Displaying publications 1 - 20 of 27 in total

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  1. Abdul Rahman N, Abd Halim MR, Mahawi N, Hasnudin H, Al-Obaidi JR, Abdullah N
    Biomed Res Int, 2017;2017:2038062.
    PMID: 28503566 DOI: 10.1155/2017/2038062
    Corn was inoculated with Lactobacillus plantarum and Propionibacterium freudenreichii subsp. shermanii either independently or as a mixture at ensiling, in order to determine the effect of bacterial additives on corn silage quality. Grain corn was harvested at 32-37% of dry matter and ensiled in a 4 L laboratory silo. Forage was treated as follows: bacterial types: B0 (without bacteria-control), B1 (L. plantarum), B2 (P. freudenreichii subsp. shermanii), and B3 (combination of L. plantarum and P. freudenreichii subsp. shermanii). Each 2 kg of chopped forage was treated with 10 mL of bacterial culture and allowed to ferment for 27 days. The first experiment determined the most suitable wavelength for detection of bacteria (490 nm and 419 nm for B1 and B2, resp.) and the preferable inoculation size (1 × 105 cfu/g). The second experiment analysed the effect of B1 and B2 applied singly or as a mixture on the fermentation characteristics and quality of corn silage. L. plantarum alone increased crude protein (CP) and reduced pH rapidly. In a mixture with P. freudenreichii, the final pH was the lowest compared to other treatments. As a mixture, inclusion of bacteria resulted in silage with lower digestibility than control. Corn silage treated with L. plantarum or P. freudenreichii either alone or mixed together produced desirable silage properties; however, this was not significantly better than untreated silage.
  2. Ahmad-Kamil EI, Ramli R, Jaaman SA, Bali J, Al-Obaidi JR
    ScientificWorldJournal, 2013;2013:892746.
    PMID: 24163635 DOI: 10.1155/2013/892746
    Seagrass is a valuable marine ecosystem engineer. However, seagrass population is declining worldwide. The lack of seagrass research in Malaysia raises questions about the status of seagrasses in the country. The seagrasses in Lawas, which is part of the coral-mangrove-seagrass complex, have never been studied in detail. In this study, we examine whether monthly changes of seagrass population in Lawas occurred. Data on estimates of seagrass percentage cover and water physicochemical parameters (pH, turbidity, salinity, temperature, and dissolved oxygen) were measured at 84 sampling stations established within the study area from June 2009 to May 2010. Meteorological data such as total rainfall, air temperature, and Southern Oscillation Index were also investigated. Our results showed that (i) the monthly changes of seagrass percentage cover are significant, (ii) the changes correlated significantly with turbidity measurements, and (iii) weather changes affected the seagrass populations. Our study indicates seagrass percentage increased during the El-Nino period. These results suggest that natural disturbances such as weather changes affect seagrass populations. Evaluation of land usage and measurements of other water physicochemical parameters (such as heavy metal, pesticides, and nutrients) should be considered to assess the health of seagrass ecosystem at the study area.
