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Total phenolic, antioxidant, antimicrobial activities and toxicity study of Gynotroches axillaris blume (Rhizophoraceae)

Abed SA, Sirat HM, Taher M

EXCLI J, 2013;12:404-12.
PMID: 26600731

The antioxidant activity and the total phenolic content, as well as the influence of petroleum ether, chloroform and methanol extracts from the leaves of Gynotroches axillaris, on microorganisms were studied. The total phenolic contents were evaluated by using Folin-Ciocalteu reagent and the obtained values ranged from 70.0 to 620 mg GAE/g. The efficiency of antioxidation, which was identified through the scavenging of free radical DPPH, exhibited that the highest IC50 was in the methanolic extract (44.7 µg/mL) as compared to the standard ascorbic acid (25.83 µg/mL) and to standard BHT (17.2 µg/mL). In vitro antimicrobial activity of extracts was tested against Gram-negative bacteria, Gram-positive bacteria and fungi. Methanol extract showed activity in the range (225-900 μg/mL) with both types, while petroleum ether and chloroform extracts were only active with Bacillus subtilis. The three extracts strongly inhibited all fungi with activity 225-450 μg/mL. The toxicity test against brine shrimps indicated that all extracts were non-toxic with LC50 value more than 1000 µg/mL. The finding of this study supports the safety of these extracts to be used in medical treatments.
Fulltext Harmony Search Algorithm for Word Sense Disambiguation

Abed SA, Tiun S, Omar N

PLoS One, 2015;10(9):e0136614.
PMID: 26422368 DOI: 10.1371/journal.pone.0136614

Word Sense Disambiguation (WSD) is the task of determining which sense of an ambiguous word (word with multiple meanings) is chosen in a particular use of that word, by considering its context. A sentence is considered ambiguous if it contains ambiguous word(s). Practically, any sentence that has been classified as ambiguous usually has multiple interpretations, but just one of them presents the correct interpretation. We propose an unsupervised method that exploits knowledge based approaches for word sense disambiguation using Harmony Search Algorithm (HSA) based on a Stanford dependencies generator (HSDG). The role of the dependency generator is to parse sentences to obtain their dependency relations. Whereas, the goal of using the HSA is to maximize the overall semantic similarity of the set of parsed words. HSA invokes a combination of semantic similarity and relatedness measurements, i.e., Jiang and Conrath (jcn) and an adapted Lesk algorithm, to perform the HSA fitness function. Our proposed method was experimented on benchmark datasets, which yielded results comparable to the state-of-the-art WSD methods. In order to evaluate the effectiveness of the dependency generator, we perform the same methodology without the parser, but with a window of words. The empirical results demonstrate that the proposed method is able to produce effective solutions for most instances of the datasets used.
Tyrosinase inhibition, anti-acetylcholinesterase, and antimicrobial activities of the phytochemicals from Gynotroches axillaris Blume

Abed SA, Sirat HM, Taher M

Pak J Pharm Sci, 2016 Nov;29(6):2071-2078.
PMID: 28375126

The leaves of Gynotroches axillaris were chemically and biologically studied. Sequential extraction of the leaves using petroleum ether, chloroform, and methanol afforded three extracts. Purification of pet. ether extract yielded, squalene and β-amyrin palmitate as the major compounds, together with palmitic acid and myristic acid as the minor components. The methanol extract yielded two flavonoids, quercitrin and epicatechin. The isolated compounds were characterized by MS, IR and NMR (1D and 2D). Anti-acetyl cholinesterase screening using TLC bio-autography assay showed that palmitic acid and myristic acid were the strongest inhibition with detection limit 1.14 and 1.28 μ/g/ 5 μL respectively. Antibacterial against Gram-positive and negative and antifungal activities exhibited that β-amyrin palmitate was the strongest (450-225 μ/mL) against all the tested microbes. The tyrosinase inhibition assay of extracts and the pure compounds were screened against tyrosinase enzyme. The inhibition percentage (I%) of methanol extract against tyrosinase enzyme was stronger than the other extracts with value 68.4%. Quercitrin (59%) was found to be the highest in the tyrosinase inhibition activity amongst the pure compounds. To the best of our knowledge, this is first report on the phytochemicals, tyrosinase inhibition, anti-acetycholinesterase and antimicrobial activities of the leaves of G. axillaris.
Chemical composition and anticholinesterase inhibitory activity of the essential oil of Pseuduvaria macrophylla (Oliv.) Merr. from Malaysia

