Synergistically engineered nanotransethosomes for co-delivery of methotrexate and baicalin for enhanced transdermal delivery against rheumatoid arthritis: Formulation, characterization, and invivo pharmacodynamic evaluation

Rheumatoid arthritis (RA) is a systemic autoimmune disease that significantly impacts the quality of life of those affected. Owing to the complex pathophysiology of RA, it is not possible for any singular treatment to entirely impede the progression of the disease. Hence, the current study aimed to adopt a holistic and synergistic approach towards the management of RA by means of a co-delivery strategy involving methotrexate (MTH), a conventional slow-acting anti-rheumatic drug, and baicalin (BCN), a bioactive phytochemical using a transethosomal (TRS) gel formulation. The present study aims to evaluate the potential benefits of administering MTH and BCN in nanoparticulate form, which may lead to improved stability and solubility, as well as enhanced penetration into the arthritic tissues of interest. The MTH-BCN-TRS that were synthesised exhibited small particle size of 151.3 nm and polydispersity index of 0.125, as well as a favourable zeta potential of -32.22 mV. Additional assessments were conducted, including a pharmacokinetic analysis, TEM, skin permeation analysis, and confocal microscopy. According to the Confocal laser scanning microscopy (CLSM) study, the formulated MTH-BCN-TRS gel exhibited superior MTH and BCN permeation through the skin layers when compared to the MTH-BCN suspension gel. The MTT experiment on Raw 264.7 and SW982 cell lines revealed a considerable reduction (P < 0.05) in the IC50 value of the MTH-BCN-TRS formulation (9.2 mM and 43.2 mM, respectively) in comparison to the drug suspension. According to the findings of the in vivo study, it was found that the MTH-BCN-TRS gel exhibits significantly promising anti-arthritic properties when compared to the conventional diclofenac gel. This was demonstrated through histopathological studies and radiographic analysis. Furthermore, skin irritation investigation on Wistar albino rats confirmed that the formulated MTH-BCN-TRS is a safe option for topical treatment on the skin. The present study has confirmed that the formulated TRS vesicles are a valuable carrier for the transdermal delivery of MTH and BCN, which may be used for the management of rheumatoid arthritis.

d-α-tocopheryl polyethylene glycol 1000 succinate surface scaffold polysarcosine based polymeric nanoparticles of enzalutamide for the treatment of colorectal cancer: In vitro, in vivo characterizations

In this study, Enzalutamide (ENZ) loaded Poly Lactic-co-Glycolic Acid (PLGA) nanoparticles coated with polysarcosine and d-α-Tocopheryl polyethylene glycol 1000 succinate (TPGS) were prepared using a three-step modified nanoprecipitation method combined with self-assembly. A three-factor, three-level Box-Behnken design was implemented with Design-Expert® software to evaluate the impact of three independent variables on particle size, zeta potential, and percent entrapment efficiency through a numeric optimization approach. The results were corroborated with ANOVA analysis, regression equations, and response surface plots. Field emission scanning electron microscopy and transmission electron microscope images revealed nanosized, spherical polymeric nanoparticles (NPs) with a size distribution ranging from 178.9 ± 2.3 to 212.8 ± 0.7 nm, a zeta potential of 12.6 ± 0.8 mV, and entrapment efficiency of 71.2 ± 0.7 %. The latter increased with higher polymer concentration. Increased polymer concentration and homogenization speed also enhanced drug entrapment efficiency. In vitro drug release was 85 ± 22.5 %, following the Higuchi model (R2 = 0.98) and Fickian diffusion (n < 0.5). In vitro cytotoxicity assessments, including Mitochondrial Membrane Potential Estimation, Apoptosis analysis, cell cycle analysis, Reactive oxygen species estimation, Wound healing assay, DNA fragmentation assay, and IC50 evaluation with Sulforhodamine B assay, indicated low toxicity and high efficacy of polymeric nanoparticles compared to the drug alone. In vivo studies demonstrated biocompatibility and target specificity. The findings suggest that TPGS surface-scaffolded polysarcosine-based polymer nanoparticles of ENZ could be a promising and safe delivery system with sustained release for colorectal cancer treatment, yielding improved therapeutic outcomes.

Development of an impedimetric sensor for susceptible detection of melatonin at picomolar concentrations in diverse pharmaceutical and human specimens

Our investigation aimed to create and manufacture an electrochemical impedance sensor with the purpose of improving the detection efficiency of melatonin (ME). To achieve this objective, we employed gold nanoparticles coated on polydopamine formed in glassy carbon electrodes (AuNPs/PDA/GCE) as a means to enhance the sensor's capabilities. A novel approach employing the signal-off strategy and electrochemical impedance spectroscopy (EIS) technique was utilized to determine ME. When the AuNPs/PDA/GCE electrode was immersed in a buffered solution containing ME, and the oxidation current of AuNPs was recorded, it was observed that the oxidation current of AuNPs decreased upon the introduction of ME molecules. The decrease in electrical current can be ascribed to the inhibitory impact of ME molecule adsorption on the electrode surface with applying -0.2 V for 150 s in acetate buffer solution (ABS) (pH, 5) through various mechanisms, which hinders the electron transfer process crucial for AuNPs oxidation. Consequently, by utilizing EIS, various concentrations of ME were quantified spanning from 1 to 18 pM. Moreover, the ME sensor achieved an impressive detection limit of 0.32 pM, indicating its remarkable sensitivity in detecting low concentrations of ME. Importantly, these novel sensors demonstrated exceptional attributes in terms of sensitivity, specificity, stability, and repeatability. The outstanding performance of these sensors, coupled with their desirable attributes, establishes their considerable potential for a wide range of practical applications. These applications encompass various fields such as clinical diagnostics, pharmaceutical analysis, environmental monitoring, and industrial quality control, where accurate and sensitive detection of ME is of utmost importance.

