Browse publications by year: 2023

  1. Fulltext A Review of the Potential Health Benefits of Nigella sativa on Obesity and Its Associated Complications
    Adam SH, Abu IF, Kamal DAM, Febriza A, Kashim MIAM, Mokhtar MH
    Plants (Basel), 2023 Sep 08;12(18).
    PMID: 37765374 DOI: 10.3390/plants12183210
    Obesity has become a worldwide epidemic and its prevalence continues to increase at an alarming rate. It is considered a major risk factor for the development of several comorbidities, including type 2 diabetes, stroke, other cardiovascular diseases and even cancer. Conventional treatments for obesity, such as dietary interventions, exercise and pharmacotherapy, have proven to have limited effectiveness and are often associated with undesirable side effects. Therefore, there is a growing interest in exploring alternative therapeutic approaches. Nigella sativa (NS), a medicinal plant with multiple pharmacological properties, has gained attention due to its potential role in the treatment of obesity and its associated complications. The aim of this review is therefore to assess the effects of NS on obesity and its complications and to provide insights into the underlying mechanisms. From this review, NS appears to play a complementary or supportive role in the treatment of obesity and its complications. However, future studies are needed to verify the efficacy of NS in the treatment of obesity and its complications and to prove its safety so that it can be introduced in patients with obesity.
  2. Fulltext Chitosan/Alginate Polymeric Nanoparticle-Loaded α-Mangostin: Characterization, Cytotoxicity, and In Vivo Evaluation against Breast Cancer Cells
    Muchtaridi M, Suryani AI, Wathoni N, Herdiana Y, Mohammed AFA, Gazzali AM, et al.
    Polymers (Basel), 2023 Sep 05;15(18).
    PMID: 37765512 DOI: 10.3390/polym15183658
    α-mangostin (Amg), a compound isolated from the mangosteen rind (Garcinia mangostana, L.), has demonstrated promising anticancer activity. However, its low solubility and selectivity against cancer cells limit its efficacy. To address this issue, researchers have developed chitosan/alginate polymeric nanoparticles (NANO-AMCAL) to enhance the effectiveness of Amg. In vitro studies have demonstrated that NANO-AMCAL is highly active against breast cancer cells. Therefore, an in vivo study was conducted to evaluate the efficacy of NANO-AMCAL in treating breast cancer in Wistar rats (Rattus norvegicus) and determine the effective dose. The rats were divided into seven treatment groups, including positive control, negative control, pure Amg, and NANO-AMCAL 5 mg, 10 mg, and 20 mg. The rats were injected subcutaneously with a carcinogenic agent, 7,12-dimethylbenz(a)anthracene (DMBA) and were evaluated for weight and tumor volume every three days during treatment. Surgery was performed on day 14, and histopathological studies were carried out on breast and lung cancer tissues. The results showed that NANO-AMCAL significantly enhanced the anticancer activity of Amg in treating breast cancer in Wistar rats. NANO-AMCAL containing 0.33 mg of Amg had a healing effect three times better than 20 mg pure Amg and was comparable to tamoxifen. The effective dose of NANO-AMCAL for anti-breast cancer treatment in Wistar rats was found to be 20 mg, which exhibited a good healing response, and the tumor volume continued to decrease up to 17.43% on the 14th day. Furthermore, histopathological tests showed tissue repair and no metastases. These findings suggest that NANO-AMCAL may be a promising therapeutic option for breast cancer treatment.
  3. Fulltext Facile Preparation of Carbon Nanotubes/Cellulose Nanofibrils/Manganese Dioxide Nanowires Electrode for Improved Solid-Sate Supercapacitor Performances
    Chin SX, Lau KS, Ginting RT, Tan ST, Khiew PS, Chia CH, et al.
    Polymers (Basel), 2023 Sep 14;15(18).
    PMID: 37765612 DOI: 10.3390/polym15183758
    Wearable energy storage devices require high mechanical stability and high-capacitance flexible electrodes. In this study, we design a flexible supercapacitor electrode consisting of 1-dimensional carbon nanotubes (CNT), cellulose nanofibrils (CNF), and manganese dioxide nanowires (MnO2 NWs). The flexible and conductive CNT/CNF-MnO2 NWs suspension was first prepared via ultrasonic dispersion approach, followed by vacuum filtration and hot press to form the composite paper electrode. The morphological studies show entanglement between CNT and CNF, which supports the mechanical properties of the composite. The CNT/CNF-MnO2 NWs electrode exhibits lower resistance when subjected to various bending angles (-120-+120°) compared to the CNT/CNF electrode. In addition, the solid-state supercapacitor also shows a high energy density of 38 μWh cm-2 and capacitance retention of 83.2% after 5000 cycles.
  4. Managing Energy Consumption of Devices with Multiconnectivity by Deep Learning and Software-Defined Networking
    Shams R, Abdrabou A, Al Bataineh M, Noordin KA
    Sensors (Basel), 2023 Sep 06;23(18).
    PMID: 37765757 DOI: 10.3390/s23187699
    Multiconnectivity allows user equipment/devices to connect to multiple radio access technologies simultaneously, including 5G, 4G (LTE), and WiFi. It is a necessity in meeting the increasing demand for mobile network services for the 5G and beyond wireless networks, while ensuring that mobile operators can still reap the benefits of their present investments. Multipath TCP (MPTCP) has been introduced to allow uninterrupted reliable data transmission over multiconnectivity links. However, energy consumption is a significant issue for multihomed wireless devices since most of them are battery-powered. This paper employs software-defined networking (SDN) and deep neural networks (DNNs) to manage the energy consumption of devices with multiconnectivity running MPTCP. The proposed method involves two lightweight algorithms implemented on an SDN controller, using a real hardware testbed of dual-homed wireless nodes connected to WiFi and cellular networks. The first algorithm determines whether a node should connect to a specific network or both networks. The second algorithm improves the selection made by the first by using a DNN trained on different scenarios, such as various network sizes and MPTCP congestion control algorithms. The results of our extensive experimentation show that this approach effectively reduces energy consumption while providing better network throughput performance compared to using single-path TCP or MPTCP Cubic or BALIA for all nodes.
  5. Fulltext Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning
    Ali A, Ali H, Saeed A, Ahmed Khan A, Tin TT, Assam M, et al.
    Sensors (Basel), 2023 Sep 07;23(18).
    PMID: 37765797 DOI: 10.3390/s23187740
    The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.
    MeSH terms: Delivery of Health Care; Humans; Computer Security; Ecosystem; Electronic Health Records
  6. Fulltext Factors influencing community pharmacists' knowledge about women's issues in epilepsy
    Jairoun AA, Al-Himyari SS, Shahwan M, Hassan N, Al-Tamimi S, Jairoun M, et al.
    Front Public Health, 2023;11:1251393.
    PMID: 37766744 DOI: 10.3389/fpubh.2023.1251393
    BACKGROUND: Previous studies have highlighted instances where pharmacists lacked knowledge regarding women's health issues related to epilepsy.

