Displaying publications 1 - 20 of 62 in total

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  1. Bostan H, Salim N, Hussein ZA, Klappa P, Shamsir MS
    Adv Bioinformatics, 2012;2012:849830.
    PMID: 23091487 DOI: 10.1155/2012/849830
    Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD) is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.
  2. Kapitonova M, Gupalo S, Alyautdin R, Ibrahim IAA, Salim N, Ahmad A, et al.
    Avicenna J Phytomed, 2022;12(1):30-41.
    PMID: 35145893 DOI: 10.22038/AJP.2021.18113
    OBJECTIVE: Modern treatment of peptic ulcers includes antibacterial and gastroprotective medications. However, current anti-ulcer drugs possess severe side effects. Therefore, all attempts to find new effective medications free from side effects are justified. Though Berberis vulgaris is a medicinal plant commonly used for the treatment of numerous disorders, gastroprotective effect of its leaf extract was not investigated before.

    MATERIALS AND METHODS: Gastric ulcer was modelled in Sprague-Dawley rats after treatment with B. vulgaris leaf extract containing 0.07% of alkaloids, 0.48% of flavonoids and 8.05% of tanning substances, 10 or 50 mg of dry extract/kg, changes in the stomach mucosa were assessed semi-quantitatively, and the gastric wall was evaluated for prostaglandin E2 level using ELISA and assessed histologically by calculation of the lesion index.

    RESULTS: B. vulgaris leaf extract at the dose of 50 mg/kg reduced the macroscopic ulcer score and the microscopic lesion index, increased prostaglandin E2 concentration in the gastric wall significantly higher than atropine and B. vulgaris leaf extract 10 mg/kg.

    CONCLUSION: The gastroprotective effect of the high dose of B. vulgaris leaf extract may be due to stimulation of prostaglandin E2 secretion in the stomach, and anti-oxidative and anti-inflammatory properties of polyphenolic complex of flavonoids and tannins present in the leaves of this plant.

  3. Chew KT, Salim N, Abu MA, Abdul Karim AK
    BMJ Sex Reprod Health, 2018 Jun 01.
    PMID: 29972367 DOI: 10.1136/bmjsrh-2017-101869
    BACKGROUND AND OBJECTIVE: Intrauterine contraceptive devices (IUDs) are an important method to reduce unmet need for family planning and for prevention of unintended pregnancy. However, IUD use in Malaysia is still low. Doctors play a major role in influencing IUD uptake among women. This study was designed to evaluate doctors' knowledge, attitudes and perceptions towards IUDs and factors associated with their current practice.

    METHODS: A questionnaire was mailed to public and private contraceptive providers who practise in Kuala Lumpur, Malaysia.

    RESULTS: A total of 400 doctors were invited and 240 (60%) of them responded to the survey. Of the respondents, 161 (65.9%) were from the public or government sector and 89 (34.1%) were from the private sector. The knowledge score of doctors was classed as 'average', and correlated well with their previous training level, working position, number of patients seen in a week and number of contraceptive methods available in their facilities. The age, gender, working duration, availability of IUDs in the premises and number of IUD insertions in a month were not statistically associated with the providers' knowledge. The use of IUDs was low, especially among private doctors, and was significantly related to their knowledge of the method. Knowledge scores, perception and practice were significantly lower in the private sector.