Synergistic effect of arsenic removal from petroleum condensate via liquid-liquid extraction: Thermodynamics, kinetics, DFT and McCabe-Thiele method

This work presents the purification of petroleum condensate by removing arsenic ions via liquid-liquid extraction (LLE). Influence of pure and synergistic extractants is investigated. In terms of the practicability, following parameters are examined: the type of extractant, operating time, and temperature. Response surface methodology is used to design parameters such as organic-aqueous ratio and extractant concentration. Under optimal conditions; a mixture of 1 mol/L HCl and 0.02 mol/L thiourea with an organic/aqueous ratio of 1:4 at 323.15 K for 60 min, the extraction of arsenic reached 78.2 %. Further, batch simulation via two-stage counter-current extraction, and estimation by McCabe-Thiele diagram proved to be enhanced arsenic extraction to 95.3 %. Analysis by FTIR show that arsenic ions in petroleum condensate are formed as triphenylarsine compound ((C6H5)3As). The process of arsenic removal proved to be zero-order endothermic, irreversible and spontaneous reaction. The results obtained from the density functional theory (DFT) confirm that arsenic ions react with the synergistic extractant: effectively forming a covalent bond (As-S).

Optimization of tetrastigma hemsleyanum extraction process based on GA-BPNN model and analysis of its antioxidant effect

Tetrastigma hemsleyanum (Tetrastigma hemsleyanum Diels et Gilg) is a valuable traditional Chinese medicine with various applications. In this study, we aimed to optimize the extraction process for the total extraction yield of five flavonoid components, namely kaempferol, quercetin, rutin, kaempferol-3-O-rutinoside, and astragalin from the Tetrastigma hemsleyanum root (THR), and explore its potential molecular mechanisms in treating oxidative diseases as well as antioxidant activity. To achieve these objectives, we employed the genetic algorithm-back propagation neural network (GA-BPNN), the Box-Behnken design (BBD) with 4-factors and 3-levels to establish the optimal ethanol extraction process for the total extraction yield of the 5 components. Using public databases, the "component core targets-disease core target genes" networks were built, as well as molecular docking. Furthermore, DPPH was used to examine the antioxidant activity of the extracts obtained from THR under the optimal extraction process. The experimental value of the total extraction yield of the 5 components achieved a maximum of 788.12 mg/kg when the ethanol concentration was 73%, the solid-liquid ratio was 26 g/mL, and the ultrasonic duration was 30 min, and the ultrasonic temperature was 76 °C. When docked with protein molecules such as 6Y8I, quercetin, and other components received moderate to high scores. When the total concentration of the 5 components was 3.033 μg/mL, the DPPH radical scavenging rate was 89.81%. Compared with the BBD method, the GA-BPNN method is more efficient and reliable for optimizing the extraction process of active ingredients in THR because of its good data-fitting ability.

In-vitro and ex-vivo antidiabetic, and antioxidant activities of Box-Behnken design optimized Solanum xanthocarpum extract loaded niosomes

One of the most prevalent lifestyle diseases, diabetes mellitus (DM) is brought on by an endocrine issue. DM is frequently accompanied by hyperglycemia, a disease that typically results in an excess of free radicals that stress tissues. The medical community is currently concentrating on creating therapeutic medications with roots in nature to lessen the damage associated with hyperglycemia. Solanum xanthocarpum has a number of medicinal benefits. The investigation aimed to produce and analyze niosomal formulations containing S. xanthocarpum extract (SXE). Niosomes were made by implementing the solvent evaporation process, which was further optimized using Box-Behnken design. Drug release, DPPH assessments, α-amylase inhibition assay, α-glucosidase inhibition assay, and confocal laser scanning microscopy (CLSM) investigation were all performed on the developed formulation (SXE-Ns-Opt). SXE-Ns-Opt displayed a 253.6 nm vesicle size, a PDI of 0.108, 62.4% entrapment efficiency, and 84.01% drug release in 24 h. The rat's intestinal CLSM image indicated that the rhodamine red B-loaded SXE-Ns-Opts had more intestinal penetration than the control. Additionally, the antioxidant effect of the obtained formulation was demonstrated as 89.46% as compared to SXE (78.10%). Additionally, acarbose, SXE, and SXE-Ns-Opt each inhibited the activity of α-amylase by 95.11%, 85.88%, and 89.87%, and also suppressed the enzyme of α-glucosidase by 88.47%, 81.07%, and 85.78%, respectively. To summarise, the establishment of the SXE-Ns-Opt formulation and its characterization demonstrated the legitimacy of the foundation. A promising candidate for the treatment of diabetes mellitus has been shown as in vitro studies, antioxidant against oxidative stress, CLSM of rat's intestine and a high degree of penetration of formulation.

Application of artificial neural networks for enhancing Aspergillus flavipes lipase synthesis for green biodiesel production

Biodiesel is a sustainable, and renewable alternative to fossil fuels that can be produced from various biological sources with the aid of lipases. This study developed a simple and novel fungal system for lipase biosynthesis to be used for catalyzing the oily residuals into biodiesel, employing the artificial neural network (ANN), and semi-solid-state fermentation (SSSF). Nigella sativa was selected among agro-industrial oily residuals as a substrate for lipase biosynthesis by Aspergillus flavipes MH47297. The effect of cultural humidity (X1), the surfactant; Brij 35 (X2), and inoculum density (X3) on lipase biosynthesis were researched based on the matrix of Box-Behnken design (BBD). The ANN together with a new fungal candidate and SSSF were then applied for the first time to model the biosynthesis process of lipase. The optimum predicted cultural conditions varied according to the model. The optimum predicted conditions were estimated separately by BBD (X1 = 5.8 ml water/g, X2 = 46.6 μl/g, and X3 = 62156610 spore/g) and ANN (X1 = 5.4 ml water/g, X2 = 54.2 μl/g, and X3 = 100000000 spore/g) models. Based on the modeling process, the response of lipase was calculated to be 214.95 (BBD) and 217.72 U (ANN), which revealed high consistency with the experimental lipase yield (209.13 ± 3.27 U for BBD, and 218 ± 2.01 U for ANN). Despite both models showing high accuracy, ANN was more accurate and surpassed the BBD model. Gas chromatography analysis showed that lipase successfully converted corn oil to biodiesel (29.5 mg/l).