  3. Ahmed H, Ajat M, Mahmood RI, Mansor R, Razak ISA, Al-Obaidi JR, et al.
    Biology (Basel), 2021 Sep 13;10(9).
    PMID: 34571787 DOI: 10.3390/biology10090909
    One of the most prevalent death causes among women worldwide is breast cancer. This study aimed to characterise and differentiate the proteomics profiles of breast cancer cell lines treated with Doxorubicin (DOX) and Doxorubicin-CaCO3-nanoparticles (DOX-Ar-CC-NPs). This study determines the therapeutic potential of doxorubicin-loaded aragonite CaCO3 nanoparticles using a Liquid Chromatography/Mass Spectrometry analysis. In total, 334 proteins were expressed in DOX-Ar-CC-NPs treated cells, while DOX treatment expressed only 54 proteins. Out of the 334 proteins expressed in DOX-CC-NPs treated cells, only 36 proteins showed changes in abundance, while in DOX treated cells, only 7 out of 54 proteins were differentially expressed. Most of the 30 identified proteins that are differentially expressed in DOX-CC-NPs treated cells are key enzymes that have an important role in the metabolism of carbohydrates as well as energy, including: pyruvate kinase, ATP synthase, enolase, glyceraldehyde-3-phosphate dehydrogenase, mitochondrial ADP/ATP carrier, and trypsin. Other identified proteins are structural proteins which included; Keratin, α- and β-tubulin, actin, and actinin. Additionally, one of the heat shock proteins was identified, which is Hsp90; other proteins include Annexins and Human epididymis protein 4. While the proteins identified in DOX-treated cells were tubulin alpha-1B chain and a beta chain, actin cytoplasmic 1, annexin A2, IF rod domain-containing protein, and 78 kDa glucose-regulated protein. Bioinformatics analysis revealed the predicted canonical pathways linking the signalling of the actin cytoskeleton, ILK, VEGF, BAG2, integrin and paxillin, as well as glycolysis. This research indicates that proteomic analysis is an effective technique for proteins expression associated with chemotherapy drugs on cancer tumours; this method provides the opportunity to identify treatment targets for MCF-7 cancer cells, and a liquid chromatography-mass spectrometry (LC-MS/MS) system allowed the detection of a larger number of proteins than 2-DE gel analysis, as well as proteins with maximum pIs and high molecular weight.
  4. Ahmed SA, Al-Shanon AF, Al-Saffar AZ, Tawang A, Al-Obaidi JR
    J Genet Eng Biotechnol, 2023 Jul 02;21(1):75.
    PMID: 37393563 DOI: 10.1186/s43141-023-00529-2
    INTRODUCTION: Cancer is a major issue in medical science with increasing death cases every year worldwide. Therefore, searching for alternatives and nonorthodox methods of treatments with high efficiency, selectivity and less toxicity is the main goal in fighting cancer. Acetyl-11-keto-β-boswellic acid (AKBA), is a derivative pentacyclic triterpenoid that exhibited various biological activities with potential anti-tumoral agents. In this research, AKBA was utilized to examine the potential cytotoxic activity against MCF-7 cells in vitro and monitor the cellular and morphological changes with a prospective impact on apoptosis induction.

