Displaying publications 1 - 20 of 62 in total

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  1. Chandran R, Tohit ERM, Stanslas J, Salim N, Mahmood TMT, Rajagopal M
    Semin Thromb Hemost, 2024 Jan 15.
    PMID: 38224699 DOI: 10.1055/s-0043-1778103
    The management of hemophilia A has undergone a remarkable revolution, in line with technological advancement. In the recent past, the primary concern associated with Factor VIII (FVIII) concentrates was the risk of infections, which is now almost resolved by advanced blood screening and viral inactivation methods. Improving patients' compliance with prophylaxis has become a key focus, as it can lead to improved health outcomes and reduced health care costs in the long term. Recent bioengineering research is directed toward prolonging the recombinant FVIII (rFVIII) coagulant activity and synthesising higher FVIII yields. As an outcome, B-domain deleted, polyethylene glycolated, single-chain, Fc-fused rFVIII, and rFVIIIFc-von Willebrand Factor-XTEN are available for patients. Moreover, emicizumab, a bispecific antibody, is commercially available, whereas fitusiran and tissue factor pathway inhibitor are in clinical trial stages as alternative strategies for patients with inhibitors. With these advancements, noninfectious complications, such as inhibitor development, allergic reactions, and thrombosis, are emerging concerns requiring careful management. In addition, the recent approval of gene therapy is a major milestone toward a permanent cure for hemophilia A. The vast array of treatment options at our disposal today empowers patients and providers alike, to tailor therapeutic regimens to the unique needs of each individual. Despite significant progress in modern treatment options, these highly effective therapies are markedly more expensive than conventional replacement therapy, limiting their access for patients in developing countries.
  2. Asmawi AA, Salim N, Abdulmalek E, Abdul Rahman MB
    Pharmaceutics, 2023 Feb 15;15(2).
    PMID: 36839974 DOI: 10.3390/pharmaceutics15020652
    Lung cancer is one of the deadliest pulmonary diseases in the world. Although docetaxel (DTX) has exhibited superior efficacy in lung cancer treatment, it has demonstrated numerous adverse effects and poor bioavailability. The natural product extract, curcumin (CCM), has reportedly reduced toxicity and synergistically improved DTX bioavailability. Nonetheless, the hydrophobic nature of DTX and CCM limits their clinical use. Nanoemulsion pulmonary delivery of DTX and CCM has demonstrated potential as a drug carrier to alleviate these drawbacks. The controlled preparation of inhalable DTX- and CCM-loaded nanoemulsions within the 100 to 200 nm range was explored in this study. A response surface methodology (RSM) based on a central composite design (CCD) was utilized to fabricate the desired size of the nanoemulsion under optimized conditions. Different process parameters were employed to control the size of the nanoemulsions procured through a high-energy emulsification technique. The size of the resultant nanoemulsions decreased with increasing energy input. The actual response according to the targeted sizes for DTX- and CCM-loaded nanoemulsion models exhibited excellent agreement with the predicted value at below 5% residual standard error under optimized conditions. The nanoemulsion of 100 nm particle size demonstrated better membrane permeability than their larger counterparts. Moreover, the formulations documented favorable physicochemical and aerodynamic pulmonary delivery properties and reduced toxicity in human lung fibroblast (MRC-5) cells. Hence, this tunable size of nanoemulsions could be a suitable alternative drug delivery for pulmonary diseases with increased local lung concentration.
  3. Awan MJ, Mohd Rahim MS, Salim N, Nobanee H, Asif AA, Attiq MO
    PeerJ Comput Sci, 2023;9:e1483.
    PMID: 37547408 DOI: 10.7717/peerj-cs.1483
