MyMedR

Displaying publications 1 - 20 of 62 in total

Abstract:

Sort:

Weighted voting-based consensus clustering for chemical structure databases

Saeed F, Ahmed A, Shamsir MS, Salim N

J Comput Aided Mol Des, 2014 Jun;28(6):675-84.
PMID: 24830925 DOI: 10.1007/s10822-014-9750-2

The cluster-based compound selection is used in the lead identification process of drug discovery and design. Many clustering methods have been used for chemical databases, but there is no clustering method that can obtain the best results under all circumstances. However, little attention has been focused on the use of combination methods for chemical structure clustering, which is known as consensus clustering. Recently, consensus clustering has been used in many areas including bioinformatics, machine learning and information theory. This process can improve the robustness, stability, consistency and novelty of clustering. For chemical databases, different consensus clustering methods have been used including the co-association matrix-based, graph-based, hypergraph-based and voting-based methods. In this paper, a weighted cumulative voting-based aggregation algorithm (W-CVAA) was developed. The MDL Drug Data Report (MDDR) benchmark chemical dataset was used in the experiments and represented by the AlogP and ECPF_4 descriptors. The results from the clustering methods were evaluated by the ability of the clustering to separate biologically active molecules in each cluster from inactive ones using different criteria, and the effectiveness of the consensus clustering was compared to that of Ward's method, which is the current standard clustering method in chemoinformatics. This study indicated that weighted voting-based consensus clustering can overcome the limitations of the existing voting-based methods and improve the effectiveness of combining multiple clusterings of chemical structures.
Fulltext Voting-based consensus clustering for combining multiple clusterings of chemical structures

Saeed F, Salim N, Abdo A

J Cheminform, 2012 Dec 17;4(1):37.
PMID: 23244782 DOI: 10.1186/1758-2946-4-37

BACKGROUND: Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster.
RESULTS: The cumulative voting-based aggregation algorithm (CVAA), cluster-based similarity partitioning algorithm (CSPA) and hyper-graph partitioning algorithm (HGPA) were examined. The F-measure and Quality Partition Index method (QPI) were used to evaluate the clusterings and the results were compared to the Ward's clustering method. The MDL Drug Data Report (MDDR) dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward's method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward's method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria.
CONCLUSIONS: The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA) was the method of choice among consensus clustering methods.
The goat as a model for studies of pneumonic pasteurellosis caused by Pasteurella multocida

Zamri-Saad M, Effendy WM, Maswati MA, Salim N, Sheikh-Omar AR

Br. Vet. J., 1996 Jul;152(4):453-8.
PMID: 8791853

A model of pneumonic pasteurellosis has been established in goats using Pasteurella multocida harvested from pneumonic lungs of goats (types A and D), rabbits (type A) and sheep (type D). The resultant infections were acute, subacute or chronic. The gross and histological lesions of the subacute and chronic infections were typical of pneumonic pasteurellosis. P. multocida type D produced significantly (P < 0.01) more severe lesions when compared with other isolates. There were strong correlations between the clinical signs and the severity of lesions.
Fulltext The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

Reafee W, Salim N, Khan A

PLoS One, 2016;11(5):e0154848.
PMID: 27152663 DOI: 10.1371/journal.pone.0154848

The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy.
Fulltext Size-Controlled Preparation of Docetaxel- and Curcumin-Loaded Nanoemulsions for Potential Pulmonary Delivery

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.
Similarity-based virtual screening with a bayesian inference network

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.
Fulltext Similarity-Based Virtual Screen Using Enhanced Siamese Multi-Layer Perceptron

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.
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.
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.
Quantum probability ranking principle for ligand-based virtual screening

Al-Dabbagh MM, Salim N, Himmat M, Ahmed A, Saeed F

J Comput Aided Mol Des, 2017 Apr;31(4):365-378.
PMID: 28220440 DOI: 10.1007/s10822-016-0003-4

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
Fulltext Quality dimensions features for identifying high-quality user replies in text forum threads using classification methods