Multivariate response surface methodology assisted modified QuEChERS method for the rapid determination of 39 pesticides and metabolites in medlar

A modified QuEChERS method coupled with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was established for residue analysis of 39 pollutants (34 commonly used multi-class pesticides and 5 metabolites) in medlar matrices (fresh, dried, and medlar juice). Samples were extracted using water with 0.1 % formic acid: acetonitrile (5: 10, v/v). The phase-out salts and five different cleanup sorbents (including N-propyl ethylenediamine (PSA), octadecyl silane bonded silica gel (C18), graphitized carbon black (GCB), Carbon nanofiber (C-Fiber) and MWCNTs) were investigated to improve the purification efficiency. The Box-Behnken Design (BBD) study was employed for an optimal solution of the volume of extraction solvent, phase-out salt, and the purification sorbents for the analytical method. The average recoveries of the target analytes in the three medlar matrices ranged from 70 % to 119 % with relative standard deviations (RSDs) of 1.0 %-19.9 %. Screening of market samples (fresh and dried medlars) collected from the major producing regions in China showed that 15 pesticides and metabolites were detected in the samples at concentrations of 0.01-2.22 mg/kg, and none of which exceeded the maximum residue limits (MRLs) set in China. The results showed that the risk of food safety by consumption of medlar products caused by the use of pesticides was low. The validated method could be used for rapid and accurate screening of multi-class multi-pesticide residues in Medlar for food safety.

Pineapple peel waste valorization for extraction of bio-active compounds and protein: Microwave assisted method and Box Behnken design optimization

Pineapple peel waste (PPW) is obtained in huge quantities out of pineapple canning industries and it is found to be rich in bioactive compounds with antioxidant activity and an opulent source of bromelain protein having commercial importance. To fulfil the purpose, microwave assisted extraction was considered. Three parameters varied were solvent to substrate ratio, microwave power and extraction time. The independent variables were solvent to substrate ratio (10:1 mL/g to 20:1 mL/g), microwave power (300 W-600 W) and extraction time (40 min-50 min). Optimization was done with three factors and three level Box- Behnken Design (BBD). Each of the experiment has been analysed for Total phenolic content (TPC), Total flavonoid content (TFC), Total tannin content (TTC) as well as for protein content. The Folin- Ciocalteu method was utilized for analysing TPC, TTC and the colorimetric method (AlCl₃) was used for the analysis of TFC, protein content was analysed by lowry's method and antioxidant activity making use of 2,2-diphenyl-1-picrylhydrazyl (DPPH). The p values were less than 0.05 which showed all the four models were significant. The experimental values and the predicted values were harmonious for the optimum conditions. The optimum condition obtained out of BBD were solvent to substrate ratio of 20:1 mL/g, microwave power of 600 W and extraction time 40 min. Antioxidant activity for the extract was found out by DPPH assay under the optimized conditions was 75% along with proteolytic activity of bromelain as 1647.612 GDUg_concentrate^-1.

Combination of zero-valent aluminum-acid system and electrochemically activated persulfate oxidation for biologically pre-treated leachate nanofiltration concentrate treatment

This study investigated the performance of combined zero-valent aluminum (ZVAl) and electrochemically activated persulfate (PS) oxidation for the leachate nanofiltration concentrate (NFC) treatment. Firstly, operating parameters in the ZVAl procedure were optimized and under the optimum conditions (ZVAl dose 1 g/L, initial pH 1.5) the removal efficiency of the chemical oxygen demand (COD), UV₂₅₄, and color were 22.39%, 29.03%, and 48.26%, respectively. Secondly, the effect of various anode types (Ti/RuO₂, Ti/IrO₂, and Ti/SnO₂) within the electrooxidation (EO) process was evaluated. The Ti/RuO₂ anode was found to be the most effective one in terms of pollutant removal efficiencies and operation cost. The efficiency of single, binary, and hybrid processes was evaluated by control experiments and the results were ranked as PS < ZVAl < ZVAl + PS < EO < EO + PS < EO + ZVAl < EO + ZVAl + PS. In the following part of the study, the Box-Behnken design was preferred to optimize the operating parameters of the hybrid EO + ZVAl + PS process. The COD, UV₂₅₄, and color removal efficiencies under optimum conditions (4.88 mM PS dose, 1.6 A current applied, and 120 min reaction time) were 62.1%, 75.2%, and 99.9%, respectively. The estimated and experimentally obtained data were close to each other. The pollutant removal efficiencies increased in parallel with the current density and reaction time; however, the effect of the PS dose remained at a negligible level. The obtained results indicate the effectiveness of the hybrid EO + ZVAl + PS process for the treatment of leachate nanofiltration concentrate under optimized conditions.

An optimized method for estimating glutaminase activity in biological samples

Spectrophotometric methodologies have been used to assess glutaminase activity, for which coloured complexes have been developed that measure spectrophotometry across the visible spectrum using different reagents. The present paper describes a precise, simple and reliable procedure for quantifying glutaminase activity, which is a key enzyme in glutamine hydrolysis and also involved in glutamine metabolism regulation. The procedure presented here measures glutaminase activity by incubating glutaminase enzyme at 37 °C for 20 min with a glutamine substrate dissolved in a buffer (pH 8.6). The enzymatic reaction contains suitable activity of glutamate oxidase, which acts to convert glutamate to hydrogen peroxide and 2-oxoglutarate. To terminate the enzymatic activity, a working solution containing pyridine-2,6-dicarboxylic (PDA) acid and ammonium vanadate (AV) was added following incubation. Oxo-peroxo-pyridine-2,6-dicarboxylato-vanadate (OPDV), a stable orange-coloured chelate complex measuring 435 nm spectrophotometrically, was produced by the interaction between the generated hydrogen peroxide and the supplied reagent. Using the response surface methodology (RSM) as an indicator of the assay's accuracy, we employed the Box-Behnken design (BBD) to improve the method's design (the OPDV-Glutaminase assay). Improvement factors were the volume of working reagent solution (PDA/AV), volume of glutamate oxidase solution (GO), and incubation time. In matched samples, this novel method was verified against a Bland-Altman plot assessment of glutaminase activity using the indophenol methodology. A correlation value of 0.99 between the two methods' comparisons showed that the novel protocol was equally applicable to the reference method.