  4. Altalib MK, Salim N
    Biomolecules, 2022 Nov 20;12(11).
    PMID: 36421733 DOI: 10.3390/biom12111719
    Information technology has become an integral aspect of the drug development process. The virtual screening process (VS) is a computational technique for screening chemical compounds in a reasonable amount of time and cost. The similarity search is one of the primary tasks in VS that estimates a molecule's similarity. It is predicated on the idea that molecules with similar structures may also have similar activities. Many techniques for comparing the biological similarity between a target compound and each compound in the database have been established. Although the approaches have a strong performance, particularly when dealing with molecules with homogenous active structural, they are not enough good when dealing with structurally heterogeneous compounds. The previous works examined many deep learning methods in the enhanced Siamese similarity model and demonstrated that the Enhanced Siamese Multi-Layer Perceptron similarity model (SMLP) and the Siamese Convolutional Neural Network-one dimension similarity model (SCNN1D) have good outcomes when dealing with structurally heterogeneous molecules. To further improve the retrieval effectiveness of the similarity model, we incorporate the best two models in one hybrid model. The reason is that each method gives good results in some classes, so combining them in one hybrid model may improve the retrieval recall. Many designs of the hybrid models will be tested in this study. Several experiments on real-world data sets were conducted, and the findings demonstrated that the new approaches outperformed the previous method.
  5. Kapitonova MY, Kuznetsov SL, Salim N, Othman S, Kamauzaman TM, Ali AM, et al.
    Bull. Exp. Biol. Med., 2014 Jan;156(3):393-8.
    PMID: 24771384 DOI: 10.1007/s10517-014-2357-8
    Morphological and phenotypical signs of cultured readaptation osteoblasts were studied after a short-term space mission. The ultrastructure and phenotype of human osteoblasts after Soyuz TMA-11 space flight (2007) were evaluated by scanning electron microscopy, laser confocal microscopy, and ELISA. The morphofunctional changes in cell cultures persisted after 12 passages. Osteoblasts retained the drastic changes in their shape and size, contour deformation, disorganization of the microtubular network, redistribution of organelles and specialized structures of the plasmalemma in comparison with the ground control cells. On the other hand, the expression of osteoprotegerin and osteocalcin (bone metabolism markers) increased; the expression of bone resorption markers ICAM-1 and IL-6 also increased, while the expression of VCAM-1 decreased. Hence, space flight led to the development of persistent shifts in cultured osteoblasts indicating injuries to the cytoskeleton and the phenotype changes, indicating modulation of bone metabolism biomarkers.
  6. Abdo A, Salim N
    ChemMedChem, 2009 Feb;4(2):210-8.
    PMID: 19072820 DOI: 10.1002/cmdc.200800290
    Many methods have been developed to capture the biological similarity between two compounds for use in drug discovery. A variety of similarity metrics have been introduced, the Tanimoto coefficient being the most prominent. Many of the approaches assume that molecular features or descriptors that do not relate to the biological activity carry the same weight as the important aspects in terms of biological similarity. Herein, a novel similarity searching approach using a Bayesian inference network is discussed. Similarity searching is regarded as an inference or evidential reasoning process in which the probability that a given compound has biological similarity with the query is estimated and used as evidence. Our experiments demonstrate that the similarity approach based on Bayesian inference networks is likely to outperform the Tanimoto similarity search and offer a promising alternative to existing similarity search approaches.
  7. Izadiyan Z, Basri M, Fard Masoumi HR, Abedi Karjiban R, Salim N, Shameli K
    Chem Cent J, 2017;11:21.
    PMID: 28293282 DOI: 10.1186/s13065-017-0248-6
    The aim of this study is the development of nanoemulsions for intravenous administration of Sorafenib, which is a poorly soluble drug with no parenteral treatment. The formulation was prepared by a high energy emulsification method and optimized by response surface methodology. The effects of overhead stirring time, high shear rate, high shear time, and cycles of high-pressure homogenizer were studied in the preparation of nanoemulsion loaded with Sorafenib. Most of the particles in nanoemulsion are spherical in shape, the smallest particle size being 82.14 nm. The results of the 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, a tetrazole reveal that the optimum formulation does not affect normal cells significantly in low drug concentrations but could remove the cancer cells. Finally, a formulation containing Sorafenib retained its properties over a period of 90 days. With characterization, the study of the formulated nanoemulsion has the potential to be used as a parenteral nanoemulsion in the treatment of cancer. Graphical abstractSchematic figure of high pressure homogenizer device.