    OBJECTIVES: To assess UAE community pharmacists' knowledge, toward women's issues in epilepsy.

    METHODS: a cross-sectional research method was employed. A team of seven pharmacy students in their final year visited a randomly selected sample of community pharmacies in the UAE and face-to-face interviews were conducted with the pharmacists using a structured questionnaire. The questionnaire includes two parts; Eight questions designed to elicit data about the demographics of the study participants and 12 questions eliciting insights into the participants' knowledge of women's issues in epilepsy.

    RESULTS: A total of 412 community pharmacist were recruited in the study. The overall level of knowledge about women's issues in epilepsy was good and the average knowledge score was 81% with a 95% confidence interval (CI) [79.1, 82.7%]. The results of multivariate analysis showed higher knowledge scores in chain pharmacies (OR 1.37; 95% CI 1.12-1.67), Chief pharmacists (OR 1.44; 95% CI 1.01-2.06), Pharmacists in charge (OR 3.46; 95% CI 2.7-4.45), pharmacists with 1-5 Years of experience (OR 2.87; 95% CI 1.71-4.82), pharmacists with 6-10 Years (OR 2.63; 95% CI 1.58-4.38), pharmacists with >10 years (OR 3.13; 95% CI 2.03-4.83), graduation form regional universities (OR 1.37; 95% CI 1.12-1.67), graduation form international universities (OR 1.73; 95% CI 1.36-2.20) and receiving a training on epilepsy (OR 1.36; 95% CI 1.12-1.67).

    CONCLUSION: While the findings reveal an overall promising level of knowledge among community pharmacists regarding the issues faced by women with epilepsy, pinpointing which clinical and demographic factors have the most significant impact on this knowledge would permit the implementation of tailored educational interventions. Workshops and modules targeting the issues faced by women with epilepsy would further raise the knowledge and competence among community pharmacists in this area, ensuring better pharmaceutical care for this population.