Development of favipiravir loaded PLGA nanoparticles entrapped in in-situ gel for treatment of Covid-19 via nasal route

In 2019 the emergence of SARS-COV-2 caused pandemic situation worldwide and claimed ∼6.4 M lives (WHO 2022). Favipiravir (FAV) is recommended as a therapy for Covid-19 which belongs to BCS class III with a short half-life of 2-5.5h. Thus, the objective of current study was the development of favipiravir loaded PLGA nanoparticles (NPs) by box-behnken design. Moreover, these NPs were entrapped in thermosensitive gel to increase the permeation through nasal route. The nanoparticles exhibit particle size of 175.6 ± 2 nm with >70 ± 0.5 %EE. NPs showed PDI (0.130) and zeta potential (-17.1 mV) suggesting homogeneity and stability of NPs. DSC, XRD, and FTIR studies concluded absence of any interaction of FAV and the excipients. SEM and AFM studies demonstrated spherical morphology of NPs with smooth surface. The NPs entrapped in-situ gel showed clarity and pH 5.5-6.1. The gelation temperature of NPs dispersed in-situ gel was found in the range of 35 °C -37 °C. The gel has viscosity in range of 34592-4568 cps. The texture analysis profile of gel showed good gelling properties. Dissolution study suggested a sustained release of FAV from NPs (24h) and NPs dispersed gel (32h) as compared to FAV solution (4h). The gel showed good mucoadhesion properties (9373.9 dyne/cm²). Ex-vivo permeation through nasal mucosa of goat elucidated NPs dispersed gel demonstrated significantly higher permeation than solution and NPs. Therefore, it would be a prospective formulation to combat Covid-19 infection with high patient compliance.

Processing and properties optimisation of carbon nanofibre-reinforced magnesium composites for biomedical applications

In the last decade, magnesium alloys have been considered as absorbable metals for biomedical applications, while some have reached their clinical use as temporary bone implants. However, their widespread use is still limited by its strength and degradability. One way of improvement can be done by reinforcing magnesium alloys with carbon nanofibres to form composites. This work aims at developing carbon nanofibre-reinforced magnesium-zinc (Mg-Zn/CNF) composites with optimum strength and degradability while ensuring their biocompatibility. A response surface method was used to determine their optimum process parameters (composition, compaction pressure, and sintering temperature), and analyse the resulting properties (elastic modulus, hardness, weight loss, and cytocompatibility). Results showed that the optimal parameters were reached at 1.8% of CNF, 425 MPa of compaction pressure, and 500 °C of sintering temperature, whereby it gave an elastic modulus of 5 GPa, hardness of 60 Hv, and a weight loss of 51% after three days immersion in PBS. The composites exhibited a hydrophobic surface that controlled the liberation of Mg²⁺ and Zn²⁺ ions, leading to more than 70% osteoblast cells viability up to seven days of incubation. This study can also serve as a starting point for future researchers interested in finding methods to fabricate Mg-Zn/CNF composites with high mechanical characteristics, corrosion resistance, and biocompatibility.

Optimized synthesis of mono and bimetallic nanoparticles mediated by unicellular algal (diatom) and its efficiency to degrade azo dyes for wastewater treatment

The silver/palladium nanoparticles (Ag/Pd NPs) were efficiently absorb UV-Visible light and reveal greater photocatalytic activity as compared to monometallic NPs. The aim of this study is photodegradation of the industrial azo dye using bimetallic Ag/Pd NPs and monometallic Ag NPs in presence of UV light for wastewater treatment. Bacillariophyceae (diatom) algae extract was utilized for the green synthesized Ag and Ag/Pd NPs. Biosynthesized nanoparticles were characterized by various useful characterization techniques viz. UV-Vis, FT-IR, SEM, TEM, and XRD. The crystallite size is found to be ∼23 nm and ∼56 nm for Ag NPs and Ag/Pd NPs, respectively, which is same as results obtained from TEM analysis, as the particle size and shape were analyzed as ∼27 and ∼56 nm, with a spherical geometry. The NPs was used to develop the optimization parameters for dye degradation such as time, temperature, and NP concentrations. A total 15 runs were considered for the study and procured by statistical software. Response surface methodology technique was implied and Box-Behnken design (BBD) design was built into the workflow. The results of the present study manifested a good connection between experimental and predicted values (R² = 0.9838). Therefore, present study promises that the prepared NPs possess excellent photocatalytic activity against harmful dyes.

Electrocoagulation treatment of raw palm oil mill effluent: Optimization process using high current application

In the electrocoagulation wastewater treatment process, extremely polluted water treatment requires an effective technique, and using high current is one of those. This study aims to optimize electrocoagulation parameters such as operation time, electrodes gap and the initial pH by applying high current intensity to treat palm oil mill effluent (POME) via Box-Behnken design (BBD) method. Chemical oxygen demand (COD), biological oxygen demand (BOD), and suspended solids (SS) were used as the response variables in the quadratic polynomial model. Most of the selected models in the analysis of variance (ANOVA) have shown significant results. A high connection between the parameters and dependent variables was surprisingly discovered in this study which the obtained value of R² for removal percentage of COD, BOD and SS were 0.9975, 0.9984 and 0.9979 respectively. Optimal removal was achieved at 19.07 A of current intensity (equivalent to 542 mA/cm² of current density), 44.97 min of treatment time, 8.60 mm of inter-electrode distance and 4.37 of pH value, resulted in 97.21%, 99.26% and 99.00% of COD, BOD and SS removal respectively. This optimized scheme of operating parameters combination offers an alternate choice for enhancing the treatment efficiency of POME and also can be a benchmark for other researchers to treat highly polluted wastewater.

Statistical optimization for the efficacious degradation of reactive azo dyes using Acinetobacter baumannii JC359

The aim of this study is to biodegrade the reactive azo dyes- Reactive black 5 (B-GDN), Reactive red 120 (RP) and Reactive blue 19 (RNB) using bacteria Acinetobacter baumannii JC359. Optimization of the process variables such as pH, temperature, dye concentration, incubation time, inoculum volume and dynamic incubating conditions for dye decolorization were performed using One Factor At a Time (OFAT) approach. Box- Behnken Design (BBD) of Response Surface Methodology (RSM) was further used to optimize the process variables. Decolorization rates of 98.8% for B-GDN, 96% for RP and 96.2% for RNB were observed after treating with A. baumannii for 48 h using the obtained design value. UV-Visible spectrophotometry and FT-IR spectral scan of dye and degraded metabolites confirmed that biodegradation had taken place. Further, the phytotoxicity evaluation was performed with Vigna radiata seeds and the degraded metabolites proved to be non-toxic. Docking studies were performed and it was found that there was significant binding affinity between the dyes and azoreductase enzyme of A. baumannii. Thus, the biodegradation of these reactive azo dyes was found to be a suitable alternative for the effective treatment of textile dyes.