    METHODS: The cytotoxic activity of AKBA was measured by 3(4,5dimethylthiazole- 2-yl)-2,5 diphyneltetrazolium bromide (MTT) assay. A dose-dependent inhibition in MCF-7 cell viability was detected. The clonogenicity of MCF-7 cells was significantly suppressed by AKBA increment in comparison with untreated cells.

    RESULT: Morphologically, exposure of MCF-7 cells to high AKBA concentrations caused changes in cell nuclear morphology which was indicated by increasing in nuclear size and cell permeability intensity. The mitochondrial membrane potential (ΔΨm) was reduced by increasing AKBA concentration with a significant release of cytochrome c. Acridine orange/ethidium bromide dual staining experiment confirmed that MCF-7 cells treated with AKBA (IC50 concentration) displayed a late stage of apoptosis indicated by intense and bright reddish colour.

    CONCLUSION: A significant increase in reactive oxygen species formation was observed. Caspase 8 and caspase 9 activities were estimated and AKBA activated the production of caspase 8 and caspase 9 in a dose-dependent pattern. Finally, the cell phase distribution analysis was conducted, and flow cytometric analysis showed that AKBA at 200 μg mL-1 significantly arrest MCF-7 cells at the G1 phase and triggered apoptosis.

  5. Al-Obaidi JR, Mohd-Yusuf Y, Razali N, Jayapalan JJ, Tey CC, Md-Noh N, et al.
    Int J Mol Sci, 2014;15(3):5175-92.
    PMID: 24663087 DOI: 10.3390/ijms15035175
    Basal stem rot is a common disease that affects oil palm, causing loss of yield and finally killing the trees. The disease, caused by fungus Ganoderma boninense, devastates thousands of hectares of oil palm plantings in Southeast Asia every year. In the present study, root proteins of healthy oil palm seedlings, and those infected with G. boninense, were analyzed by 2-dimensional gel electrophoresis (2-DE). When the 2-DE profiles were analyzed for proteins, which exhibit consistent significant change of abundance upon infection with G. boninense, 21 passed our screening criteria. Subsequent analyses by mass spectrometry and database search identified caffeoyl-CoA O-methyltransferase, caffeic acid O-methyltransferase, enolase, fructokinase, cysteine synthase, malate dehydrogenase, and ATP synthase as among proteins of which abundances were markedly altered.
  6. Al-Obaidi JR
    Electrophoresis, 2016 05;37(10):1257-63.
    PMID: 26891916 DOI: 10.1002/elps.201600031
    Mushrooms are considered an important food for their traditionally famous nutritional and medicinal values, although much information about their potential at the molecular level is unfortunately unknown. Edible mushrooms include fungi that are either collected wild or cultivated. Many important species are difficult to cultivate but attempts have been made with varying degrees of success, with the results showing unsatisfactory economical cultivation methods. Recently, proteomic analysis has been developed as a powerful tool to study the protein content of fungi, particularly basidiomycetes. This mini-review article highlights the contribution of proteomics platforms to the study of edible mushrooms, focusing on the molecular mechanisms involved in developmental stages. This includes extracellular and cytoplasmic effector proteins that have potential or are involved in the synthesis of anticancer, antidiabetic, antioxidant, and antibiotic, in blood pressure control, in the supply of vitamins and minerals, and in other responses to environmental changes. The contribution of different proteomics techniques including classical and more advanced techniques is also highlighted.
  7. Al-Obaidi JR, Saidi NB, Usuldin SR, Hussin SN, Yusoff NM, Idris AS
    Protein J, 2016 Apr;35(2):100-6.
    PMID: 27016942 DOI: 10.1007/s10930-016-9656-z