    MeSH terms: Cross-Sectional Studies; Epilepsy*; Female; Humans; Pharmacies*; Pharmacists; Multivariate Analysis
  7. Fulltext Interleukin-35 and Thymoquinone nanoparticle-based intervention for liver protection against paracetamol-induced liver injury in rats
    Abduh MS, Saghir SAM, Al-Gabri NA, Ahmeda AF, Abdelkarim M, Aldaqal SM, et al.
    Saudi J Biol Sci, 2023 Oct;30(10):103806.
    PMID: 37766887 DOI: 10.1016/j.sjbs.2023.103806
    Paracetamol (PAR) is a commonly used antipyretic and analgesic agent, but its excessive usage can induce liver damage and major health consequences. Interleukin-35 (IL-35) is utilized to treat immunological disorders, intestinal illness, arthritis, allergic disease, hepatitis, and cancer. Thymoquinone (THYO) is also effective against a wide range of disorders. Consequently, this study sought out to explore the ameliorative effects of IL-35 and THYO against PAR-induced hepatotoxicity in rats. Sixty male rats were separated into six groups (10 rats/group): I control (0.5 mL NaCl, 0.9%/rat via oral gavage); II (IL-35), and III (TYHO) received intraperitoneal (i.p) injection of IL-35 (200 ng/kg) or THYO (0.5 mg/kg), respectively. Group IV (PAR) received 600 mg/kg of PAR orally; V (PAR + IL-35) and VI (PAR + TYHO); rats received 600 mg/kg of PAR orally and i.p injection of IL-35 (200 ng/kg) or THYO (0.5 mg/kg), respectively. Administration of IL-35 or THYO markedly mitigated the increasing in the levels of liver parameters triggered by PAR and noticeable enhancement of antioxidant and immunological markers were observed. Additionally, IL-35 or THYO decreased TNF-α, NF-κB, IL-10, IL-6 and IFN-γ in contrast to the PAR control group. Moreover, levels of Capase-3, and cytochrome C were significantly reduced by THYO or IL35, while, levels of Bcl-2 were markedly increased. Furthermore, significant downregulation of IL1-β, TNF-α, TGF-β, and Caspas-3 genes, as well as significant upregulation of Bcl-2 and IL-10 expression were detected. In conclusion, IL-35 and THYO insulated liver from PAR toxicity by mitigating oxidative stress, tissue damage, inflammation, and apoptosis.
  8. Fulltext Enhancing diabetic retinopathy classification using deep learning
    Alwakid G, Gouda W, Humayun M, Jhanjhi NZ
    Digit Health, 2023;9:20552076231203676.
    PMID: 37766903 DOI: 10.1177/20552076231203676
    Prolonged hyperglycemia can cause diabetic retinopathy (DR), which is a major contributor to blindness. Numerous incidences of DR may be avoided if it were identified and addressed promptly. Throughout recent years, many deep learning (DL)-based algorithms have been proposed to facilitate psychometric testing. Utilizing DL model that encompassed four scenarios, DR and its stages were identified in this study using retinal scans from the "Asia Pacific Tele-Ophthalmology Society (APTOS) 2019 Blindness Detection" dataset. Adopting a DL model then led to the use of augmentation strategies that produced a comprehensive dataset with consistent hyper parameters across all test cases. As a further step in the classification process, we used a Convolutional Neural Network model. Different enhancement methods have been used to raise visual quality. The proposed approach detected the DR with a highest experimental result of 97.83%, a top-2 accuracy of 99.31%, and a top-3 accuracy of 99.88% across all the 5 severity stages of the APTOS 2019 evaluation employing CLAHE and ESRGAN techniques for image enhancement. In addition, we employed APTOS 2019 to develop a set of evaluation metrics (precision, recall, and F1-score) to use in analyzing the efficacy of the suggested model. The proposed approach was also proven to be more efficient at DR location than both state-of-the-art technology and conventional DL.
  9. Fulltext Bidirectional crosstalk between the peripheral nervous system and lymphoid tissues/organs
    Boahen A, Hu D, Adams MJ, Nicholls PK, Greene WK, Ma B
    Front Immunol, 2023;14:1254054.
    PMID: 37767094 DOI: 10.3389/fimmu.2023.1254054