Prediction and optimization of adsorption properties for Cs+on NiSiO@NiAlFe LDHs hollow spheres from aqueous solution: Kinetics, isotherms, and BBD model

In this work, novel NiSiO@NiAlFe layered double hydroxides (LDHs) hollow spheres were prepared by hydrothermal method. It was worth noting that LDHs' grafting towards NiSiO hollow spheres could avoid the LDHs' aggregation, and thus enhanced the material's adsorption capacity. Furthermore, adsorption kinetics, adsorption isotherms, and Box-Behnken Design (BBD) model were conducted. Results indicated that NiSiO@NiAlFe LDHs hollow spheres had sufficient adsorption capability towards Cs⁺. The adsorption kinetics satisfied the pseudo-second-order adsorption model, Temkin model and Langmuir isotherm model. The adsorption process was efficient at the alkaline condition (pH = 10). The adsorption kinetics indicated that the adsorption process could reach the equilibrium in only 20 min. The maximum adsorption capacity of Cs⁺ towards NiSiO@NiAlFe LDHs hollow spheres was estimated to be 61.5 mg g^-1. Moreover, the adsorption thermodynamics indicated that the adsorption process was exothermal, feasible and spontaneous. Thus, NiSiO@NiAlFe LDHs hollow spheres presented a broad potential for treating cesium containing wastewater.

CrVI reductive transformation process by humic acid extracted from bog peat: Effect of variables and multi-response modeling

The present paper reports the efficiency of bog peat-derived humic acid (HA) in the reductive removal of hexavalent chromium (Cr^VI) from aqueous solution as affected by solution pH, the dose of Fe^III and reaction time (numeric variables) and light irradiation (categorical variable). A three-level Box-Behnken design (BBD) applied to design experimental matrix, model the effects and interactions of variables on four determined responses (residual concentration of dissolved Cr^VI, dissolved Cr^III, dissolved Fe^II and total Cr^VI) and optimize the experimental conditions for highest Cr^VI removal efficiency (Cr^VI RE). Reaction mechanisms are also well discussed. Regression models were developed and analyzed by the ANOVA test and models determination coefficient R². Obtained models were significant (F values > 13) and an excellent relationship between experimental and predicted responses (R²: 98.1-99.6%) was observed. The optimum conditions were established corresponding to the residual concentration of dissolved Cr^VI as an index for Cr^VI removal efficiency (RE). In the dark system, the highest Cr^VI RE (98.1%) was obtained under the following conditions: pH = 1, reaction time = 7 d and Fe^III dosage = 0.110 mM. In the light-irradiated system, the optimal Cr^VI RE of 98.3% was observed in pH = 1, reaction time = 5 d and Fe^III dosage = 0.075 mM. Almost all reduced Cr^III remained in the solution even at high pH value. No adsorption or precipitation of Cr^III on the HA surface at pH 5 was confirmed by surface analyses of HA using X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM).

Selective extraction of polar lipids of mango kernel using Supercritical Carbon dioxide (SC-CO2) extraction: Process optimization of extract yield/phosphorous content and economic evaluation

Lipids are biomolecules extracted from plant sources and plant residues and have a beneficial role in various food, nutrition and medical applications. Supercritical carbon-dioxide as an advanced high-pressure technology which increases the productivity and has negligible environmental impact is employed for the selective extraction of polar lipids from the lipid matrix in mango kernel for the first time. The process parameters affecting the extraction such as pressure, temperature and the flow rate of CO₂ are ranged in the intervals of 30-50 MPa, 40-60 °C and 10-30 g min^-1, respectively. Optimization using Box Behnken design obtained the highest yield of 3.38% at 40 °C, 50 MPa and 30 g min^-1. The phosphorous content was evaluated to understand the behaviour of polar lipids extraction at higher pressures. The study showed the effect of process parameters having significant influence on polarity and solvating capacity of CO₂ which enabled for the extraction of polar lipids adding value to the mango kernel converting waste into valuable industrial products. The economic evaluation estimates the return on investment of a plant processing 3000 tons of mango kernel per year to account net present value (NPV) almost five times higher than the investment expenses and the payback period is under 4 years.

Tailoring lipid nanoconstructs for the oral delivery of paliperidone: Formulation, optimization and in vitro evaluation

PURPOSE

The present research work involves Quality by Design (QbD)-based fabrication of lipid nanoconstructs (LNC) of paliperidone (PPD) bearing superior biopharmaceutical attributes.

METHODS

LNC of paliperidone was prepared by melt emulsification-probe sonication and high-pressure homogenization method followed by optimization using QbD approach. Preparing LNC by both these methods will give the benefit of identifying the best optimized formulation which will be further evaluated for in vitro studies.

RESULTS

The best optimized formulation was obtained using melt emulsification-probe sonication technique with small particle size (86.35 nm), high entrapment efficiency (90.07 %), and high loading capacity (8.49 %). The drug release from LNC was found to be 5, 8, and 9-folds greater than drug suspension in pH 1.2, 6.8, and 7.4 respectively (p < 0.001). Stability studies of LNC in simulated gastric fluid pH 1.2 and fasted state simulated intestinal fluid depicted no alteration in particle size and polydispersity index of LNC but were found to increase in fed state simulated intestinal fluid. The drug permeability through rat intestine for LNC was found to be approximately 6-folds (p < 0.05) greater as compared to the drug suspension which was further confirmed by confocal microscopy. The in vitro lipolysis study presented significantly highest solubilization (p < 0.001) in the aqueous phase thereby anticipating higher in vivo absorption.

CONCLUSION

Thus, it was concluded that LNC bears the knack of improving the solubilization and permeation potential of an otherwise hydrophobic drug, paliperidone."

Datasets on the optimization of alginate extraction from sargassum biomass using response surface methodology

This article presents data associated with the extraction of sodium alginate from waste Sargassum seaweed in the Caribbean utilizing an optimization approach using Response Surface Methodology [1]. A Box-Behnken (BBD) Response Surface Methodology using Design Expert 10.0.3 software on the alkaline extraction process was used. Data consists of the effects of 4 process variables (temperature, extraction time, alkali concentration and excess volume of alkali: dried seaweed) on the yield of sodium alginate. The model was validated, and extracts were characterization using High Performance Liquid Chromatography (HPLC), Gel Permeation Chromatography (GPC), Fourier Transform Infrared Spectroscopy (FTIR) and Nuclear Magnetic Resonance (NMR). The data illustrates the applicability of our model in potentially valorizing this waste product into a valuable resource. Furthermore, our methodology can be applied to other macroalgae for efficient extraction of sodium alginate of commercial quality.