    Anterior cruciate ligament (ACL) tears are a common knee injury that can have serious consequences and require medical intervention. Magnetic resonance imaging (MRI) is the preferred method for ACL tear diagnosis. However, manual segmentation of the ACL in MRI images is prone to human error and can be time-consuming. This study presents a new approach that uses deep learning technique for localizing the ACL tear region in MRI images. The proposed multi-scale guided attention-based context aggregation (MGACA) method applies attention mechanisms at different scales within the DeepLabv3+ architecture to aggregate context information and achieve enhanced localization results. The model was trained and evaluated on a dataset of 917 knee MRI images, resulting in 15265 slices, obtaining state-of-the-art results with accuracy scores of 98.63%, intersection over union (IOU) scores of 95.39%, Dice coefficient scores (DCS) of 97.64%, recall scores of 97.5%, precision scores of 98.21%, and F1 Scores of 97.86% on validation set data. Moreover, our method performed well in terms of loss values, with binary cross entropy combined with Dice loss (BCE_Dice_loss) and Dice_loss values of 0.0564 and 0.0236, respectively, on the validation set. The findings suggest that MGACA provides an accurate and efficient solution for automating the localization of ACL in knee MRI images, surpassing other state-of-the-art models in terms of accuracy and loss values. However, in order to improve robustness of the approach and assess its performance on larger data sets, further research is needed.
  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. 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.
  6. Chandran R, Mohd Tohit ER, Stanslas J, Salim N, Tuan Mahmood TM
    Tissue Eng Part C Methods, 2022 10;28(10):545-556.
    PMID: 35485888 DOI: 10.1089/ten.TEC.2022.0045
    Caffeine is therapeutically effective for treating apnea, cellulite formation, and pain management. It also exhibits neuroprotective and antioxidant activities in different models of Parkinson's disease and Alzheimer's disease. However, caffeine administration in a minimally invasive and sustainable manner through the transdermal route is challenging owing to its hydrophilic nature. Therefore, this study demonstrated a transdermal delivery approach for caffeine by utilizing hydrogel microneedle (MN) as a permeation enhancer. The influence of formulation parameters such as molecular weight (MW) of PMVE/MA (polymethyl vinyl ether/maleic anhydride) copolymer and sodium bicarbonate (NaHCO3) concentration on the swelling kinetics and mechanical integrity of the hydrogel MNs was investigated. In addition, the effect of different MN application methods and needle densities of hydrogel MN on the skin insertion efficiency and penetration depth was also evaluated. The swelling degree at equilibrium percentage (% Seq) recorded for hydrogels fabricated with Gantrez S-97 (MW = 1,500,000 Da) was significantly higher than formulation with Gantrez AN-139 (MW = 1,080,000 Da). Increasing the concentration of NaHCO3 also significantly increased the % Seq. Moreover, a 100% penetration was recorded for both the applicator and combination of applicator and thumb pressure compared with only 11% for thumb pressure alone. The average diameter of micropores created by the applicator method was 62.94 μm, which was significantly lower than the combination of both applicator and thumb pressure MN application (100.53 μm). Based on histological imaging, the penetration depth of hydrogel MN increased as the MN density per array decreased. The hydrogel MN with the optimized formulation and skin insertion parameters was tested for caffeine delivery in an in vitro Franz diffusion cell setup. Approximately 2.9 mg of caffeine was delivered within 24 h, and the drug release profile was best fitted to the Korsmeyer-Peppas model, displaying Super Case II kinetics. In conclusion, a combination of thumb and impact application methods and reduced needle density improved the skin penetration efficiency of hydrogel MNs. The results also show that hydrogel MNs fabricated from 3% w/w NaHCO3 and high MW of copolymer exhibit optimum physical and swelling properties for enhanced transdermal delivery.
  7. Kapitonova M, Gupalo S, Alyautdin R, Ibrahim IAA, Salim N, Ahmad A, et al.
    Avicenna J Phytomed, 2022 2 12;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.