  8. Khan A, Gul MA, Zareei M, Biswal RR, Zeb A, Naeem M, et al.
    Comput Intell Neurosci, 2020;2020:7526580.
    PMID: 32565772 DOI: 10.1155/2020/7526580
    With the growing information on web, online movie review is becoming a significant information resource for Internet users. However, online users post thousands of movie reviews on daily basis and it is hard for them to manually summarize the reviews. Movie review mining and summarization is one of the challenging tasks in natural language processing. Therefore, an automatic approach is desirable to summarize the lengthy movie reviews, and it will allow users to quickly recognize the positive and negative aspects of a movie. This study employs a feature extraction technique called bag of words (BoW) to extract features from movie reviews and represent the reviews as a vector space model or feature vector. The next phase uses Naïve Bayes machine learning algorithm to classify the movie reviews (represented as feature vector) into positive and negative. Next, an undirected weighted graph is constructed from the pairwise semantic similarities between classified review sentences in such a way that the graph nodes represent review sentences, while the edges of graph indicate semantic similarity weight. The weighted graph-based ranking algorithm (WGRA) is applied to compute the rank score for each review sentence in the graph. Finally, the top ranked sentences (graph nodes) are chosen based on highest rank scores to produce the extractive summary. Experimental results reveal that the proposed approach is superior to other state-of-the-art approaches.
  9. Elhaj FA, Salim N, Harris AR, Swee TT, Ahmed T
    Comput Methods Programs Biomed, 2016 Apr;127:52-63.
    PMID: 27000289 DOI: 10.1016/j.cmpb.2015.12.024
    Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support vector machine and radial basis function method.
  10. Awan MJ, Rahim MSM, Salim N, Mohammed MA, Garcia-Zapirain B, Abdulkareem KH
    Diagnostics (Basel), 2021 Jan 11;11(1).
    PMID: 33440798 DOI: 10.3390/diagnostics11010105
    The most commonly injured ligament in the human body is an anterior cruciate ligament (ACL). ACL injury is standard among the football, basketball and soccer players. The study aims to detect anterior cruciate ligament injury in an early stage via efficient and thorough automatic magnetic resonance imaging without involving radiologists, through a deep learning method. The proposed approach in this paper used a customized 14 layers ResNet-14 architecture of convolutional neural network (CNN) with six different directions by using class balancing and data augmentation. The performance was evaluated using accuracy, sensitivity, specificity, precision and F1 score of our customized ResNet-14 deep learning architecture with hybrid class balancing and real-time data augmentation after 5-fold cross-validation, with results of 0.920%, 0.916%, 0.946%, 0.916% and 0.923%, respectively. For our proposed ResNet-14 CNN the average area under curves (AUCs) for healthy tear, partial tear and fully ruptured tear had results of 0.980%, 0.970%, and 0.999%, respectively. The proposing diagnostic results indicated that our model could be used to detect automatically and evaluate ACL injuries in athletes using the proposed deep-learning approach.
  11. Asmawi AA, Salim N, Ngan CL, Ahmad H, Abdulmalek E, Masarudin MJ, et al.
    Drug Deliv Transl Res, 2019 04;9(2):543-554.
    PMID: 29691812 DOI: 10.1007/s13346-018-0526-4
    Docetaxel has demonstrated extraordinary anticancer effects on lung cancer. However, lack of optimal bioavailability due to poor solubility and high toxicity at its therapeutic dose has hampered the clinical use of this anticancer drug. Development of nanoemulsion formulation along with biocompatible excipients aimed for pulmonary delivery is a potential strategy to deliver this poorly aqueous soluble drug with improved bioavailability and biocompatibility. In this work, screening and selection of pharmaceutically acceptable excipients at their minimal optimal concentration have been conducted. The selected nanoemulsion formulations were prepared using high-energy emulsification technique and subjected to physicochemical and aerodynamic characterizations. The formulated nanoemulsion had mean particle size and ζ-potential in the range of 90 to 110 nm and - 30 to - 40 mV respectively, indicating high colloidal stability. The pH, osmolality, and viscosity of the systems met the ideal requirement for pulmonary application. The DNE4 formulation exhibited slow drug release and excellent stability even under the influence of extreme environmental conditions. This was further confirmed by transmission electron microscopy as uniform spherical droplets in nanometer range were observed after storage at 45 ± 1 °C for 3 months indicating high thermal stability. The nebulized DNE4 exhibited desirable aerosolization properties for pulmonary delivery application and found to be more selective on human lung carcinoma cell (A549) than normal cell (MRC-5). Hence, these characteristics make the formulation a great candidate for the potential use as a carrier system for docetaxel in targeting lung cancer via pulmonary delivery.