Application of a new metal-organic framework of [Ni2F2(4,4'-bipy)2(H2O)2](VO3)2.8H2O as an efficient adsorbent for removal of Congo red dye using experimental design optimization

The new metal-organic framework of [Ni₂F₂(4,4'-bipy)₂(H₂O)₂](VO₃)₂.8H₂O was synthesized by a sonochemical method for the adsorptive removal of Congo red (CR) in a batch system. It was characterized by infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), thermogravimetric (TGA), and elemental analyses. Box-Behnken design (BBD) was applied to obtain an appropriate regression model for removal percent (R%) of CR dye. The optimized conditions for three effective factors: adsorbent dosage, temperature, and CR concentration were m = 0.0107 g, T = 45 °C, and C_d = 50 mg.L^-1, respectively, while maximum removal percent is 96%. Langmuir isotherm shows that the maximum monolayer adsorption capacity (q_max) is 242.1 mg.g^-1. The pseudo-second-order kinetic model better describes the adsorption kinetics behavior. Thermodynamic parameters illustrate that the adsorption process is endothermic and spontaneous chemisorption. The aim of this study is the introduction of a new metal-organic framework that can adsorb Congo red with high adsorption capacity. Therefore, due to synthesis of the new metal-organic framework as a high efficient adsorbent for Congo red removal, and also multivariate optimization of removal conditions, this study outright is novel.

Design and Development of Lomustine Loaded Chitosan Nanoparticles for Efficient Brain Targeting

AIMS

The present research work discussed the preparation of lomustine loaded with chitosan nanoparticles (LNCp) by ionic gelation method with homogenization using the design on experiments by Box-Behnken design.

METHODS

The nanoparticles are evaluated by particle size, zeta potential, surface morphology, drug content, entrapment efficiency and in-vitro drug release.

RESULTS

The FT-IR results support that drug have no interaction with excipients, which are used in the preparation of nanoparticle. The particle size, drug content and encapsulation efficiency of the developed nanoparticles ranged from 190 to 255 nm, 80.88% to 94.02%, and 77.12 to 88.74%, respectively. The drug release rate is diffusion-controlled over 8 hours. The F-value for all of the responses shows that the models are significant. The p-value, less than 0.05 for all the responses reveals the significance of the models. Graphical optimisation is done by desirability plot and overlay plot, which contains optimal values of independent variables with the desirability of 1.

CONCLUSION

In conclusion, the results suggested that the optimised lomustine loaded chitosan nanoparticles are useful for brain targeting hence hold the potential for further research and clinical application.

Adsorptive removal of surfactant using dolochar: A kinetic and statistical modeling approach

Disturbingly high rates of consumption of surfactants in household and industries have led to mark them as emerging contaminants in the environment. In the present work, removal of sodium dodecyl sulfate (SDS), an anionic surfactant, using an industrial waste (dolochar) was explored. The adsorbent material was characterized with the help of Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Kinetic evaluation was performed using first, pseudo-first, second, and pseudo-second order models. Adsorption of SDS over dolochar was expressed best by pseudo-second order kinetic model with regression coefficient (R² ) of .99. Three input parameters including adsorbent dose (20-10 g/L), initial concentration (30-100 mg/L) of the surfactant, and contact time (2-60 min) were chosen for optimization using response surface methodology based on Box-Behnken design (BBD) approach. A total of 15 experiments were run to examine the effect of these variables on removal of SDS by dolochar in a multivariate system. A regression analysis indicated the experimental data fitted well to a quadratic polynomial model with coefficient of regression (R² ) as .99. ANOVA and lack-of-fit test depicted the precision and efficiency of the model. The optimized conditions for SDS removal were found to be adsorbent dose 16.62 g/L, contact time 40 min, and initial concentration 47 mg/L with removal efficiency as 98.91%. PRACTITIONER POINTS: Daily ablutions and use of personal care products introduce a number of surfactants and recalcitrant compounds into the environment. Adsorption is a handy and easy to operate treatment technique to remove graywater pollutants. Kinetic and statistical modeling may be recommended as one of the most prominent tools to understand the removal mechanism. Decentralized treatment of graywater using industrial wastes is recommended as sustainable solution in the developing nations.

A new insight into highly contaminated landfill leachate treatment using Kefir grains pre-treatment combined with Ag-doped TiO2 photocatalytic process

This study investigates the performance of the combination of biological pre-treatment with Kefir grains (KGs) and photocatalytic process using Ag-doped TiO₂ nanoparticles (NPs) for the simultaneous removal of toxic pollutants from landfill leachate (LFL). After 5 days of 1% (w/v) KGs pre-treatment at 37 °C, TOC, COD, NH₄⁺-N, and PO₄^3- removal rates were 93, 83.33, 70 and 88.25%, respectively. The removal efficiencies were found to be 100, 94, 62.5, 53.16 and 47.52 % for Cd, Ni, Zn, Mn and Cu, respectively. The optimal conditions of Ag-doped TiO₂ photocatalytic process were optimized using Box-Behnken design and response surface methodology (BBD-RSM) to enhance the quality of pre-treated LFL. Interestingly, Ag-doped TiO₂ photocatalytic process increases the overall removal efficiencies to 98, 96, 85 and 93% of TOC, COD, NH₄⁺-N, and PO₄^3-, respectively. Furthermore, the removal efficiency of toxic heavy metals was gradually improved. In addition, KGs and Ag-doped TiO₂ exhibited excellent recyclability showing the potential of combined biological/photocatalytic process to treat hazardous LFL.

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches

Textile industry wastewaters, which cause serious problems in the environment and human health, include synthetic dyes, complex organic pollutants, surfactants, and other toxic chemicals and therefore must be removed by advanced treatment methods. Determination of appropriate treatment conditions for efficient use of advanced treatment methods is an important and necessary step. In the last thirty years, the Artificial Neural Network-Genetic Algorithm (ANN-GA) and Response Surface Methodology (RSM) have emerged as the most effective empirical modeling and optimization methods especially for nonlinear systems. Reactive Red 195 azo dyestuff was chosen as the target pollutant. The color removal efficiency was modeled and optimized as a function of Sono-Fenton conditions such as H₂O₂ dosage, Fe²⁺ dosage, initial pH value, ultrasound power, and ultrasound frequency, using ANN-GA and RSM. The generalization and predictive ability of these methods were compared using the results of the 46 experimental sets generated by the Box-Behnken design. The mean square errors for these models are 3.01612 and 0.00295, and the regression coefficients showing the superiority of ANN in determining nonlinear behavior are 0.9856 and 0.9164, respectively. In optimal conditions, the prediction errors with hybrid ANN-GA and RSM models are 0.002% and 3.225%, respectively.