  8. Gan TS, Juares Rizal A, Salim NL, Lau LL, Voo SYM
    Med J Malaysia, 2022 Jan;77(1):6-11.
    PMID: 35086988
    INTRODUCTION: Atopic dermatitis (AD) is a chronic relapsing pruritic inflammatory skin disease that commonly occurs among children as well as adults. AD patients were reported to have high prevalence of ocular manifestations, which may be due to the disease nature or drug complications. This study aimed to determine the prevalence of ocular manifestations in patients with AD.

    MATERIALS AND METHODS: Eighty patients who fulfilled the UK Working Party's Diagnostic Criteria for Atopic Dermatitis were included in the cross-sectional study. A standardized case report form was formulated to collect the demographic data and disease profile of the participants. AD severity was evaluated using the EASI and SCORAD score. All patients underwent a complete ophthalmological evaluation.

    RESULTS: The prevalence of ocular manifestations among the patients with AD was 48.8%. Fifty-four (67.5%) patients had facial dermatitis and 37 (46.2%) showed periorbital signs. The mean AD disease duration was 10.99 ± 11.20 years. Majority of the patients had mild to moderate AD. The most frequent ocular manifestation was allergic conjunctivitis (18.75%) followed by cataract (8.75%) and ocular hypertension (8.75%). Among the patients with ocular manifestations, 27 (69.2%) patients regularly applied topical corticosteroids on the face. The use of systemic corticosteroids was seen in 19 (42.2%) patients. Prolonged AD duration was significantly associated with the development of ocular manifestations.

    CONCLUSIONS: Nearly half of the patients with AD were complicated with ocular disease regardless of the AD severity, facial dermatitis and presence of periorbital signs. Long disease duration is associated with ocular manifestations, especially steroid related complications.