Osman A, Salim N, Saeed F

PLoS One, 2019;14(5):e0215516.
PMID: 31091242 DOI: 10.1371/journal.pone.0215516

The Text Forum Threads (TFThs) contain a large amount of Initial-Posts Replies pairs (IPR pairs) which are related to information exchange and discussion amongst the forum users with similar interests. Generally, some user replies in the discussion thread are off-topic and irrelevant. Hence, the content is of different qualities. It is important to identify the quality of the IPR pairs in a discussion thread in order to extract relevant information and helpful replies because a higher frequency of irrelevant replies in the thread could take the discussion in a different direction and the genuine users would lose interest in this discussion thread. In this study, the authors have presented an approach for identifying the high-quality user replies to the Initial-Post and use some quality dimensions features for their extraction. Moreover, crowdsourcing platforms were used for judging the quality of the replies and classified them into high-quality, low-quality or non-quality replies to the Initial-Posts. Then, the high-quality IPR pairs were extracted and identified based on their quality, and they were ranked using three classifiers i.e., Support Vector Machine, Naïve Bayes, and the Decision Trees according to their quality dimensions of relevancy, author activeness, timeliness, ease-of-understanding, politeness, and amount-of-data. In conclusion, the experimental results for the TFThs showed that the proposed approach could improve the extraction of the quality replies and identify the quality features that can be used for the Text Forum Thread Summarization.
Outcome of corticosteroid injection versus physiotherapy in the treatment of mild trigger fingers

Salim N, Abdullah S, Sapuan J, Haflah NH

J Hand Surg Eur Vol, 2012 Jan;37(1):27-34.
PMID: 21816888 DOI: 10.1177/1753193411415343

We compared the effectiveness of physiotherapy and corticosteroid injection treatment in the management of mild trigger fingers. Mild trigger fingers are those with mild crepitus, uneven finger movements and actively correctable triggering. This is a single-centred, prospective, block randomized study with 74 patients; 39 patients for steroid injection and 35 patients for physiotherapy. The study duration was from Jun 2009 until August 2010. Evaluation was done at 6 weeks, 3 months and 6 months post-treatment. At 3 months, the success rate (absence of pain and triggering) for those receiving steroid injection was 97.4% and physiotherapy 68.6%. The group receiving steroid injection also had lower pain score, higher rate of satisfaction, stronger grip strength and early recovery to near normal function (findings were all significant, p
Fulltext Optimization of nanoemulsion containing gemcitabine and evaluation of its cytotoxicity towards human fetal lung fibroblast (MRC5) and human lung carcinoma (A549) cells

Wahgiman NA, Salim N, Abdul Rahman MB, Ashari SE

Int J Nanomedicine, 2019;14:7323-7338.
PMID: 31686809 DOI: 10.2147/IJN.S212635

Background: Gemcitabine (GEM) is a chemotherapeutic agent, which is known to battle cancer but challenging due to its hydrophilic nature. Nanoemulsion is water-in-oil (W/O) nanoemulsion shows potential as a carrier system in delivering gemcitabine to the cancer cell.
Methods: The behaviour of GEM in MCT/surfactants/NaCl systems was studied in the ternary system at different ratios of Tween 80 and Span 80. The system with surfactant ratio 3:7 of Tween 80 and Span 80 was chosen for further study on the preparation of nanoemulsion formulation due to the highest isotropic region. Based on the selected ternary phase diagram, a composition of F1 was chosen and used for optimization by using the D-optimal mixture design. The interaction variables between medium chain triglyceride (MCT), surfactant mixture Tween 80: Span 80 (ratio 3:7), 0.9 % sodium chloride solution and gemcitabine were evaluated towards particle size as a response.
Results: The results showed that NaCl solution and GEM gave more effects on particle size, polydispersity index and zeta potential of 141.57±0.05 nm, 0.168 and -37.10 mV, respectively. The optimized nanoemulsion showed good stability (no phase separation) against centrifugation test and storage at three different temperatures. The in vitro release of gemcitabine at different pH buffer solution was evaluated. The results showed the release of GEM in buffer pH 6.5 (45.19%) was higher than GEM in buffer pH 7.4 (13.62%). The cytotoxicity study showed that the optimized nanoemulsion containing GEM induced cytotoxicity towards A549 cell and at the same time reduced cytotoxicity towards MRC5 when compared to the control (GEM solution).
Fulltext Optimization of Quercetin loaded Palm Oil Ester Based Nanoemulsion Formulation for Pulmonary Delivery

