From the three selected plants, polyphenolic compounds were mined from public database resources like PCIDB (Phytochemical interactions DB), Dr. Dukes DB, and literature search. Structural and chemical information of these phytocompounds were obtained from PubChem small molecule database (https://pubchem.ncbi.nlm.nih.gov/). This compiled dataset of bioactive compounds was filtered for duplicates and ubiquitous molecules.

Virtual screening was performed using Dock6.9 software developed by UCSF (Allen et al., 2015). We used a flexible docking approach for virtual screening as most of the phytocompounds had larger molecular weight and would help to accurately predict the binding mode as well as intermolecular interactions of selected phytocompounds with CT. The three dimensional structure of CT was retrieved from the RCSB structural database (PDB ID: 1XTC) that has five β-subunits bound to the one α-subunit. We prepared the CT structure by adding missing residues and refining the generated model by performing energy minimization using steepest descent algorithm followed by conjugate gradient. The grid was set at the region where CT was reported to bind with GM1 receptor and the binding pocket residues were selected from the earlier reported structures (Merritt et al., 1994). Amongst all the five chains of β-subunits, we chose chain F (shown in brown surface representation in Figure 1 ) which showed a larger cavity at the GM1 binding interface and hence considered it as a potential binding site.

The default parameters for flexible docking were selected in this study. Selected 20 compounds were prepared for docking by adding hydrogen and converting them into ‘mol2’ file format using Openbabel2.4. The ligand conformations were ranked by considering their grid score. Best docked conformations were selected by analysing their intermolecular interactions with the active site of CT causing the disruption of CT binding to the GM1 receptor.

Drug likeness prediction and side effects of top 10 hits with 1XTC were performed by submitting the canonical SMILES of each molecule to an online prediction server ADMETlab 2.0 (Xiong et al., 2021).

Based on the drug-likeness character, least grid score, and intermolecular interactions with active site residues, we prioritized two phenolic acids; Chlorogenic acid (C. arborea, P. granatum, and P. guajava) and Ellagic acid (C. arborea, P. granatum and P. guajava) and two flavonoids; Rutin (P. granatum and P. guajava), Phloridzin (P. guajava and P. granatum) for further MD simulation studies along with their respective standards Gallic acid and Quercetrin. The stability of these six complexes were studied by performing all-atom MD simulation in explicit solvent using gromacs ver. 2021 (Abraham et al., 2015; Khanal et al., 2022; Khanal et al., 2023). The partial charges on the ligands were generated using antechamber module of AmberTools21 and x-leap was used to generate a topology file for the entire complexes with Amber-99SBildn forcefield.

Complexes were solvated using TIP3P water model and systems were neutralized by adding the required number of counter ions. These solvated systems were subjected to energy minimization using the steepest descent followed by a conjugate gradient algorithm. These energy minimized systems were equilibrated using canonical ‘NVT’ and isothermal-isobaric ‘NPT’ ensembles where temperature and pressure kept constant to 300K and 1 bar, respectively. Further, unrestrained all-atom explicit MD simulations were performed for 100ns, and trajectories at every 2fs were recorded. The parameters for MD simulations were taken from earlier similar studies (Bhandare and Ramaswamy, 2018; Gangopadhyay et al., 2019; Dwivedi et al., 2022; Patil et al., 2022). The trajectories obtained were analysed using inbuilt gromacs tools, chimera was used to analyse individual snapshots, and generate publication quality images. The tool ‘g_mmpbsa’ was used to calculate the relative binding energy using MM/PBSA approach (Kumari and Kumar, 2014). Intermolecular interactions were investigated using Biovia Discovery studio visualizer 2021.

Bark of C. arborea, young leaves of P. guajava and fruit peel of P. granatum were collected in the Belagavi district of Karnataka, India. The collected plants and their parts were identified and authenticated by a certified plant taxonomist at ICMR-NITM, Belagavi. The voucher specimens were deposited in ICMR-NITM under accession numbers 1590 (C. arborea), 1690 (P. granatum), 1589 (P. guajava). Extraction of these powdered plant parts was carried out using 70% ethanol (v/v) in water by cold maceration technique (Ćujić et al., 2016). Six herbal compounds, including three phenolic acids, Ellagic acid (EA), Chlorogenic acid (CHL), Gallic acid (GA), and three flavonoids; Rutin (RTN), Phloridzin (PHD), and Quercetrin (QTRN), selected using in silico studies were procured from Sigma Aldrich. Quantification of these six compounds in hydro-alcoholic extract was performed using High-Performance Thin-Layer Chromatography (HPTLC).