Modeling and optimization data analysis on photocatalytic decolourization of amido black 10B using ZnO catalyst

This article contains the experimental and statistical data related to decolourization of Amido Black 10B using photocatalytic process. Box-Behnken experimental design (BBD) has been used to study the influence of operational parameters on photocatalytic oxidation of Amido Black 10B by using zinc oxide (ZnO) as a catalyst. This data set presents a concise description of experimental conditions for variable factors such as initial dye concentration of 100 ppm, oxidant dosage 20 mMol/L and catalyst dose 1g/L at natural pH for 4 hr of reaction time in presence of 12W intensity ultra-violet radiation were optimized for over a response parameter, decolorization efficiency of Amido Black 10B. The effects of decolorization on process variables were investigated by developing a mathematical model, results indicated that ZnO can be used as an efficient catalyst for the decolorization of Amido Black 10B. Analysis of variance (ANOVA) showed a high coefficient of statistical measure value (R² = 0.9915) and prediction of the driven regression model was found to be satisfactory.

Development of Timolol Maleate Loaded Chitosan Nanoparticles For Improved Ocular Delivery

BACKGROUND

The poor retention and penetration are the major issues in the bioavailability of drugs through ocular route. Recently, the natural polymers have been exploited for the development of nanoparticles to improve the ocular performance of various drugs. In the present investigation, nanoparticles of timolol maleate (TM) were developed by using chitosan polymer to improve its release through ocular delivery.

METHOD

Ionic gelation method was used for the development of timolol loaded chitosan nanoparticles by using a cross linking agent, sodium tripolyphosphate (NaTPP). The Box- Behnken design was used for the optimization of various parameters for the development of nanoparticles.

OBJECTIVE

The objective behind the study was to study the effect of three critical parameters; concentration of chitosan (X1), the concentration of NaTPP (X2), and the volume of NaTPP (X3) on the drug release from the prepared nanoparticles.

RESULTS

The results obtained showed that high level of the chitosan concentration and low level of the NaTPP concentration and the mid levels of the NaTPP volume resulted in high levels of encapsulation efficiency. The loading capacity was found maximum at a low level of chitosan and mid level of volume of the NaTPP with a low level of NaTPP concentration. The optimized batch (NP-2) showed that the entrapment efficiency was 75.34±0.17%, the particle size of 190.9 nm and in vitro cumulative percentage of drug release was 49.11±0.49% in 12 h.

CONCLUSION

The study concluded that chitosan nanoparticles loaded with timolol maleate resulted in improved drug release for ocular treatment.

Optimization of bioclogging in vermifilters: A statistical approach

In the present research, an experiment was conducted with the objective of optimization of the role of earthworms in alleviating the bioclogging of a horizontal subsurface flow vermifilter (HSSFVF), caused due to the application of organics rich brewery wastewater. In this experiment, for the optimization of bioclogging of the vermifilters, the Box-Behnken Design (BBD) and response surface methodology (RSM) were involved. Hydraulic loading rate (HLR), influent COD and earthworm density (EWD) are the variables against which the bioclogging of the HSSFVF has been optimized. EWD of 9475 earthworms/m³, HLR of 1.84 m³/m²-d and influent COD of 3701 mg/L have been observed as the optimized values for the minimum bioclogging in the vermifiltration of brewery wastewater. At this optimum boundary conditions, the reduction in hydraulic conductivity was obtained as 1.49%, against the predicted value of 1.67% based upon the BBD model. The verification of the model against real brewery wastewater yielded insignificant error and thus very strongly portrays the suitability of the derived BBD model. The study indicates that the bioclogging from the vermifilters can be minimized, if the variables are optimized using the response surface methodology.

Thermo-activated peroxydisulfate oxidation of indomethacin: Kinetics study and influences of co-existing substances

The widespread occurrence of non-steroidal anti-inflammatory drugs (NSAIDs) (e.g., Indomethacin) in the ambient environment has attracted growing concerns due to their potential threats to ecosystems and human health. Herein, we investigated the degradation of indomethacin (IM) by thermo-activated peroxydisulfate (PDS). The pseudo first-order rate constant (k_obs) of degradation of IM was increased significantly with higher temperatures and PDS doses. Moreover, when the initial pH value was raised from 5 to 9 the IM degradation was initially decreased and then increased. Basic conditions were favorable for the removal of IM in the thermo-activated peroxydisulfate system. A response surface methodology based on the Box-Behnken design (BBD) was successfully employed for the optimization of the thermo-activated peroxydisulfate (PDS) system. The presence of chlorine ions manifested a dual effect on the degradation of IM, while bicarbonate and SRFA (as a NOM model) reduced it. Radical scavenging tests and electron spin resonance (ESR) revealed that the dominant oxidizing species were SO₄^- and OH at pH 9. Furthermore, the TOC removal efficiency attained 28.8% and the release of Cl^-was 38.5% at 60 °C within 24min, while the mineralization rate of IM were 85.5% with the PDS concentration up to 20  mM at 2 h oxidation. To summarize, thermo-activated PDS oxidation is a promising technique for the remediation of IM-contaminated water.

Optimization of co-culture inoculated microbial fuel cell performance using response surface methodology

Microbial fuel cells (MFCs) are considered as promising technology to achieve simultaneous wastewater treatment and electricity generation. However, operational and technological developments are still required to make it as a sustainable technology. In the present study, response surface methodology (RSM) was used to evaluate the effects of substrate concentration, co-culture composition, pH and time on the performance of co-culture (Klebsiella variicola and Pseudomonas aeruginosa) inoculated double chamber MFC. From the statistical analysis, it can be seen that the performance of MFC was not influenced by the interaction between the initial COD and time, pH and time, pH and initial COD, time and initial COD. However, the interaction between the inoculum composition and time, pH and the inoculum composition, initial COD and inoculum composition significantly influenced the performance of MFC. Based on the RSM results, best performance (power density and COD removal efficiency) was obtained when the inoculum composition, initial COD, pH and time were about 1:1, 26.690 mg/L, 7.21 and 15.50 days, respectively. The predictions from the model were in close agreement with the experimental results suggesting that the proposed model could adequately represent the actual relationships between the independent variables generating electricity and the COD removal efficiency.

Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis

Purpose: The objective of this study was to synthesize and statistically optimize dimethyl fumarate (DMF) loaded solid lipid nanoparticles (SLNs) for better management of multiple sclerosis (MS).

Methods: SLNs were formulated by hot emulsion, ultrasonication method and optimized with response surface methodology (RSM). A three factor and three level box-behnken design was used to demonstrate the role of polynomial quadratic equation and contour plots in predicting the effect of independent variables on dependent responses that were particle size and % entrapment efficiency (%EE).

Results: The results were analyzed by analysis of variance (ANOVA) to evaluate the significant differences between the independent variables. The optimized SLNs were characterized and found to have an average particle size of 300 nm, zeta potential value of -34.89 mv and polydispersity index value < 0.3. Entrapment efficiency was found to be 59% and drug loading was 15%. TEM microphotograph revealed spherical shape and no aggregation of nanoparticles. In-vitro drug release profile was an indicative of prolonged therapy. In-vivo pharmacokinetic data revealed that the relative bioavailability was enhanced in DMF loaded SLNs in Wistar rats.

Conclusion: This study showed that the present formulation with improved characteristics can be a promising formulation with a longer half-life for the better management of MS.

Loteprednol Etabonate Nanoparticles: Optimization via Box-Behnken Design Response Surface Methodology and Physicochemical Characterization

BACKGROUND

Abstract: The objective of the present work was to prepare and optimize the loteprednoletabonate (LE) loaded poly (D,L-lactide co-glycolide) (PLGA) polymer based nanoparticle carrier. The review on recent patents (US9006241, US20130224302A1, US2012/0028947A1) assisted in the selection of drug and polymer for designing nanoparticles for ocular delivery applications.

METHODS

The nanoparticles were prepared by solvent evaporation followed by high speed homogenization. Biodegradable polymer PLGA (50:50) grade was utilized to develop various formulations with different drug:polymer ratio. A Box-Behnken design with 33 factorial design was selected for the present study and 17 runs were carried out in totality. The influence of various process variables (viz., polymer concentration, homogenization speed and sonication time) on the characteristics of nanoparticles including the in vitro drug release profile were studied.

RESULTS

The nanoparticulate formulations were evaluated for mean spherical diameter, polydispersity index (PDI), zeta potential, surface morphology, drug entrapment and in-vitro drug release profile. The entrapment efficiency, drug loading and mean particle size were found to be 96.31±1.68 %, 35.46±0.35 % and 167.6±2.1 nm respectively.

CONCLUSION

The investigated process and formulation variables were found to have significant effect on the particle size, drug loading (DL), entrapment efficiency (EE), and in vitro drug release profile. A biphasic in vitro drug release profile was apparent from the optimized nanoparticles (NPs) for 24 hours.

Formulation and Optimization of Topical Solid Lipid Nanoparticles based Gel of Dapsone Using Design of Experiment

OBJECTIVE

The present research work was designed to formulate and evaluate solid lipid nanoparticles (SLN) loaded gel of Dapsone (DS). An attempt was made to develop topical gel with better skin permeation rate.

METHOD

The SLN formulations of DS were prepared by microemulsion technique and evaluated for its in vitro characteristics. The effect of DS concentration in lipid phase (X1), Gelucire:Precirol ratio (X2) and lipid:Smix ratio (X3) on entrapment efficiency (Y1) and drug release (Y2) from SLN was studied using Box-Behnken design. The result of dependent variables was used to generate polynomial equations and the surface response and counterplots. The optimized SLN formulation was incorporated into the gel using 1% carbopol-934 as a gelling agent. The SLN loaded gel was characterized for pH, viscosity, percent drug content, in vitro drug release and ex vivo permeation through rat skin.

RESULTS

The optimized DS SLN formulation, with 20% drug loading, 0.5:1 as Gelucire : Precirol ratio in lipid phase and 1:3 as Lipid : Smix ratio, showed 95.64±0.2% drug entrapment, 61.1±0.6% of drug release after 8 h, particle size of 168.5 nm with polydispersity index of 0.335 and zeta potential of -16.8±6.1 mV. DS SLN gel demonstrated biphasic release pattern with greater drug permeation through rat skin (Jss, 39.27±2.1 µg/cm2/hr) as compared to plain DS gel (Jss, 22.64±1.8 µg/cm2/hr).

CONCLUSION

The present study demonstrated DS SLN gel as a possible alternative to a conventional topical formulation for the treatment of acne.

Development of chitosan based edible films: process optimization using response surface methodology

Three-factors Box-Behnken design of response surface methodology (RSM) was used to optimize chitosan level (1.5, 2.0, 2.5 %w/v), glycerol level (0.5, 0.75, 1.0 %w/v) and drying temperature (35, 40, 45 °C) for the development of chitosan based edible films. The optimization was done on the basis of different responses viz. thickness, moisture, solubility, colour profile (L*, a*, b* value), penetrability, density, transmittance and water vapor transmission rate (WVTR). The linear effect of chitosan was significant (p < 0.05) on all the responses. However, density was only significantly (p < 0.05) affected by glycerol in a negative linear fashion. Drying temperature also significantly (p < 0.05) affected thickness, penetrability, transmittance and WVTR in linear terms. The quadratic regression coefficient of chitosan showed a significant effect (p < 0.05) on moisture, solubility and WVTR; glycerol level on moisture, L* value and transmittance; and drying temperature on a* value, penetrability, transmittance and WVTR. The effect of interaction of glycerol x temperature as well as chitosan x temperature was also significant (p < 0.05) on a* value and WVTR of edible films. The optimized conditions were: 2.0 % w/v chitosan level, 0.75 % w/v glycerol level and drying temperature 40 °C at a constant time of 48 h. All the response variables were in favourable range including thickness; 108.59 mμ, penetrability; 16.41 N, transmittance; 75.60 %, WVTR; 0.00174 g/m(2)-t for the optimized edible film. Results concluded that edible films with desirable bio-mechanical properties can be successfully developed and effectively utilized in the food packaging industry.