  9. Awan MJ, Mohd Rahim MS, Salim N, Rehman A, Nobanee H
    J Healthc Eng, 2022;2022:2550120.
    PMID: 35444781 DOI: 10.1155/2022/2550120
    In recent times, knee joint pains have become severe enough to make daily tasks difficult. Knee osteoarthritis is a type of arthritis and a leading cause of disability worldwide. The middle of the knee contains a vital portion, the anterior cruciate ligament (ACL). It is necessary to diagnose the ACL ruptured tears early to avoid surgery. The study aimed to perform a comparative analysis of machine learning models to identify the condition of three ACL tears. In contrast to previous studies, this study also considers imbalanced data distributions as machine learning techniques struggle to deal with this problem. The paper applied and analyzed four machine learning classification models, namely, random forest (RF), categorical boosting (Cat Boost), light gradient boosting machines (LGBM), and highly randomized classifier (ETC) on the balanced, structured dataset of ACL. After oversampling a hyperparameter adjustment, the above four models have achieved an average accuracy of 95.72%, 94.98%, 94.98%, and 98.26%. There are 2070 observations and eight features in the collection of three diagnosis ACL classes after oversampling. The area under curve value was approximately 0.998, respectively. Experiments were performed using twelve machine learning algorithms with imbalanced and balanced datasets. However, the accuracy of the imbalanced dataset has remained under 76% for all twelve models. After oversampling, the proposed model may contribute to the investigation of ACL tears on magnetic resonance imaging and other knee ligaments efficiently and automatically without involving radiologists.
  10. Altalib MK, Salim N
    Molecules, 2021 Nov 03;26(21).
    PMID: 34771076 DOI: 10.3390/molecules26216669
    Traditional drug development is a slow and costly process that leads to the production of new drugs. Virtual screening (VS) is a computational procedure that measures the similarity of molecules as one of its primary tasks. Many techniques for capturing the biological similarity between a test compound and a known target ligand have been established in ligand-based virtual screens (LBVSs). However, despite the good performances of the above methods compared to their predecessors, especially when dealing with molecules that have structurally homogenous active elements, they are not satisfied when dealing with molecules that are structurally heterogeneous. The main aim of this study is to improve the performance of similarity searching, especially with molecules that are structurally heterogeneous. The Siamese network will be used due to its capability to deal with complicated data samples in many fields. The Siamese multi-layer perceptron architecture will be enhanced by using two similarity distance layers with one fused layer, then multiple layers will be added after the fusion layer, and then the nodes of the model that contribute less or nothing during inference according to their signal-to-noise ratio values will be pruned. Several benchmark datasets will be used, which are: the MDL Drug Data Report (MDDR-DS1, MDDR-DS2, and MDDR-DS3), the Maximum Unbiased Validation (MUV), and the Directory of Useful Decoys (DUD). The results show the outperformance of the proposed method on standard Tanimoto coefficient (TAN) and other methods. Additionally, it is possible to reduce the number of nodes in the Siamese multilayer perceptron model while still keeping the effectiveness of recall on the same level.
  11. Mohd Nordin UU, Ahmad N, Salim N, Mohd Yusof NS
    RSC Adv, 2021 Aug 23;11(46):29080-29101.
    PMID: 35478537 DOI: 10.1039/d1ra06087b
    Psoriasis is a lingering inflammatory skin disease that attacks the immune system. The abnormal interactions between T cells, immune cells, and inflammatory cytokines causing the epidermal thickening. International guidelines have recommended topical treatments for mild to moderate psoriasis whilst systemic and phototherapy treatments for moderate to severe psoriasis. However, current therapeutic approaches have a wider extent to treat moderate to severe type of psoriasis especially since the emergence of diverse biologic agents. In the meantime, topical delivery of conventional treatments has prompted many unsatisfactory effects to penetrate through the skin (stratum corneum). By understanding the physiology of stratum corneum barrier functions, scientists have developed different types of lipid-based nanoparticles like solid lipid nanoparticles, nanostructured lipid carriers, nanovesicles, and nanoemulsions. These novel drug delivery systems help the poorly solubilised active pharmaceutical ingredient reaches the targeted site seamlessly because of the bioavailability feature of the nanosized molecules. Lipid-based nanoparticles for psoriasis treatments create a paradigm for topical drug delivery due to their lipids' amphiphilic feature to efficiently encapsulate both lipophilic and hydrophilic drugs. This review highlights different types of lipid-based nanoparticles and their recent works of nano formulated psoriasis treatments. The encapsulation of psoriasis drugs through lipid nanocarriers unfold numerous research opportunities in pharmaceutical applications but also draw challenges for the future development of nano drugs.
  12. Dinshaw IJ, Ahmad N, Salim N, Leo BF
    Pharmaceutics, 2021 Jul 06;13(7).
    PMID: 34371716 DOI: 10.3390/pharmaceutics13071024