CAMAG-HPTLC system was used for detection, separation and densitometric analysis of hydro-alcoholic extracts of C. arborea, P. guajava, P. granatum for selected six compounds (Pai et al., 2014; Pai and Joshi, 2018). The stock solutions of extracts and standards were prepared as 1.0 mg/mL in methanol except EA which was dissolved in 99.7% DMSO. Analysis was performed on a pre-coated TLC silica gel G60 F₂₅₄ plates (ALUGRAM) (10 × 10 cm) for phenolics (EA, CHL and GA) and RP-18W/UV₂₅₄ (ALUGRAM) (10 × 10 cm) for flavonoids (RTN, PHD and QRTN). Standards and sample bands (6 mm) were applied using CAMAG Linomat-5 TLC Sampler using 100 μl syringe. Band length 6 mm, application rate 50 μL/s distance from the bottom of the plate (Y) 10 mm, distance from edge of plate (X) 10 mm, distance between bands were auto set. The plates were developed up to a distance of 80 mm with toluene: ethyl acetate: methanol: formic acid in the ratio of 3:3:0.8:0.6 v/v (for phenolics) and tetrahydrofuran: water: formic acid in the ratio of 4: 6: 0.5 v/v (for flavonoids) as mobile phase. The details of peaks were recorded at 280 nm (for phenolics) and 310 nm (for flavonoids) using CAMAG TLC scanner 3 and WinCATS–Planar Chromatography Manager, (Version 1.4.4.6337), Switzerland.

Cell free culture filtrate (CFCF) of clinical strains of V. cholerae collected during cholera outbreaks in the years 2010 and 2012 from the southern Indian state of Karnataka, India were used in the current study (Roy et al., 2012; Dey et al., 2014). A single isolate efficiently secreting CT into CFCF was screened and selected using GM1 ELISA. CT procured from Sigma Aldrich was used as the standard to plot the CT standard curve. The clinical isolate of V. cholerae was cultured in AK1 media to stimulate the production of CT as described (Iwanaga et al., 1986). Initially, MH broth was inoculated with a pure culture of V. cholerae and grown for 12 hrs at 37°C. Then the inoculum size in MH broth was adjusted to 10⁵-10⁷cfu/mL, 1mL of this inoculum was added to 10mL of AK1 media in stationary tubes followed by incubation for 4hrs and subsequently transferred to a flask kept on a shaker at 150rpm for 16hrs at 37°C. CFCF was obtained by centrifuging the culture at 12000 rpm for 20 min and filtering the obtained culture supernatant through a sterile 0.22μm syringe filter. This unconcentrated CFCF was stored as multiple aliquots at -20°C until further use to prevent repeated freeze-thawing as it affects CT concentration in CFCF.

Pure CT reconstituted as 5mg/mL in deionized water was taken at known concentration from 1250ng/mL and diluted two-folds upto 39ng/mL whereas CFCF was taken at different dilutions (1:5; 1:10; 1:20 and 1:30) in PBS (pH7.4) and both were added to 96 micro-titer well pre-coated with GM1 (1.44μM). Distilled water and AK1 media were used as solvent controls for CT and CFCF respectively and the total volume in each well was made to 100μL with PBS. Initial incubation was carried out for 1 hr at 37°C, and GM1 ELISA was performed as described (Svennerholm and Wiklund, 1983) using polyclonal rabbit anti-CT antibody diluted 1:600 and anti-rabbit IgG-peroxidase diluted 1:200 in PBS procured from Sigma Aldrich. Absorbance was recorded at 492nm and the concentration of CT in CFCF was determined from the standard curve. This CFCF with quantified CT concentration was used for all the in vitro and in vivo experiments.