  12. Arbain NH, Salim N, Masoumi HRF, Wong TW, Basri M, Abdul Rahman MB
    Drug Deliv Transl Res, 2019 04;9(2):497-507.
    PMID: 29541999 DOI: 10.1007/s13346-018-0509-5
    Bioavailability of quercetin, a flavonoid potentially known to combat cancer, is challenging due to hydrophobic nature. Oil-in-water (O/W) nanoemulsion system could be used as nanocarrier for quercertin to be delivered to lung via pulmonary delivery. The novelty of this nanoformulation was introduced by using palm oil ester/ricinoleic acid as oil phase which formed spherical shape nanoemulsion as measured by transmission electron microscopy and Zetasizer analyses. High energy emulsification method and D-optimal mixture design were used to optimize the composition towards the volume median diameter. The droplet size, polydispersity index, and zeta potential of the optimized formulation were 131.4 nm, 0.257, and 51.1 mV, respectively. The formulation exhibited high drug entrapment efficiency and good stability against phase separation and storage at temperature 4 °C for 3 months. It was discovered that the system had an acceptable median mass aerodynamic diameter (3.09 ± 0.05 μm) and geometric standard deviation (1.77 ± 0.03) with high fine particle fraction (90.52 ± 0.10%), percent dispersed (83.12 ± 1.29%), and percent inhaled (81.26 ± 1.28%) for deposition in deep lung. The in vitro release study demonstrated that the sustained release pattern of quercetin from naneomulsion formulation up to 48 h of about 26.75% release and it was in adherence to Korsmeyer's Peppas mechanism. The cytotoxicity study demonstrated that the optimized nanoemulsion can potentially induce cyctotoxicity towards A549 lung cancer cells without affecting the normal cells. These results of the study suggest that nanoemulsion is a potential carrier system for pulmonary delivery of molecules with low water solubility like quercetin.
  13. Saleh Huddin A, Md Yusuf N, Razak MRMA, Ogu Salim N, Hisam S
    Infect Genet Evol, 2019 11;75:103952.
    PMID: 31279818 DOI: 10.1016/j.meegid.2019.103952
    It has been discovered that Plasmodium knowlesi (P. knowlesi) is transmitted from macaque to man. Thus, the aim of the present study was to determine P. knowlesi genetic diversity in both human (n = 147) and long-tailed macaque (n = 26) samples from high- and low-endemicity localities. Genotyping was performed using seven neutral microsatellite loci markers. The size of the alleles, multiplicity of infection (MOI), mean number of alleles (Na), expected heterozygosity (HE), linkage disequilibrium (LD), and genetic differentiation (FST) were determined. In highly endemic P. knowlesi localities, the MOI for human and long-tailed macaque isolates was 1.04 and 1.15, respectively, while the Na was 11.14 and 7.86, respectively. Based on the allele frequency distribution for all loci, and with FST 
  14. Saeed F, Salim N, Abdo A
    Int J Comput Biol Drug Des, 2014 01 09;7(1):31-44.
    PMID: 24429501 DOI: 10.1504/IJCBDD.2014.058584
    Many types of clustering techniques for chemical structures have been used in the literature, but it is known that any single method will not always give the best results for all types of applications. Recent work on consensus clustering methods is motivated because of the successes of combining multiple classifiers in many areas and the ability of consensus clustering to improve the robustness, novelty, consistency and stability of individual clusterings. In this paper, the Cluster-based Similarity Partitioning Algorithm (CSPA) was examined for improving the quality of chemical structures clustering. The effectiveness of clustering was evaluated based on the ability to separate active from inactive molecules in each cluster and the results were compared with the Ward's clustering method. The chemical dataset MDL Drug Data Report (MDDR) database was used for experiments. The results, obtained by combining multiple clusterings, showed that the consensus clustering method can improve the robustness, novelty and stability of chemical structures clustering.
  15. Hentabli H, Bengherbia B, Saeed F, Salim N, Nafea I, Toubal A, et al.
    Int J Mol Sci, 2022 Oct 30;23(21).
    PMID: 36362018 DOI: 10.3390/ijms232113230
    Determining and modeling the possible behaviour and actions of molecules requires investigating the basic structural features and physicochemical properties that determine their behaviour during chemical, physical, biological, and environmental processes. Computational approaches such as machine learning methods are alternatives to predicting the physiochemical properties of molecules based on their structures. However, the limited accuracy and high error rates of such predictions restrict their use. In this paper, a novel technique based on a deep learning convolutional neural network (CNN) for the prediction of chemical compounds' bioactivity is proposed and developed. The molecules are represented in the new matrix format Mol2mat, a molecular matrix representation adapted from the well-known 2D-fingerprint descriptors. To evaluate the performance of the proposed methods, a series of experiments were conducted using two standard datasets, namely the MDL Drug Data Report (MDDR) and Sutherland, datasets comprising 10 homogeneous and 14 heterogeneous activity classes. After analysing the eight fingerprints, all the probable combinations were investigated using the five best descriptors. The results showed that a combination of three fingerprints, ECFP4, EPFP4, and ECFC4, along with a CNN activity prediction process, achieved the highest performance of 98% AUC when compared to the state-of-the-art ML algorithms NaiveB, LSVM, and RBFN.
