Displaying publications 21 - 40 of 62 in total

Abstract:
Sort:
  1. Fulltext Machine Learning-Based Performance Comparison to Diagnose Anterior Cruciate Ligament Tears
    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.
  2. Fulltext Efficient Detection of Knee Anterior Cruciate Ligament from Magnetic Resonance Imaging Using Deep Learning Approach
    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.
  3. Fulltext Response Factorial Design Analysis on Papain-Generated Hydrolysates from Actinopyga lecanora for Determination of Antioxidant and Antityrosinase Activities
    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.
  4. Fulltext CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures
    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.
  5. Investigation and Optimization of Hydrogel Microneedles for Transdermal Delivery of Caffeine
    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.
  6. Shifting Paradigms and Arising Concerns in Severe Hemophilia A Treatment
    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.
  7. Knowledge, attitudes and practice regarding copper intrauterine contraceptive devices among doctors in Malaysia
    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.

  8. Fulltext Aspect extraction on user textual reviews using multi-channel convolutional neural network
    Da'u A, Salim N
    PeerJ Comput Sci, 2019;5:e191.
    PMID: 33816844 DOI: 10.7717/peerj-cs.191
    Aspect extraction is a subtask of sentiment analysis that deals with identifying opinion targets in an opinionated text. Existing approaches to aspect extraction typically rely on using handcrafted features, linear and integrated network architectures. Although these methods can achieve good performances, they are time-consuming and often very complicated. In real-life systems, a simple model with competitive results is generally more effective and preferable over complicated models. In this paper, we present a multichannel convolutional neural network for aspect extraction. The model consists of a deep convolutional neural network with two input channels: a word embedding channel which aims to encode semantic information of the words and a part of speech (POS) tag embedding channel to facilitate the sequential tagging process. To get the vector representation of words, we initialized the word embedding channel and the POS channel using pretrained word2vec and one-hot-vector of POS tags, respectively. Both the word embedding and the POS embedding vectors were fed into the convolutional layer and concatenated to a one-dimensional vector, which is finally pooled and processed using a Softmax function for sequence labeling. We finally conducted a series of experiments using four different datasets. The results indicated better performance compared to the baseline models.
  9. Fulltext Nanoemulsions: A Review on the Conceptualization of Treatment for Psoriasis Using a 'Green' Surfactant with Low-Energy Emulsification Method
    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.
  10. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals
    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.
  11. Fulltext Chemical named entities recognition: a review on approaches and applications
    Eltyeb S, Salim N
    J Cheminform, 2014;6:17.
    PMID: 24834132 DOI: 10.1186/1758-2946-6-17
    The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related properties and activities from the scientific literature to "text mine" these extracted data and determine contextual relationships helps research scientists, particularly those in drug development. One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts. In this review, the authors briefly introduce the fundamental concepts of chemical literature mining, the textual contents of chemical documents, and the methods of naming chemicals in documents. We sketch out dictionary-based, rule-based and machine learning, as well as hybrid chemical named entity recognition approaches with their applied solutions. We end with an outlook on the pros and cons of these approaches and the types of chemical entities extracted.
  12. Ocular co-morbidities in patients with atopic dermatitis - a cross-sectional study from a tertiary referral hospital, Malaysia
    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.