    Psoriasis is a skin disease that is not lethal and does not spread through bodily contact. However, this seemingly harmless condition can lead to a loss of confidence and social stigmatization due to a persons' flawed appearance. The conventional methods of psoriasis treatment include taking in systemic drugs to inhibit immunoresponses within the body or applying topical drugs onto the surface of the skin to inhibit cell proliferation. Topical methods are favored as they pose lesser side effects compared to the systemic methods. However, the side effects from systemic drugs and low bioavailability of topical drugs are the limitations to the treatment. The use of nanotechnology in this field has enhanced drug loading capacity and reduced dosage size. In this review, biosurfactants were introduced as a 'greener' alternative to their synthetic counterparts. Glycolipid biosurfactants are specifically suited for anti-psoriatic application due to their characteristic skin-enhancing qualities. The selection of a suitable oil phase can also contribute to the anti-psoriatic effect as some oils have skin-healing properties. The review covers the pathogenic pathway of psoriasis, conventional treatments, and prospective ingredients to be used as components in the nanoemulsion formulation. Furthermore, an insight into the state-of-the-art methods used in formulating nanoemulsions and their progression to low-energy methods are also elaborated in detail.
  13. Salma H, Melha YM, Sonia L, Hamza H, Salim N
    J Pharm Sci, 2021 06;110(6):2531-2543.
    PMID: 33548245 DOI: 10.1016/j.xphs.2021.01.032
    The purpose of this study was to simultaneously predict the drug release and skin permeation of Piroxicam (PX) topical films based on Chitosan (CTS), Xanthan gum (XG) and its Carboxymethyl derivatives (CMXs) as matrix systems. These films were prepared by the solvent casting method, using Tween 80 (T80) as a permeation enhancer. All of the prepared films were assessed for their physicochemical parameters, their in vitro drug release and ex vivo skin permeation studies. Moreover, deep learning models and machine learning models were applied to predict the drug release and permeation rates. The results indicated that all of the films exhibited good consistency and physicochemical properties. Furthermore, it was noticed that when T80 was used in the optimal formulation (F8) based on CTS-CMX3, a satisfactory drug release pattern was found where 99.97% of PX was released and an amount of 1.18 mg/cm2 was permeated after 48 h. Moreover, Generative Adversarial Network (GAN) efficiently enhanced the performance of deep learning models and DNN was chosen as the best predictive approach with MSE values equal to 0.00098 and 0.00182 for the drug release and permeation kinetics, respectively. DNN precisely predicted PX dissolution profiles with f2 values equal to 99.99 for all the formulations.
  14. 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.
  15. Ab Aziz NA, Salim N, Zarei M, Saari N, Yusoff FM
    Prep Biochem Biotechnol, 2021;51(1):44-53.
    PMID: 32701046 DOI: 10.1080/10826068.2020.1789991
    The study was conducted to determine anti-tyrosinase and antioxidant activities of the extracted collagen hydrolysate (CH) derived from Malaysian jellyfish, Rhopilema hispidum. Collagen was extracted using 1:1 (w:v) 0.1 M NaOH solution at temperature 25 °C for 48 hr followed by treatment of 1:2 (w:v) distilled water for another 24 hr and freeze-dried. The extracted collagen was hydrolyzed using papain at optimum temperature, pH and enzyme/substrate ratio [E/S] of 60 °C, 7.0 and 1:50, respectively. CH was found to exhibit tyrosinase inhibitory activity, DPPH radical scavenging and metal ion-chelating assays up to 64, 28, and 83%, respectively, after 8 hr of hydrolysis process. The molecular weight of CH was found <10 kDa consisting of mainly Gly (19.219%), Glu (10.428%), and Arg (8.848%). The UV-visible spectrum analysis showed a major and minor peak at 218 and 276 nm, accordingly. The FTIR spectroscopy confirmed the amide groups in CH. The SEM images demonstrated spongy and porous structure of CH. In the cytotoxicity study, CH has no cytotoxicity against mouse embryonic 3T3 fibroblast cell line with IC50 value >500 µg/ml. Results revealed that the CH generated from this study has a potential to be developed as active ingredient in cosmeceutical application.
  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. Bahari AN, Saari N, Salim N, Ashari SE
    Molecules, 2020 Jun 08;25(11).
    PMID: 32521731 DOI: 10.3390/molecules25112663
    Actinopyga lecanora (A. lecanora) is classified among the edible species of sea cucumber, known to be rich in protein. Its hydrolysates were reported to contain relatively high antioxidant activity. Antioxidants are one of the essential properties in cosmeceutical products especially to alleviate skin aging. In the present study, pH, reaction temperature, reaction time and enzyme/substrate ratio (E/S) have been identified as the parameters in the papain enzymatic hydrolysis of A. lecanora. The degree of hydrolysis (DH) with antioxidant activities of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric-reducing antioxidant power (FRAP) assays were used as the responses in the optimization. Analysis of variance (ANOVA), normal plot of residuals and 3D contour plots were evaluated to study the effects and interactions between parameters. The best conditions selected from the optimization were at pH 5.00, 70 °C of reaction temperature, 9 h of hydrolysis time and 1.00% enzyme/substrate (E/S) ratio, with the hydrolysates having 51.90% of DH, 42.70% of DPPH activity and 109.90 Fe2+μg/mL of FRAP activity. The A. lecanora hydrolysates (ALH) showed a high amount of hydrophobic amino acids (286.40 mg/g sample) that might be responsible for antioxidant and antityrosinase activities. Scanning electron microscopy (SEM) image of ALH shows smooth structures with pores. Antityrosinase activity of ALH exhibited inhibition of 31.50% for L-tyrosine substrate and 25.40% for L-DOPA substrate. This condition suggests that the optimized ALH acquired has the potential to be used as a bioactive ingredient for cosmeceutical applications.
  18. Samiun WS, Ashari SE, Salim N, Ahmad S
    Int J Nanomedicine, 2020;15:1585-1594.
    PMID: 32210553 DOI: 10.2147/IJN.S198914
    Background: Aripiprazole, which is a quinolinone derivative, has been widely used to treat schizophrenia, major depressive disorder, and bipolar disorder.