CHO cell line used for analysing cytotoxicity of six herbal compounds was procured from NCCS, Pune. Cytotoxicity of the six compounds on the CHO cell line was determined using the MTT assay as described (Plumb et al., 1989). CHO cells were seeded at a density of 20,000 cells/well and incubated for 24 hours at 37°C and 5% CO₂. The stock solutions of CHL, GA, RTN, PHD, and QRTN were prepared as 2 mg/mL in 0.05% DMSO, whereas EA stock was prepared as 2 mg/mL in 99.7% DMSO and filtered using 0.22μm syringe filters. After 24hrs, CHO cells were treated with increasing concentrations of six compounds, ranging from 18 to 700μg/mL each, in triplicates in DMEM media supplemented with 2% FBS and incubated for 24hrs at 37°C and 5% CO₂. Simultaneously, untreated cells and cells treated with DMSO were taken as cell control and vehicle control, respectively. Subsequently, cells were washed twice with PBS and treated with 20μL of 0.5% MTT solution in PBS for 4 hours, and formazan crystals formed after 4 hours were solubilized using DMSO. The absorbance was taken at 570nm and the IC₅₀ of six compounds on the CHO cell line was estimated using the cytotoxicity percentage.

Using IC₅₀ values, two non-cytotoxic concentrations (NC1 and NC2) for each of the six compounds were determined by using 25% and 12.5% of their respective IC₅₀ values, and the viability percentage was estimated by the MTT assay.

The binding inhibition of CT to GM1 by selected phenolic acids (EA and CHL) and flavonoids (RTN and PHD) along with their respective standards was determined by GM1 ELISA as described earlier. Initially, the CT concentration in CFCF was estimated from the CT standard curve. CFCF titer with a CT concentration of 3200ng/mL was diluted twofold up to 100ng/mL to plot the CFCF absorbance curve and to select the CT concentration exhibiting maximum absorbance at the highest dilution. The selected CFCF titer was treated with NC1 and NC2 of each of the six compounds and incubated on a shaker at 120rpm for four hours at 37°C. Later, this pre-incubated mixture was added along with CFCF control to a pre-coated GM1 96-well micro-titer plate, and GM1 ELISA was performed in triplicates. Simultaneously, each concentration of six compounds was also added in triplicates to get the background measurements, and the binding inhibition percentage was calculated.

Elevated cAMP levels in CT-induced CHO cell lines were evaluated using the abcam cAMP in vitro competitive ELISA kit as per the manufacturer’s instructions. CHO cells seeded at a density of 4x10⁴ cells/well in a 96-well microtiter plate were treated with a pre-incubated mixture containing CFCF (CT=100ng/mL) and each of six compounds at NC1 and NC2 in duplicates. Untreated CHO cells and cells treated with CFCF alone were taken as cell control and positive control, respectively. Concurrently, cells were also treated with each of the six compounds to establish that the selected compounds have no effect on the intracellular cAMP levels. The inhibitory activity of six compounds against CT-induced cAMP levels in CHO cell line was evaluated as an increase in bound percent (B%) of cAMP w.r.t. CFCF control.

The protective activity of six compounds against CT-induced cell elongation in CHO cell line was analyzed as described by Saha et al., 2013. CHO cells were seeded at a density of 6x10⁴/well in 12-well culture plates supplemented with 10% FBS + DMEM media and incubated for 24hrs at 5% CO₂ and 37°C. CFCF titer with CT concentration 100ng/mL was treated with NC1 and NC2 of each of six compounds and incubated at 37°C under shaking conditions at 120rpm for 4hrs. After 24 hrs, the pre-incubated mixture was added to CHO cells in duplicates supplemented with 2% FBS+DMEM media and further incubated for 18 hrs at 5% CO₂ and 37°C. CHO cells were also simultaneously treated with six compounds alone to check their effect on cell morphology. After 18 hrs, cells were washed twice with PBS, replenished with fresh media, and observed for morphological changes under a phase contrast microscope.

The ligated-ileal loop assay using adult Swiss albino mice was performed as described by Sawasvirojwong et al., 2013 to investigate the neutralizing activity of three phenolic acids, i.e. EA, CHL, and GA against CFCF-induced fluid accumulation. This animal study was approved by the Institutional Animal Ethical Committee of ICMR-NITM, Belagavi (Accession number: IAEC/ICMR-NITM BGM/2018/07). Six-week old Swiss albino mice weighing 25-30g were procured from the laboratory animal facility of MMDC, Belagavi, Karnataka and acclimatized under controlled conditions of temperature, humidity, and light at the Animal Research Facility of ICMR-NITM, Belagavi.