    The central nervous system (CNS) influences the immune system generally by regulating the systemic concentration of humoral substances (e.g., cortisol and epinephrine), whereas the peripheral nervous system (PNS) communicates specifically with the immune system according to local interactions/connections. An imbalance between the components of the PNS might contribute to pathogenesis and the further development of certain diseases. In this review, we have explored the "thread" (hardwiring) of the connections between the immune system (e.g., primary/secondary/tertiary lymphoid tissues/organs) and PNS (e.g., sensory, sympathetic, parasympathetic, and enteric nervous systems (ENS)) in health and disease in vitro and in vivo. Neuroimmune cell units provide an anatomical and physiological basis for bidirectional crosstalk between the PNS and the immune system in peripheral tissues, including lymphoid tissues and organs. These neuroimmune interactions/modulation studies might greatly contribute to a better understanding of the mechanisms through which the PNS possibly affects cellular and humoral-mediated immune responses or vice versa in health and diseases. Physical, chemical, pharmacological, and other manipulations of these neuroimmune interactions should bring about the development of practical therapeutic applications for certain neurological, neuroimmunological, infectious, inflammatory, and immunological disorders/diseases.
  10. Dataset on the assessment of pervious concrete containing palm oil kernel shell and seashell in heavy metal removal from stormwater
    Khankhaje E, Kim T, Jang H, Kim CS, Kim J, Rafieizonooz M
    Data Brief, 2023 Oct;50:109570.
    PMID: 37767122 DOI: 10.1016/j.dib.2023.109570
    The dataset currently available comprises data on the removal rates of heavy metals (Ba, Se, Cr, Fe, Cd, As, and Co) through the incorporation of seashells and palm oil kernel shells into pervious concrete for stormwater treatment. Stormwater runoff was collected from commercial areas in Taman University, Skudai, Johor, Malaysia. The stormwater samples underwent filtration and were preserved in high-density polyethylene (HDPE) bottles at a temperature of 4 °C for use as incoming water. The outgoing water, referred to as effluent, was obtained from tests performed on pervious concrete samples after a curing period of 28 days. The pervious concrete mixes were created with a water-to-binder ratio (w/b ratio) of 32% and a sand ratio of 10%. Three different levels of palm oil kernel shell and seashell content were used as coarse aggregate replacements: 0%, 25%, and 50%. Two single-size group were considered for both palm oil kernel shell and seashell: (6.3-9.5 mm) and (4.75-6.3 mm). Heavy metal analyses were conducted on the influent and effluent using a PerkinElmer ELAN 6100 Series Inductively Coupled Plasma- Mass Spectrometer (ICP-MS). The available datasets consist of both raw and analyzed data.
  11. Fulltext Children's understanding of financial literacy and parents' choice of financial knowledge learning methods in Malaysia
    Murugiah L, Ismail R, Taib HM, Applanaidu SD, Long MNHBH
    MethodsX, 2023 Dec;11:102383.
    PMID: 37767158 DOI: 10.1016/j.mex.2023.102383
    Financial literacy is an essential lifelong skill that should be taught to children at any age. It holds the key to develop a generation of adults who are knowledgeable about money and the economy. Additionally, OECD (2018) suggests that using digital tools could significantly enhance financial literacy and well-being. Therefore, this paper aims to:(i)assess the financial literacy level of primary school children in the northern region of Malaysia and(ii)explore interactive and engaging methods for teaching financial literacy.The sample size was determined using Krejcie and Morgan's (1970) approach, resulting in 419 primary school students aged 7 to 12 and their parents. An online questionnaire was employed, and multi-regression analysis was conducted. The findings highlighted those primary students displayed a high level of financial literacy, scoring above 80 % on the questionnaire. Furthermore, parents expressed a preference for their children to enroll in personal finance subjects offered by schools, have financial assignments or activities at school, and engage in online financial games. The study emphasized the crucial roles of schools, teachers, and active parental involvements to enhance financial literacy. This study recommends incorporating interactive and attractive teaching methods through in-class and online activities at the school level.
  12. Intravenous immunoglobulin-resistant Kawasaki disease: Risk factors in children in a middle-income country
    Zahari N, Bah MNM, Sulieman MF, Choo HL
    Ann Pediatr Cardiol, 2023;16(2):102-108.
    PMID: 37767168 DOI: 10.4103/apc.apc_159_22
    BACKGROUND: Identifying risk factors in patients with intravenous immunoglobulin (IVIG) resistance Kawasaki disease (KD) is vital in managing and preventing coronary artery aneurysms (CAAs). We aimed to study the risk factors for IVIG resistance KD in Malaysian children.