Arbain NH, Salim N, Wui WT, Basri M, Rahman MBA

J Oleo Sci, 2018 Aug 01;67(8):933-940.
PMID: 30012897 DOI: 10.5650/jos.ess17253

In this research, the palm oil ester (POE)- based nanoemulsion formulation containing quercetin for pulmonary delivery was developed. The nanoemulsion formulation was prepared by high energy emulsification method and then further optimized using D-optimal mixture design. The concentration effects of the mixture of POE:ricinoleic acid (RC), ratio 1:1 (1.50-4.50 wt.%), lecithin (1.50-2.50 wt.%), Tween 80 (0.50-1.00 wt.%), glycerol (1.50-3.00 wt.%), and water (88.0-94.9 wt.%) towards the droplet size were investigated. The results showed that the optimum formulation with 1.50 wt.% POE:RC, 1.50 wt.% lecithin, 1.50 wt.% Tween 80, 1.50 wt.% glycerol and 93.90 % water was obtained. The droplet size, polydispersity index (PDI) and zeta potential of the optimized formulation were 110.3 nm, 0.290 and －37.7 mV, respectively. The formulation also exhibited good stability against storage at 4℃ for 90 days. In vitro aerosols delivery evaluation showed that the aerosols output, aerosols rate and median mass aerodynamic diameter of the optimized nanoemulsion were 99.31%, 0.19 g/min and 4.25 µm, respectively. The characterization of physical properties and efficiency for aerosols delivery results suggest that POE- based nanoemulsion containing quercetin has the potential to be used for pulmonary delivery specifically for lung cancer treatment.
Fulltext Optimization of Processing Parameters of Nanoemulsion Containing Aripiprazole Using Response Surface Methodology

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.
Fulltext Optimization and Characterization of Palm Oil-based Nanoemulsion Loaded with Parthenium hysterophorus Crude Extract for Natural Herbicide Formulation

Zainuddin NJ, Ashari SE, Salim N, Asib N, Omar D, Lian GEC

J Oleo Sci, 2019 Aug 01;68(8):747-757.
PMID: 31292338 DOI: 10.5650/jos.ess18209

The present study revealed the optimization of nanoemulsion containing palm oil derivatives and Parthenium hysterophorus L. crude extract (PHCE) as pre-emergence herbicide formulation against Diodia ocimifolia. The nanoemulsion formulation was prepared by high energy emulsification method, and it was optimized by mixture experimental design (MED). From the optimization process, analysis of variance (ANOVA) showed a fit quadratic polynomial model with an optimal formulation composition containing 30.91% of palm kernel oil ester (PKOE), 28.48% of mixed surfactants (Tensiofix and Tween 80, 8:2), 28.32% of water and 12.29% of PHCE. The reading of both experimental and predicted particle size in the verification experiment were acceptable with a residual standard error (RSE) was less than 2%. Under the optimal condition, the smallest particle size obtained was 140.10 nm, and the particle was shown by morphology analysis to be spherical and demonstrated good stability (no phase separation) under centrifugation and different storage conditions (25 ± 5°C and 45°C). Nanoemulsion stored for 60 days exhibits monodisperse emulsion with a slight increase of particle size. The increase in particle size over time might have contributed by Ostwald ripening phenomenon which is shown by a linear graph from Ostwald ripening rate analysis. In the in vitro germination test, P. hysterophorus nanoemulsion (PHNE) was shown to cause total inhibition of D. ocimifolia seed at lower concentration (5 g L-1) as compared to PHCE (10 g L-1). The finding of the research could potentially serve as a platform for the development of palm oil based formulation containing plant crude extract for green weed management.
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.
New fragment weighting scheme for the Bayesian inference network in ligand-based virtual screening

Abdo A, Salim N

J Chem Inf Model, 2011 Jan 24;51(1):25-32.
PMID: 21155550 DOI: 10.1021/ci100232h

Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in the Bayesian network are encoded using a set of conditional probability distributions, which can be estimated by the fragment weighting function, a function of the frequencies of the fragments in the molecule or the reference structure as well as throughout the collection. The weighting function combines one or more fragment weighting schemes. In this paper, we have investigated five different weighting functions and present a new fragment weighting scheme. Later on, these functions were modified to combine the new weighting scheme. Simulated virtual screening experiments with the MDL Drug Data Report (23) and maximum unbiased validation data sets show that the use of new weighting scheme can provide significantly more effective screening when compared with the use of current weighting schemes.
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.
Fulltext Movie Review Summarization Using Supervised Learning and Graph-Based Ranking Algorithm

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.

Filters

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

External Links