    Ganoderma species are a group of fungi that have the ability to degrade lignin polymers and cause severe diseases such as stem and root rot and can infect economically important plants and perennial crops such as oil palm, especially in tropical countries such as Malaysia. Unfortunately, very little is known about the complex interplay between oil palm and Ganoderma in the pathogenesis of the diseases. Proteomic technologies are simple yet powerful tools in comparing protein profile and have been widely used to study plant-fungus interaction. A critical step to perform a good proteome research is to establish a method that gives the best quality and a wide coverage of total proteins. Despite the availability of various protein extraction protocols from pathogenic fungi in the literature, no single extraction method was found suitable for all types of pathogenic fungi. To develop an optimized protein extraction protocol for 2-DE gel analysis of Ganoderma spp., three previously reported protein extraction protocols were compared: trichloroacetic acid, sucrose and phenol/ammonium acetate in methanol. The third method was found to give the most reproducible gels and highest protein concentration. Using the later method, a total of 10 protein spots (5 from each species) were successfully identified. Hence, the results from this study propose phenol/ammonium acetate in methanol as the most effective protein extraction method for 2-DE proteomic studies of Ganoderma spp.
  8. Al-Obaidi JR, Jambari NN, Ahmad-Kamil EI
    J Fungi (Basel), 2021 Jun 24;7(7).
    PMID: 34202552 DOI: 10.3390/jof7070503
    Fungi, especially edible mushrooms, are considered as high-quality food with nutritive and functional values. They are of considerable interest and have been used in the synthesis of nutraceutical supplements due to their medicinal properties and economic significance. Specific fungal groups, including predominantly filamentous endophytic fungi from Ascomycete phylum and several Basidiomycetes, produce secondary metabolites (SMs) with bioactive properties that are involved in the antimicrobial and antioxidant activities. These beneficial fungi, while high in protein and important fat contents, are also a great source of several minerals and vitamins, in particular B vitamins that play important roles in carbohydrate and fat metabolism and the maintenance of the nervous system. This review article will summarize and discuss the abilities of fungi to produce antioxidant, anticancer, antiobesity, and antidiabetic molecules while also reviewing the evidence from the last decade on the importance of research in fungi related products with direct and indirect impact on human health.
  9. Al-Obaidi JR, Halabi MF, AlKhalifah NS, Asanar S, Al-Soqeer AA, Attia MF
    Biol Res, 2017 Aug 24;50(1):25.
    PMID: 28838321 DOI: 10.1186/s40659-017-0131-x
    Jojoba is considered a promising oil crop and is cultivated for diverse purposes in many countries. The jojoba seed produces unique high-quality oil with a wide range of applications such as medical and industrial-related products. The plant also has potential value in combatting desertification and land degradation in dry and semi-dry areas. Although the plant is known for its high-temperature and high-salinity tolerance growth ability, issues such as its male-biased ratio, relatively late flowering and seed production time hamper the cultivation of this plant. The development of efficient biotechnological platforms for better cultivation and an improved production cycle is a necessity for farmers cultivating the plant. In the last 20 years, many efforts have been made for in vitro cultivation of jojoba by applying different molecular biology techniques. However, there is a lot of work to be done in order to reach satisfactory results that help to overcome cultivation problems. This review presents a historical overview, the medical and industrial importance of the jojoba plant, agronomy aspects and nutrient requirements for the plant's cultivation, and the role of recent biotechnology and molecular biology findings in jojoba research.
  10. Al-Obaidi JR, Jamaludin AA, Rahman NA, Ahmad-Kamil EI
    Planta, 2024 Mar 29;259(5):103.
    PMID: 38551683 DOI: 10.1007/s00425-024-04378-2
    Heavy metal pollution caused by human activities is a serious threat to the environment and human health. Plants have evolved sophisticated defence systems to deal with heavy metal stress, with proteins and enzymes serving as critical intercepting agents for heavy metal toxicity reduction. Proteomics continues to be effective in identifying markers associated with stress response and metabolic processes. This review explores the complex interactions between heavy metal pollution and plant physiology, with an emphasis on proteomic and biotechnological perspectives. Over the last century, accelerated industrialization, agriculture activities, energy production, and urbanization