  16. Asmawi AA, Salim N, Abdulmalek E, Abdul Rahman MB
    Int J Mol Sci, 2020 Jun 19;21(12).
    PMID: 32575390 DOI: 10.3390/ijms21124357
    The synergistic anticancer effect of docetaxel (DTX) and curcumin (CCM) has emerged as an attractive therapeutic candidate for lung cancer treatment. However, the lack of optimal bioavailability because of high toxicity, low stability, and poor solubility has limited their clinical success. Given this, an aerosolized nanoemulsion system for pulmonary delivery is recommended to mitigate these drawbacks. In this study, DTX- and CCM-loaded nanoemulsions were optimized using the D-optimal mixture experimental design (MED). The effect of nanoemulsion compositions towards two response variables, namely, particle size and aerosol size, was studied. The optimized formulations for both DTX- and CCM-loaded nanoemulsions were determined, and their physicochemical and aerodynamic properties were evaluated as well. The MED models achieved the optimum formulation for DTX- and CCM-loaded nanoemulsions containing a 6.0 wt% mixture of palm kernel oil ester (PKOE) and safflower seed oils (1:1), 2.5 wt% of lecithin, 2.0 wt% mixture of Tween 85 and Span 85 (9:1), and 2.5 wt% of glycerol in the aqueous phase. The actual values of the optimized formulations were in line with the predicted values obtained from the MED, and they exhibited desirable attributes of physicochemical and aerodynamic properties for inhalation therapy. Thus, the optimized formulations have potential use as a drug delivery system for a pulmonary application.
  17. Salim N, Basri M, Rahman MB, Abdullah DK, Basri H
    Int J Nanomedicine, 2012;7:4739-47.
    PMID: 22973096 DOI: 10.2147/IJN.S34700
    During recent years, there has been growing interest in the use of nanoemulsion as a drug-carrier system for topical delivery. A nanoemulsion is a transparent mixture of oil, surfactant and water with a very low viscosity, usually the product of its high water content. The present study investigated the modification of nanoemulsions with different hydrocolloid gums, to enhanced drug delivery of ibuprofen. The in vitro characterization of the initial and modified nanoemulsions was also studied.
  18. Musa SH, Basri M, Fard Masoumi HR, Shamsudin N, Salim N
    Int J Nanomedicine, 2017;12:2427-2441.
    PMID: 28405165 DOI: 10.2147/IJN.S125302
    Psoriasis is a chronic autoimmune disease that cannot be cured. It can however be controlled by various forms of treatment, including topical, systemic agents, and phototherapy. Topical treatment is the first-line treatment and favored by most physicians, as this form of therapy has more patient compliance. Introducing a nanoemulsion for transporting cyclosporine as an anti-inflammatory drug to an itchy site of skin disease would enhance the effectiveness of topical treatment for psoriasis. The addition of nutmeg and virgin coconut-oil mixture, with their unique properties, could improve cyclosporine loading and solubility. A high-shear homogenizer was used in formulating a cyclosporine-loaded nanoemulsion. A D-optimal mixture experimental design was used in the optimization of nanoemulsion compositions, in order to understand the relationships behind the effect of independent variables (oil, surfactant, xanthan gum, and water content) on physicochemical response (particle size and polydispersity index) and rheological response (viscosity and k-value). Investigation of these variables suggests two optimized formulations with specific oil (15% and 20%), surfactant (15%), xanthan gum (0.75%), and water content (67.55% and 62.55%), which possessed intended responses and good stability against separation over 3 months' storage at different temperatures. Optimized nanoemulsions of pH 4.5 were further studied with all types of stability analysis: physical stability, coalescence-rate analysis, Ostwald ripening, and freeze-thaw cycles. In vitro release proved the efficacy of nanosize emulsions in carrying cyclosporine across rat skin and a synthetic membrane that best fit the Korsmeyer-Peppas kinetic model. In vivo skin analysis towards healthy volunteers showed a significant improvement in the stratum corneum in skin hydration.
  19. Syed Azhar SNA, Ashari SE, Salim N
    Int J Nanomedicine, 2018;13:6465-6479.
    PMID: 30410332 DOI: 10.2147/IJN.S171532
    Introduction: Kojic monooleate (KMO) is an ester derived from a fungal metabolite of kojic acid with monounsaturated fatty acid, oleic acid, which contains tyrosinase inhibitor to treat skin disorders such as hyperpigmentation. In this study, KMO was formulated in an oil-in-water nanoemulsion as a carrier for better penetration into the skin.

