sugar level; NT—Non-Toxic; DN—Diabetic Neuropathy.
Risk of bias assessment in case-controlled animal studies.
Selection Bias | Selection Bias | Selection Bias | Performance Bias | Performance Bias | Detection Bias | Detection Bias | Attrition Bias | Reporting Bias | Others | Overall Review Author’s Judgement | Reference |
---|---|---|---|---|---|---|---|---|---|---|---|
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Low risk | Low risk | High risk | High risk | High risk | High risk | Low risk | High risk | Low risk | Low risk | Unclear * | [ |
Unclear * = Insufficient information; NB: Refer to
Regression of moderator on effect size showing a model y= −3.31791 + 0.13252x and p < 0.05.
B | SE | CI LL | CI UL | β | Z-Value | p-Value | |
---|---|---|---|---|---|---|---|
Intercept | −3.31791 | 1.81 | −7.98 | 1.34 | −1.83 | 0.067 | |
Moderator | 0.13252 | 0.03 | 0.06 | 0.21 | 0.91 | 4.45 | 0.000 |
Analysis of variance | Sum of squares (Q*) | df | p | Mean square | F-Value | p-value | |
Model | 19.79 | 1 | 0.000 | 19.79 | 19.75 | 0.011 | |
Residual | 4.01 | 4 | 0.405 | 1.00 | |||
Total | 23.80 | 5 | 0.000 | ||||
Combined effect size | 3.98 | ||||||
T2 (method of moments estimation) | 3.34 | ||||||
R2 | 83.16% |
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Abstract
This systematic review with metanalysis evaluated and analyzed the beneficial effects of certain plants food in type 2 diabetes (T2D) when consumed alone or in combination with chitosan. The main objective of the paper was to examine the relation of chitosan nanogel and mixed food plant (MFP) to control T2D. The databases included Medline, Scopus, PubMed, as well as Cochrane available between the month of January 1990 to January 2021. The eligibility criteria for selecting studies were case-controlled studies that included unripe plantain, bitter yam, okra, and chitosan either used-alone or in combination with non-specified food plants (NSFP). Two-fold autonomous critics retrieved the information required and evaluated the risk of bias of involved studies. Random-effect meta-analyses on blood glucose controls, were performed. Results of 18 studies included: seven that examined unripe plantains, one bitter yam, two okras, and eight chitosan, found regarding the decrease in blood glucose level. Meta-analysis of the results found a large proportion of I2 values for all studies (98%), meaning heterogeneity. As a consequence, the combined effect sizes were not useful. Instead, prediction interval (PI) was used (mean difference 4.4 mg/dL, 95% PI −6.65 to 15.50 and mean difference 3.4 mg/dL, 95% PI −23.65 to 30.50) rather than the estimate of its confidence interval (CI). These studies were at 50% high risk of bias and 50% low risk of bias and there was judged to be an unclear risk of bias due to the insufficient information from the included study protocol (moderately low). The intervention lasted between three and 84 days, indicating potency and effectiveness of the intervention at both short and long durations. Due to the moderately low quality of the studies, the findings were cautiously interpreted. In conclusion, the current evidence available from the study does support the relation of chitosan with mixed unripe plantain, bitter yam and okra for the management of T2D. Further high-quality case-controlled animal studies are required to substantiate if indeed chitosan nanogel should be cross-linked with the specified food plant (SFP) for the management T2D.
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1 Department of Life and Health Sciences, University of Nicosia, 46 Makedonitissas Ave., CY-2417, P.O. Box 24005, Nicosia CY-1700, Cyprus
2 Department of Health Sciences, College of Natural and Health Sciences, Zayed University, Khalifa B City, Abu Dhabi 144534, United Arab Emirates