have established a constant need for natural resources, resulting in environmental degradation. The widespread buildup of heavy metals in ecosystems as a result of human activity is especially concerning. Although some heavy metals are required by organisms in trace amounts, high concentrations pose serious risks to the ecosystem and human health. As immobile organisms, plants are directly exposed to heavy metal contamination, prompting the development of robust defence mechanisms. Proteomics has been used to understand how plants react to heavy metal stress. The development of proteomic techniques offers promising opportunities to improve plant tolerance to toxicity from heavy metals. Additionally, there is substantial scope for phytoremediation, a sustainable method that uses plants to extract, sequester, or eliminate contaminants in the context of changes in protein expression and total protein behaviour. Changes in proteins and enzymatic activities have been highlighted to illuminate the complex effects of heavy metal pollution on plant metabolism, and how proteomic research has revealed the plant's ability to mitigate heavy metal toxicity by intercepting vital nutrients, organic substances, and/or microorganisms.
  11. Albahri AS, Hamid RA, Alwan JK, Al-Qays ZT, Zaidan AA, Zaidan BB, et al.
    J Med Syst, 2020 May 25;44(7):122.
    PMID: 32451808 DOI: 10.1007/s10916-020-01582-x
    Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such as Middle East respiratory syndrome-CoV, severe acute respiratory syndrome (SARS)-CoV, and the new virus named SARS-CoV-2, rarely infect and spread among humans. On January 30, 2020, the International Health Regulations Emergency Committee of the World Health Organisation declared the outbreak of the resulting disease from this new CoV called 'COVID-19', as a 'public health emergency of international concern'. This global pandemic has affected almost the whole planet and caused the death of more than 315,131 patients as of the date of this article. In this context, publishers, journals and researchers are urged to research different domains and stop the spread of this deadly virus. The increasing interest in developing artificial intelligence (AI) applications has addressed several medical problems. However, such applications remain insufficient given the high potential threat posed by this virus to global public health. This systematic review addresses automated AI applications based on data mining and machine learning (ML) algorithms for detecting and diagnosing COVID-19. We aimed to obtain an overview of this critical virus, address the limitations of utilising data mining and ML algorithms, and provide the health sector with the benefits of this technique. We used five databases, namely, IEEE Xplore, Web of Science, PubMed, ScienceDirect and Scopus and performed three sequences of search queries between 2010 and 2020. Accurate exclusion criteria and selection strategy were applied to screen the obtained 1305 articles. Only eight articles were fully evaluated and included in this review, and this number only emphasised the insufficiency of research in this important area. After analysing all included studies, the results were distributed following the year of publication and the commonly used data mining and ML algorithms. The results found in all papers were discussed to find the gaps in all reviewed papers. Characteristics, such as motivations, challenges, limitations, recommendations, case studies, and features and classes used, were analysed in detail. This study reviewed the state-of-the-art techniques for CoV prediction algorithms based on data mining and ML assessment. The reliability and acceptability of extracted information and datasets from implemented technologies in the literature were considered. Findings showed that researchers must proceed with insights they gain, focus on identifying solutions for CoV problems, and introduce new improvements. The growing emphasis on data mining and ML techniques in medical fields can provide the right environment for change and improvement.
  12. Albahri OS, Al-Obaidi JR, Zaidan AA, Albahri AS, Zaidan BB, Salih MM, et al.
    Comput Methods Programs Biomed, 2020 Nov;196:105617.
    PMID: 32593060 DOI: 10.1016/j.cmpb.2020.105617
    CONTEXT: People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19.

    OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.

    METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.

    RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.

    DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.

  13. Albahri OS, Zaidan AA, Albahri AS, Alsattar HA, Mohammed R, Aickelin U, et al.
    J Adv Res, 2022 Mar;37:147-168.
    PMID: 35475277 DOI: 10.1016/j.jare.2021.08.009
    INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues.

    OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods.

    METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the 'recipients list' and 'COVID-19 distribution criteria'. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM.

    RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values.

    CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.

  14. Alsalem MA, Alamoodi AH, Albahri OS, Dawood KA, Mohammed RT, Alnoor A, et al.
    Artif Intell Rev, 2022 Jan 27.
    PMID: 35103030 DOI: 10.1007/s10462-021-10124-x
    The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.
  15. Alsalem MA, Albahri OS, Zaidan AA, Al-Obaidi JR, Alnoor A, Alamoodi AH, et al.
    Appl Intell (Dordr), 2022 Jan 08.
    PMID: 35035091 DOI: 10.1007/s10489-021-02813-5
    Mesenchymal stem cells (MSCs) have shown promising ability to treat critical cases of coronavirus disease 2019 (COVID-19) by regenerating lung cells and reducing immune system overreaction. However, two main challenges need to be addressed first before MSCs can be efficiently transfused to the most critical cases of COVID-19. First is the selection of suitable MSC sources that can meet the standards of stem cell criteria. Second is differentiating COVID-19 patients into different emergency levels automatically and prioritising them in each emergency level. This study presents an efficient real-time MSC transfusion framework based on multicriteria decision-making(MCDM) methods. In the methodology, the testing phase represents the ability to adhere to plastic surfaces, the upregulation and downregulation of specific surface protein markers and finally the ability to differentiate into different kinds of cells. In the development phase, firstly, two scenarios of an augmented dataset based on the medical perspective are generated to produce 80 patients with different emergency levels. Secondly, an automated triage algorithm based on a formal medical guideline is proposed for real-time monitoring of COVID-19 patients with different emergency levels (i.e. mild, moderate, severe and critical) considering the improvement and deterioration procedures from one level to another. Thirdly, a unique decision matrix for each triage level (except mild) is constructed on the basis of the intersection between the evaluation criteria of each emergency level and list of COVID-19 patients. Thereafter, MCDM methods (i.e. analytic hierarchy process [AHP] and vlsekriterijumska optimizcija i kaompromisno resenje [VIKOR]) are integrated to assign subjective weights for the evaluation criteria within each triage level and then prioritise the COVID-19 patients on the basis of individual and group decision-making(GDM) contexts. Results show that: (1) in both scenarios, the proposed algorithm effectively classified the patients into four emergency levels, including mild, moderate, severe and critical, taking into consideration the improvement and deterioration cases. (2) On the basis of experts' perspectives, clear differences in most individual prioritisations for patients with different emergency levels in both scenarios were found. (3) In both scenarios, COVID-19 patients were prioritised identically between the internal and external group VIKOR. During the evaluation, the statistical objective method indicated that the patient prioritisations underwent systematic ranking. Moreover, comparison analysis with previous work proved the efficiency of the proposed framework. Thus, the real-time MSC transfusion for COVID-19 patients can follow the order achieved in the group VIKOR results.
  16. Chin CF, Teoh EY, Chee MJY, Al-Obaidi JR, Rahmad N, Lawson T
    Protein J, 2019 12;38(6):704-715.
    PMID: 31552579 DOI: 10.1007/s10930-019-09868-x
    Mango (Mangifera indica L.) is an economically important fruit. However, the marketability of mango is affected by the perishable nature and short shelf-life of the fruit. Therefore, a better understanding of the mango ripening process is of great importance towards extending its postharvest shelf life. Proteomics is a powerful tool that can be used to elucidate the complex ripening process at the cellular and molecular levels. This study utilized 2-dimensional gel electrophoresis (2D-GE) coupled with MALDI-TOF/TOF to identify differentially abundant proteins during the ripening process of the two varieties of tropical mango, Mangifera indica cv. 'Chokanan' and Mangifera indica cv 'Golden Phoenix'. The comparative analysis between the ripe and unripe stages of mango fruit mesocarp revealed that the differentially abundant proteins identified could be grouped into the three categories namely, ethylene synthesis and aromatic volatiles, cell wall degradation and stress-response proteins. There was an additional category for differential proteins identified from the 'Chokanan' variety namely, energy and carbohydrate metabolism. However, of all the differential proteins identified, only methionine gamma-lyase was found in both 'Chokanan' and 'Golden Phoenix' varieties. Six differential proteins were selected from each variety for validation by analysing their respective transcript expression using reverse transcription-quantitative PCR (RT-qPCR). The results revealed that two genes namely, glutathione S-transferase (GST) and alpha-1,4 glucan phosphorylase (AGP) were found to express in concordant with protein abundant. The findings will provide an insight into the fruit ripening process of different varieties of mango fruits, which is important for postharvest management.
  17. Dakheel KH, Rahim RA, Neela VK, Al-Obaidi JR, Hun TG, Isa MNM, et al.
    BMC Microbiol, 2019 05 28;19(1):114.
    PMID: 31138130 DOI: 10.1186/s12866-019-1484-9
    BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) biofilm producers represent an important etiological agent of many chronic human infections. Antibiotics and host immune responses are largely ineffective against bacteria within biofilms. Alternative actions and novel antimicrobials should be considered. In this context, the use of phages to destroy MRSA biofilms presents an innovative alternative mechanism.