  13. Fulltext A new graph-based molecular descriptor using the canonical representation of the molecule
    Hentabli H, Saeed F, Abdo A, Salim N
    ScientificWorldJournal, 2014;2014:286974.
    PMID: 25140330 DOI: 10.1155/2014/286974
    Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried.
  14. Fulltext Convolutional Neural Network Model Based on 2D Fingerprint for Bioactivity Prediction
    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.
  15. Fulltext Adapting Document Similarity Measures for Ligand-Based Virtual Screening
    Himmat M, Salim N, Al-Dabbagh MM, Saeed F, Ahmed A
    Molecules, 2016 Apr 13;21(4):476.
    PMID: 27089312 DOI: 10.3390/molecules21040476
    Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in virtual screening. In this work, we propose a similarity measure for ligand-based virtual screening, which has been derived from a text processing similarity measure. It has been adopted to be suitable for virtual screening; we called this proposed measure the Adapted Similarity Measure of Text Processing (ASMTP). For evaluating and testing the proposed ASMTP we conducted several experiments on two different benchmark datasets: the Maximum Unbiased Validation (MUV) and the MDL Drug Data Report (MDDR). The experiments have been conducted by choosing 10 reference structures from each class randomly as queries and evaluate them in the recall of cut-offs at 1% and 5%. The overall obtained results are compared with some similarity methods including the Tanimoto coefficient, which are considered to be the conventional and standard similarity coefficients for fingerprint-based similarity calculations. The achieved results show that the performance of ligand-based virtual screening is better and outperforms the Tanimoto coefficients and other methods.
  16. Fulltext Leptin induces the expression of tumorigenic genes in the gastric mucosa of male Sprague-Dawley rats
    Isyraqiah F, K Kutty M, Durairajanayagam D, Salim N, Singh H
    Exp Biol Med (Maywood), 2018 Oct;243(14):1118-1124.
    PMID: 30449153 DOI: 10.1177/1535370218813909
  17. Fulltext Modeling and optimization of nanoemulsion containing Sorafenib for cancer treatment by response surface methodology
    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.
  18. Improvement of physicochemical properties of nanocolloidal carrier loaded with low water solubility drug for parenteral cancer treatment by Response Surface Methodology
    Izadiyan Z, Basri M, Fard Masoumi HR, Abedi Karjiban R, Salim N, Kalantari K
    Mater Sci Eng C Mater Biol Appl, 2019 Jan 01;94:841-849.
    PMID: 30423770 DOI: 10.1016/j.msec.2018.10.015
    Nanoemulsions have been used as a drug carrier system, particularly for poorly water-soluble drugs. Sorafenib is a poorly soluble drug and also there is no parenteral treatment. The aim of this study is the development of nanoemulsions for intravenous administration of Sorafenib. The formulations were prepared by high energy emulsification method and optimized by using Response Surface Methodology (RSM). Here, the effect of independent composition variables of lecithin (1.16-2.84%, w/w), Medium-Chain Triglycerides (2.32-5.68%, w/w) and polysorbate 80 (0.58-1.42%, w/w) amounts on the properties of Sorafenib-loaded nanoemulsion was investigated. The three responses variables were particle size, zeta potential, and polydispersity index. Optimization of the conditions according to the three dependent variables was performed for the preparation of the Sorafenib-loaded nanoemulsions with the minimum value of particle size, suitable rage of zeta potential, and polydispersity index. A formulation containing 0.05% of Sorafenib kept its properties in a satisfactory range over the evaluated period. The composition with 3% Medium-Chain Triglycerides, 2.5% lecithin and 1.22% polysorbate 80 exhibited the smallest particle size and polydispersity index (43.17 nm and 0.22, respectively) with the zeta potential of -38.8 mV was the optimized composition. The fabricated nanoemulsion was characterized by the transmission electron microscope (TEM), viscosity, and stability assessment study. Also, the cytotoxicity result showed that the optimum formulations had no significant effect on a normal cell in a low concentration of the drug but could eliminate the cancer cells. The dose-dependent toxicity made it a suitable candidate for parenteral applications in the treatment of breast cancer. Furthermore, the optimized formulation indicated good storage stability for 3 months at different temperatures (4 ± 2 °C, 25 ± 2 °C and 45 ± 2 °C).
  19. Coccidial infections of goats in Selangor, peninsular Malaysia
    Jalila A, Dorny P, Sani R, Salim NB, Vercruysse J
    Vet Parasitol, 1998 Jan 31;74(2-4):165-72.
    PMID: 9561704
    Coccidial infections were studied in goats in the state of Selangor (peninsular Malaysia) during a 12-month period. The study included 10 smallholder farms on which kids were monitored for faecal oocyst counts from birth until 1-year old. Eimeria oocysts were found in 725 (89%) of 815 faecal samples examined. Nine species of Eimeria were identified. The most prevalent were E. arloingi, found in 71% of the samples, E. ninakohlyakimovae (67%), E. christenseni (63%) and E. alijevi (61%). The other species found were, E. hirci, E. jolchijevi, E. caprovina, E. caprina and E. pallida, present in 34, 22, 12, 9 and 4% of the samples, respectively. Oocyst counts were significantly higher in animals of less than 4-months old (P < 0.05). High oocyst counts were mainly caused by non-pathogenic species. Poor hygienic conditions were found to be associated with a higher intensity of coccidial infections. Mortality rates in kids could not be related to the intensity of coccidial infections.
  20. Fulltext Gastroprotective effect of Berberis vulgaris on ethanol-induced gastric mucosal injury: Histopathological evaluations
    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.

Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links