Salleh WMNHW, Khamis S, Nafiah MA, Abed SA

Nat Prod Res, 2021 Jun;35(11):1887-1892.
PMID: 31293176 DOI: 10.1080/14786419.2019.1639183

This study was designed to examine the chemical composition and anticholinesterase inhibitory activity of the essential oil of Pseuduvaria macrophylla (Oliv.) Merr. (Annonaceae) from Malaysia. The essential oil was obtained by hydrodistillation and fully analyzed by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). The analysis led to the identification of thirty-four chemical components that represented 87.7 ± 0.5% of the total oil. The essential oil was found to be rich in germacrene D (21.1 ± 0.4%), bicyclogermacrene (10.5 ± 0.5%), δ-cadinene (5.6 ± 0.2%), α-copaene (5.1 ± 0.3%), and α-cadinol (5.0 ± 0.3%). Anticholinesterase activity was evaluated using Ellman method. The essential oil showed weak inhibitory activity against acetylcholinesterase (I%: 32.5%) and butyrylcholinesterase (I%: 35.4%) assays. Our findings demonstrate that the essential oil could be very useful for the characterization, pharmaceutical and therapeutic applications of the essential oil from Pseuduvaria macrophylla.
The phytochemistry and biological diversity of Ferulago genus (Apiaceae): a systematic review

Salleh WMNHW, Abed SA, Taher M, Kassim H, Tawang A

J Pharm Pharmacol, 2021 Mar 01;73(1):1-21.
PMID: 33791809 DOI: 10.1093/jpp/rgaa034

OBJECTIVES: The genus Ferulago belonging to the family Apiaceae is a flora widely distributed in Central Asia and the Mediterranean and used in folk medicine. It is administered as a sedative, tonic, digestive, aphrodisiac, also as a treatment for intestinal worms and haemorrhoids. Herein, we reported a review on phytochemistry and its biological activities reported from 1990 up to early 2020. All the information and reported studies concerning Ferulago plants were summarized from the library and digital databases (e.g. Scopus, Medline, Scielo, ScienceDirect, SciFinder and Google Scholar).
KEY FINDINGS: The phytochemical investigations of Ferulago species revealed the presence of coumarins as the main bioactive compounds, including daucane derivatives, sesquiterpenes aryl esters, phenol derivatives, flavonoids and essential oils. Moreover, the therapeutic potentials of the pure compounds isolated from the genus Ferulago possess promising properties namely anticholinesterase, antimicrobial, anticoagulant, antileishmanial, antioxidant, antibacterial and antiproliferative.
SUMMARY: Today, significant advances in phytochemical and biological activity studies of different Ferulago species have been revealed. The traditional uses and reported biological results could be correlated via the chemical characterization of these plants. All these data will support the biologists in the elucidation of the biological mechanisms of these plants.
Fulltext A Sequential Handwriting Recognition Model Based on a Dynamically Configurable CRNN

Al-Saffar A, Awang S, Al-Saiagh W, Al-Khaleefa AS, Abed SA

Sensors (Basel), 2021 Nov 02;21(21).
PMID: 34770612 DOI: 10.3390/s21217306

Handwriting recognition refers to recognizing a handwritten input that includes character(s) or digit(s) based on an image. Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a need to develop a dynamic handwriting recognition system. Inspired by the neuroevolutionary technique, this paper proposes a Dynamically Configurable Convolutional Recurrent Neural Network (DC-CRNN) for the handwriting recognition sequence modeling task. The proposed DC-CRNN is based on the Salp Swarm Optimization Algorithm (SSA), which generates the optimal structure and hyperparameters for Convolutional Recurrent Neural Networks (CRNNs). In addition, we investigate two types of encoding techniques used to translate the output of optimization to a CRNN recognizer. Finally, we proposed a novel hybridized SSA with Late Acceptance Hill-Climbing (LAHC) to improve the exploitation process. We conducted our experiments on two well-known datasets, IAM and IFN/ENIT, which include both the Arabic and English languages. The experimental results have shown that LAHC significantly improves the SSA search process. Therefore, the proposed DC-CRNN outperforms the handcrafted CRNN methods.
Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia

Tao H, Al-Hilali AA, Ahmed AM, Mussa ZH, Falah MW, Abed SA, et al.

Chemosphere, 2023 Mar;317:137914.
PMID: 36682637 DOI: 10.1016/j.chemosphere.2023.137914

Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.