    Methods: The nanoemulsion was prepared by using high and low energy emulsification technique. D-optimal mixture experimental design was generated as a tool for optimizing the composition of nanoemulsions suitable for topical delivery systems. Effects of formulation variables including KMO (2.0%-10.0% w/w), mixture of castor oil (CO):lemon essential oil (LO; 9:1) (1.0%-5.0% w/w), Tween 80 (1.0%-4.0% w/w), xanthan gum (0.5%-1.5% w/w), and deionized water (78.8%-94.8% w/w), on droplet size as a response were determined.

    Results: Analysis of variance showed that the fitness of the quadratic polynomial fits the experimental data with F-value (2,479.87), a low P-value (P<0.0001), and a nonsignificant lack of fit. The optimized formulation of KMO-enriched nanoemulsion with desirable criteria was KMO (10.0% w/w), Tween 80 (3.19% w/w), CO:LO (3.74% w/w), xanthan gum (0.70% w/w), and deionized water (81.68% w/w). This optimum formulation showed good agreement between the actual droplet size (110.01 nm) and the predicted droplet size (111.73 nm) with a residual standard error <2.0%. The optimized formulation with pH values (6.28) showed high conductivity (1,492.00 µScm-1) and remained stable under accelerated stability study during storage at 4°C, 25°C, and 45°C for 90 days, centrifugal force as well as freeze-thaw cycles. Rheology measurement justified that the optimized formulation was more elastic (shear thinning and pseudo-plastic properties) rather than demonstrating viscous characteristics. In vitro cytotoxicity of the optimized KMO formulation and KMO oil showed that IC50 (50% inhibition of cell viability) value was >100 µg/mL.

    Conclusion: The survival rate of 3T3 cell on KMO formulation (54.76%) was found to be higher compared to KMO oil (53.37%) without any toxicity sign. This proved that the KMO formulation was less toxic and can be applied for cosmeceutical applications.

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