    RESULTS: Twenty-five MRSA biofilm producers were used as substrates to isolate MRSA-specific phages. Despite the difficulties in obtaining an isolate of this phage, two phages (UPMK_1 and UPMK_2) were isolated. Both phages varied in their ability to produce halos around their plaques, host infectivity, one-step growth curves, and electron microscopy features. Furthermore, both phages demonstrated antagonistic infectivity on planktonic cultures. This was validated in an in vitro static biofilm assay (in microtiter-plates), followed by the visualization of the biofilm architecture in situ via confocal laser scanning microscopy before and after phage infection, and further supported by phages genome analysis. The UPMK_1 genome comprised 152,788 bp coding for 155 putative open reading frames (ORFs), and its genome characteristics were between the Myoviridae and Siphoviridae family, though the morphological features confined it more to the Siphoviridae family. The UPMK_2 has 40,955 bp with 62 putative ORFs; morphologically, it presented the features of the Podoviridae though its genome did not show similarity with any of the S. aureus in the Podoviridae family. Both phages possess lytic enzymes that were associated with a high ability to degrade biofilms as shown in the microtiter plate and CLSM analyses.

    CONCLUSIONS: The present work addressed the possibility of using phages as potential biocontrol agents for biofilm-producing MRSA.

  18. Dakheel KH, Abdul Rahim R, Neela VK, Al-Obaidi JR, Hun TG, Yusoff K
    Biomed Res Int, 2016;2016:4708425.
    PMID: 28078291 DOI: 10.1155/2016/4708425
    Twenty-five methicillin-resistant Staphylococcus aureus (MRSA) isolates were characterized by staphylococcal protein A gene typing and the ability to form biofilms. The presence of exopolysaccharides, proteins, and extracellular DNA and RNA in biofilms was assessed by a dispersal assay. In addition, cell adhesion to surfaces and cell cohesion were evaluated using the packed-bead method and mechanical disruption, respectively. The predominant genotype was spa type t127 (22 out of 25 isolates); the majority of isolates were categorized as moderate biofilm producers. Twelve isolates displayed PIA-independent biofilm formation, while the remaining 13 isolates were PIA-dependent. Both groups showed strong dispersal in response to RNase and DNase digestion followed by proteinase K treatment. PIA-dependent biofilms showed variable dispersal after sodium metaperiodate treatment, whereas PIA-independent biofilms showed enhanced biofilm formation. There was no correlation between the extent of biofilm formation or biofilm components and the adhesion or cohesion abilities of the bacteria, but the efficiency of adherence to glass beads increased after biofilm depletion. In conclusion, nucleic acids and proteins formed the main components of the MRSA clone t127 biofilm matrix, and there seems to be an association between adhesion and cohesion in the biofilms tested.
  19. Dakheel KH, Abdul Rahim R, Al-Obaidi JR, Neela VK, Hun TG, Mat Isa MN, et al.
    Biotechnol Lett, 2022 Feb 05.
    PMID: 35122191 DOI: 10.1007/s10529-022-03229-y
    OBJECTIVE: The degradation activity of two bacteriophages UPMK_1 and UPMK_2 against methicillin-resistant Staphylococcus aureus phages were examined using gel zymography.

    METHODS: The analysis was done using BLASTP to detect peptides catalytic domains. Many peptides that are related to several phage proteins were revealed.

    RESULTS: UPMK_1 and UPMK_2 custom sequence database were used for peptide identification. The biofilm-degrading proteins in the bacteriophage UPMK_2 revealed the same lytic activity towards polysaccharide intercellular adhesin-dependent and independent of Methicillin-resistant Staphylococcus aureus (MRSA) biofilm producers in comparison to UPMK_1, which had lytic activity restricted solely to its host.

    CONCLUSION: Both bacteriophage enzymes were involved in MRSA biofilm degradation during phage infection and they have promising enzybiotics properties against MRSA biofilm formation.

  20. Fisol AFBC, Saidi NB, Al-Obaidi JR, Lamasudin DU, Atan S, Razali N, et al.
    Microb Ecol, 2021 Apr 22.
    PMID: 33890145 DOI: 10.1007/s00248-021-01757-0
    Rigidoporus microporus is the fungus accountable for the white root rot disease that is detrimental to the rubber tree, Hevea brasiliensis. The pathogenicity mechanism of R. microporus and the identity of the fungal proteins and metabolites involved during the infection process remain unclear. In this study, the protein and metabolite profiles of two R. microporus isolates, Segamat (SEG) and Ayer Molek (AM), were investigated during an in vitro interaction with H. brasiliensis. The isolates were used to inoculate H. brasiliensis clone RRIM 2025, and mycelia adhering to the roots of the plant were collected for analysis. Transmission electron microscope (TEM) images acquired confirms the hyphae attachment and colonization of the mycelia on the root of the H. brasiliensis clones after 4 days of inoculation. The protein samples were subjected to 2-DE analysis and analyzed using MALDI-ToF MS/MS, while the metabolites were extracted using methanol and analyzed using LC/MS-QTOF. Based on the differential analyses, upregulation of proteins that are essential for fungal evolution such as malate dehydrogenase, fructose 1,6-biphosphate aldolase, and glyceraldehyde-3-phosphate dehydrogenase hints an indirect role in fungal pathogenicity, while metabolomic analysis suggests an increase in acidic compounds which may lead to increased cell wall degrading enzyme activity. Bioinformatics analyses revealed that the carbohydrate and amino acid metabolisms were prominently affected in response to the fungal pathogenicity. In addition to that, other pathways that were significantly affected include "Protein Ubiquitination Pathway," Unfolded Protein Response," "HIFα Signaling," and "Sirtuin Signaling Pathway." The identification of responsive proteins and metabolites from this study promotes a better understanding of mechanisms underlying R. microporus pathogenesis and provides a list of potential biological markers for early recognition of the white root rot disease.
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