A total of 48 Swiss albino mice were randomized into 8 groups (n =6) and the grouping is detailed as (A) Saline control (Untreated): received 100ul of PBS/loop; (B) CFCF control: received CFCF with CT concentration (1µg/loop); (C) EA1: 50µg of EA + CFCF (CT 1µg)/loop; (D) EA2: 25µg of EA + CFCF (CT 1µg)/loop; (E) CHL1: 50µg of PGRPE + CFCF (CT 1µg)/loop; (F) CHL2: 25µg of CHL + CFCF(CT 1µg)/loop; (G) GA1: 50µg of GA + CFCF(CT 1µg)/loop; (H) GA2: 25µg of GA + CFCF (CT 1µg)/loop. Group C-H received a pre-incubated mixture of each of three herbal compounds at two variable concentrations with CFCF in each ligated-ileal loop.

Prior to the experiment, mice were fasted overnight, given free access to water, and later anaesthetized by Intraperitoneal injection of Ketamine-Xylazine (87.5mg/kg; 12.5mg/kg, respectively). A loop of distal ileum approximately 2 cm in length was exteriorized by making a small abdominal incision and tying at both ends using surgical thread. Without causing any injury to the tissue, these ligated-ileal loops were injected with a PBS/CFCF/pre-incubated mixture of three compounds with CFCF, gently restituted, and sutured. After 18 hrs, mice were sacrificed and ileal loops were excised. The protection of EA, CHL, and GA against CFCF-induced fluid accumulation was evaluated as the mean weight/length ratio of ligated-ileal loops.

The inhibitory activity of three phenolic acids against CFCF-induced cAMP levels in ligated-ileal loops was estimated using abcam competitive ELISA as per the manufacturer’s instructions. After 18 hours, the weight of ileal tissues excised from sacrificed mice was measured and stored at -80°C. Prior to the experiment, the ileal tissues from each group (A to H) were pooled and 100mg of tissue was homogenized using lysis buffer. The supernatant collected by centrifuging the homogenized tissue at 12000rpm for 10 min at 4°C was assayed for cellular cAMP levels.

Histological analysis of mice ligated-ileal loops was carried out by initially fixing them in 10% formalin and then the intestinal tissue sections were stained using hematoxylin and eosin. The histopathological changes were investigated as described by Sawasvirojwong et al. (2013) at 40X magnification using light microscopy.

Previously reported 20 polyphenolic compounds were chosen from three plants, excluding the pervasive molecules ( Supplementary Table 1 ). The docking study reveals the stable binding of selected 20 compounds to the preferred binding site (expected to bind to the GM1 receptor) with varying binding affinity. The grid score cut off for flavonoids and phenolic acids was selected based on grid scores of standards QRTN (-37.249) and GA (-28.355) ( Supplementary Tables 2 and 3 ). We have carefully analyzed the top 10 hits (including standard-gallic acid) to get more structural insights into their intermolecular interactions. All the selected 10 top hits from the flexible virtual screening show maximum binding affinity when compared to the standard GA. Table 1 represents the list of top 10 hits, their grid scores, and intermolecular interactions. The maximum number of combined H-bonding and other interactions are observed in the complex CT-Ellagic acid (10), followed by CT-Procyanidin B3 (9) and CT-Delphinidin (9).

The ADMET profile and drug-likeness of the top 10 hits are listed in Supplementary Table 4 . Phenolic acids showed a more favorable ADMET profile and drug-likeness compared to the flavonoids. From among the top 10 hits, we selected two phenolic acids and two flavonoids complexes with their respective standards based on their grid score and drug-likeness for further molecular dynamics simulation studies (CT-Ellagic acid, CT-Chlorogenic acid, CT-Gallic acid, CT-Rutin, CT-Phloridzin, and CT-Quercetrin). These complexes are abbreviated as CT-EA, CT-CHL, CT-GA, CT-RTN, CT-PHD, CT-QRTN, and these abbreviations are used in the entire manuscript hereafter. The binding modes (in 3D) and their atomic level intermolecular interactions (2D) for these six selected complexes are represented in Figures 2 , 3 .