    Purpose: A Central Composite Rotatable Design (CCRD) of Response Surface Methodology (RSM) was used purposely to optimize process parameters conditions for formulating nanoemulsion containing aripiprazole using high emulsification methods.

    Methods: This design is used to investigate the influences of four independent variables (overhead stirring time (A), shear rate (B), shear time (C), and the cycle of high-pressure homogenizer (D)) on the response variable namely, a droplet size (Y) of nanoemulsion containing aripiprazole.

    Results: The optimum conditions suggested by the predicted model were: 120 min of overhead stirring time, 15 min of high shear homogenizer time, 4400 rpm of high shear homogenizer rate and 11 cycles of high-pressure homogenizer, giving a desirable droplet size of nanoemulsion containing aripiprazole of 64.52 nm for experimental value and 62.59 nm for predicted value. The analysis of variance (ANOVA) showed the quadratic polynomial fitted the experimental values with F-value (9.53), a low p-value (0.0003) and a non-significant lack of-fit. It proved that the models were adequate to predict the relevance response. The optimized formulation with a viscosity value of 3.72 mPa.s and pH value of 7.4 showed good osmolality value (297 mOsm/kg) and remained stable for three months in three different temperatures (4°C, 25°C, and 45°C).

    Conclusion: This proven that response surface methodology is an efficient tool to produce desirable droplet size of nanoemulsion containing aripiprazole for parenteral delivery application.

  19. 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.
  20. Asilah Za'don NH, Amirul Farhana MK, Farhanim I, Sharifah Izwan TO, Appukutty M, Salim N, et al.
    Med J Malaysia, 2019 12;74(6):461-467.
    PMID: 31929469
    INTRODUCTION: High-intensity interval training (HIIT) has been found to improve cardiometabolic health outcome as compared to moderate-intensity continuous exercise. However, there is still limited data on the benefits of HIIT on the expression of regulatory proteins that are linked to skeletal muscle metabolism and insulin sensitivity in obese adults. This study investigated the effects of HIIT intervention on expressions of peroxisome proliferatoractivated receptor-γ coactivator 1-∝ (PGC-1∝) and adiponectin receptor-1 (AdipoR1), insulin sensitivity (HOMAIR index), and body composition in overweight/obese individuals.

    METHODS: Fifty overweight/obese individuals aged 22-29 years were assigned to either no-exercise control (n=25) or HIIT (n=25) group. The HIIT group underwent a 12-week intervention, three days/week, with intensity of 65-80% of age-based maximum heart rate. Anthropometric measurements, homeostatic model of insulin resistance (HOMA-IR) and gene expression analysis were conducted at baseline and post intervention.

    RESULTS: Significant time-by-group interactions (p<0.001) were found for body weight, BMI, waist circumference and body fat percentage. The HIIT group had lower body weight (2.3%, p<0.001), BMI (2.7%, p<0.001), waist circumference (2.4%, p<0.001) and body fat percentage (4.3%, p<0.001) post intervention. Compared to baseline, expressions of PGC-1∝ and AdipoR1 were increased by approximately three-fold (p=0.019) and two-fold (p=0.003) respectively, along with improved insulin sensitivity (33%, p=0.019) in the HIIT group.

    CONCLUSION: Findings suggest that HIIT possibly improved insulin sensitivity through modulation of PGC-1∝ and AdipoR1. This study also showed that improved metabolic responses can occur despite modest reduction in body weight in overweight/obese individuals undergoing HIIT intervention.

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