Molecular dynamics simulations are used to investigate the structural stability and intermolecular interactions of the six complexes: CT-EA, CT-CHL, CT-GA, CT-RTN, CT-PHD, and CT-QRTN. The quality check was performed over the 100 ns trajectory generated using gromacs by analyzing potential energy of the simulated systems. The equilibration of the simulated complexes was confirmed by plotting the temperature and pressure over the MD simulation trajectory. It is observed that the temperature, pressure, and potential energy of the simulated complexes are stable with no considerable fluctuations. The temperature and pressure are maintained constant at 300K and 1bar, respectively, during the simulation in all the studied complexes ( Supplementary Figure 1 ). The average backbone RMSD value of these six complexes ranges between 1.5 and 3.5Å. It was observed that these complexes are well equilibrated during the 0 to 60 ns of the simulation and thereafter show stable dynamics throughout the simulation period ( Figure 4A ). The RMSD of chain F is stabilized at a value below 2.25Å except for the CT-GA complex, which showed a maximum RMSD value after 60 ns of simulation time ( Figure 4B ). The complex CT-EA and CT-PHD show the lowest RMSF values except for the flexible loop at the binding pocket region in the CT. The residues participating in the non-bonded interactions showed fewer fluctuations as their flexibility was arrested by stable intermolecular interactions ( Figure 4C ). The Rg value, analyzed for the entire CT complex and separately for Chain F, also revealed the stable dynamics during the 100ns simulation in all the complexes ( Figures 5A, B ). A similar observation was made for solvent accessible surface area analysis of the overall CT complex. However, variations in the SASA value of chain F (GM1 binding pocket) were observed during the simulation. The graphical representation of SASA with for CT and chain F is shown in Figures 5C, D , respectively.

From structural stability analysis, it is observed that docked complexes are well stabilized during the simulation. Therefore, we characterized intermolecular interactions in the initial and final MD simulation conformations. Furthermore, we also noted the intermolecular interactions precisely with the active site residues. The maximum number of H-bonds formed between CT and ligands during the MD simulations in all the six complexes is shown in Supplementary Figure 2 . The list of all the non-bonded interactions (H-bonds, hydrophobic interactions, etc.) that trigger stable complex formation before and after simulations is given in Supplementary Table 5 . Total non-bonded interactions are increased in the complexes CT-PHD (6 to 9) and CT-QTRN (3 to 12), whereas other complexes showed a decrease in the total non-bonded interactions in initial and final MD conformations. This revealed the consistent interactions with the binding pocket residues are increased in the complexes CT-PHD and CT-QRTN, whereas in other complexes these interactions are not consistent. The initial (0 ns) and final (100 ns) snapshots of the MD simulation trajectory are shown in Figure 6 . To gain more structural insights into these intermolecular interactions, we plotted the minimum distance between the six compounds and CT chain F ( Figure 7 ). It showed the distance of CT-EA and CT-PHD is constant <2.5Å, whereas in other complexes it showed significant fluctuations (up to 7Å). The relative binding energy of six complexes was calculated using the MM/PBSA approach and is represented in Table 2 . The order of binding free energy was observed as CT-EA > CT-CHL > CT-GA for phenolic acids and CT-PHD > CT-QRTN > CT-RTN for flavonoids. The selected polyphenolic compounds showed much higher binding affinity than their respective controls. This highlights the potency of these compounds in the successful inhibition of CT.

We analyzed conformational changes at the binding site over the simulation period using the DSSP tool. Supplementary Figure 3 represents the distortions in the secondary structure calculated in all the complexes (A-F). The binding pocket architecture was well stabilized in complexes CT-EA and CT-PHD compared to other complexes, mainly due to the increased helical content in the chain-F (also refer to Supplementary Videos 1-6 ).

The residue decomposition energy calculated over the stable trajectory revealed the contribution of individual resides in the binding energy ( Supplementary Figure 4 ). The positive contribution energy refers to the specific residue that does not favor the interactions, while the negative contribution energy refers to favorable interactions, binding pocket residues show the least binding energy. Most of the residues in complexes CT-EA, CT-PHD, and CT-CHL showed negative contribution energy. But in other studied complexes, the contribution energies varied a lot, which makes it hard for them to form stable complexes.

Quantitative analysis of phenolics (EA, CHL and GA) and flavonoids (RTN, PHD and QRTN) in in hydro-alcoholic extracts of C. arborea, P. guajava and P. granatum performed using HPTLC is represented in Table 3 . The HPTLC-PDA chromatogram are represented separately for phenolic acids and flavonoids in Supplementary Figure 5 .

Among the six selected compounds, GA was observed to be more cytotoxic to CHO cells with an IC₅₀ of 102.7 ± 1.14μg/mL whereas CHL, with its IC₅₀ value of 398.2 ± 5.4μg/mL showed the least cytotoxicity. The MTT assay revealed that two non-cytotoxic concentrations (NC1 and NC2) of each of the six compounds showed > 90% viability on the CHO cell line ( Figure 8 ). Table 4 lists the IC₅₀ of six compounds along with their respective NC1 and NC2.

Using the CT standard curve, the average concentration of CT in CFCF was calculated as 19.78 ± 0.52μg/mL. The maximum absorbance shown by the highest dilution of CFCF with a CT concentration of 1600ng/mL indicated the saturation of GM1 with CT. The selected six compounds (NC1 and NC2) were pre-incubated with CFCF titer with a CT concentration of 1600ng/mL and binding inhibition percentage (BI%) was evaluated using GM1 ELISA. Phenolic acids, EA, and CHL showed distinct activity against CT binding to GM1 compared to the standard GA, whereas, among flavonoids, PHD showed higher BI% ( Figure 9 ).

The elevation of cAMP levels in the CHO cell lines was determined as the bound percent (B%) of cAMP using competitive ELISA (cellular cAMP levels are inversely proportional to B%) following kit instructions. Significant reduction in cAMP levels (***p<0.001) was observed for all three phenolic acids compared with CFCF control at both NC1 and NC2, whereas flavonoids showed a significant reduction in cellular cAMP levels (***p<0.001) at NC1 only ( Figure 10 ).

The protective activity of phenolic acids and flavonoids against CFCF (CT=100ng/ml) induced cell elongation was investigated by phase contrast microscopy. All the selected compounds, excluding RTN, showed protection against CT-induced cell elongation at both NC1 and NC2. Further, EA and CHL showed greater protective activities among the selected six compounds ( Figure 11 ).

Based on in vitro results, EA, CHL, and GA at two concentrations (50µg and 25µg/loop) were selected for further in vivo validation. The mean weight/length (W/L) ratio of saline instilled ileal loops was 0.078 g/cm ± 0.01 and that of CFCF treated ileal loops was calculated as 0.249 g/cm ± 0.02. Ligated-ileal loops of mice treated with CFCF containing 1µg of CT caused significant intestinal fluid accumulation after 18 hrs of the incubation period ( ^ΔΔΔp<0.001) compared to Saline control. Interestingly, both EA (0.091g/cm and 0.094g/cm) and CHL (0.132g/cm, 0.176g/cm) showed a significant decrease (***p<0.001) in mean W/L ratio at 50ug and 25µg respectively, whereas standard GA (0.188g/cm) showed a significant reduction (**p<0.01) at 50ug in fluid accumulation induced by CFCF compared to CFCF control ( Figure 12 ). The mean W/L ratio of control and test groups is represented in Supplementary Table 6 .

Cellular cAMP levels in ligated-ileal tissues were estimated as an increase in bound percent (B%) using competitive ELISA. A significant increase in cAMP was observed in CFCF control ( ^ΔΔΔp<0.001) compared with the saline control group. Three selected phenolic acids showed significant inhibitory activity (***p<0.001) against CFCF-induced elevation of cAMP levels in ileal tissues ( Figure 13 ).

The histological changes of ileal loop tissue sections of all groups were observed after staining with Eosin and Hematoxylin ( Figure 14 ). After 18 hrs of treatment of CFCF, remarkable histopathological changes viz., increased inflammatory cellular infiltration in sub mucosa (green arrows, Figure 14.2C ) along with degeneration of mucosal tissue and diffused edema in mucosal and sub mucosal layers (red arrows, Figure 14.2D ) of the intestine were observed in CFCF control group compared to Saline control group ( Figures 14.2A, B ). Inflammation in sub mucosa is represented in Figure 14.2C and 14.2E. J, I for CFCF control and test groups respectively whereas diffused edema and mucosal tissue degeneration in mucosa is shown in Figure 14.2D and 14.2F, H, J for control and test groups. Among the pre-treated groups, 50ug of EA and CHL showed substantial protective activity against CFCF induced histopathological changes as evidenced by decreased inflammation and edema in the intestinal tissues ( Figures 14.2E, F and 14.2G, H ). However, indistinct amelioration in histopathological changes was observed for the standard GA ( Figure 14.2I, J ) compared to CFCF control.