    METHODS: This retrospective observational study of children with KD was conducted at two tertiary hospitals in Malaysia from January 2014 to December 2019. Multivariable binary logistic regression was used to analyze the risk factors associated with IVIG resistance.

    RESULTS: A total of 174 patients, 118 males (67.8%) with a median age of 1.4-year-old (interquartile range: 0.1-12.1-year-old), were analyzed. Early (<5 days) and late (>10 days) IVIG treatments were observed in 14 (8.1%) and 19 (11.0%), respectively. Thirty-two patients (18.4%) had IVIG resistance. The independent factors associated with IVIG resistance were high white cell count, hypoalbuminemia, and extremities changes with an odd ratio of 4.7, 3.0, and 4.0, respectively. In addition, CAA was significantly higher in IVIG resistance compared to IVIG responder patients (57.5% [19/33] vs. 23.4% [33/141], P < 0.001). The sensitivity was high in Harada (93.8%) but low in Kobayashi and Egami (46.9% and 34.4%, respectively). The specificity was high with Egami (79.6%) but low in Harada and Kobayashi (22.5% and 64.1%, respectively).

    CONCLUSION: Leukocytosis, hypoalbuminemia, and extremities changes were independent risk factors for IVIG resistance. The variation in sensitivity and specificity of the Japanese scoring makes it unsuitable for predicting IVIG resistance in Malaysian children.

  13. Fulltext Tailored spectroscopic characteristics of a new type of CuO nanoparticles-inserted borate glass system: Samarium concentration tuning effect
    Abdullahi I, Hashim S, Ghoshal SK, Sayyed MI
    Heliyon, 2023 Oct;9(10):e20262.
    PMID: 37767474 DOI: 10.1016/j.heliyon.2023.e20262
    The demand for new glass hosts with emergent properties is constantly growing for various miniaturized applications. Thus, some new types of Sm2O3-activated strontium-telluro-alumino-magnesium-borate glasses with copper oxide nanoparticles (CuONps) insertion were made using melt-quenching approach. The obtained glasses were characterized to determine the effects of Sm2O3 concentration changes on their thermal, structural, and luminescence properties. XRD, FTIR, and HRTEM analyses of the samples verified their glassy nature, presence of different functional units and CuONps, respectively. DTA analysis showed excellent thermal stability of these glasses with a stability factor as much as 125 °C. The optical absorption properties of the glasses were highly sensitive to Sm3+ concentrations variation. The Judd-Ofelt intensity parameters of the glasses with and without CuONps followed the trend of Ω6˃Ω4˃Ω2 and Ω4˃Ω6˃Ω2, respectively. These glasses displayed 4 visible luminescence bands at 561, 598, 645, and 705 nm corresponding to 4G5/2 → 6H5/2, 4G5/2 → 6H7/2, 4G5/2 → 6H9/2, and 4G5/2 → 6H11/2 transitions in Sm3+. In addition, branching ratio above 80% and stimulated emission cross-section up to 135.82 × 10-23 cm2 were achieved. The stimulated emission cross-section and optical gain were enhanced due to the inclusion of CuONps in the glasses. These glasses may be useful for solid state laser and optical amplifier development.
  14. Fulltext When procrastination pays off: Role of knowledge sharing ability, autonomous motivation, and task involvement for employee creativity
    Adeel A, Sarminah S, Jie L, Kee DMH, Qasim Daghriri Y, Alghafes RA
    Heliyon, 2023 Oct;9(10):e19398.
    PMID: 37767479 DOI: 10.1016/j.heliyon.2023.e19398
    The prime objective of this research was to investigate procrastination as a prospectively constructive element of the creative process among employees working at different hierarchical levels in a Chinese organization. Building on self-determination theory, this research postulates a connection between procrastination and creativity through the incubation of knowledge absorption, autonomous motivation and task engagement as boundary conditions. Data was collected from 213 individuals from the workforce and their immediate managers belonging to a Chinese furniture company; then analyzed with Mplus for simple regression analysis, mediated moderated analyses, and coefficient estimates of all the study variables. The outcomes of this investigation showed an inverse relationship between procrastination with creativity, while creativity being strongest in the medium levels of procrastination; however, when autonomous motivation and/or task engagement are strong, procrastination depicts an inverted-U-shaped association; however, in scenarios where both autonomous motivation and the task engagement are low, procrastination has a negative linear relationship. With the results of this research, we have shown that moderate procrastination has a causal effect on the generation of creative ideas. This research demonstrated that as long as employees had strong autonomous drive or high task engagement, their supervisors awarded them better ratings when they procrastinated moderately on their assignments. Limitations and future research directions were also discussed.
  15. Fulltext The impact of environmental regulation, Environment, Social and Government Performance, and technological innovation on enterprise resilience under a green recovery
    Wu Y, Tham J
    Heliyon, 2023 Oct;9(10):e20278.
    PMID: 37767495 DOI: 10.1016/j.heliyon.2023.e20278
    In recent years, the world has witnessed an alarming rise in extreme events, posing significant challenges to the survival and growth of enterprises. In response, adopting a green development strategy has emerged as an imperative for businesses to bolster their resilience. It is crucial to recognize that not all enterprises possess the same level of resilience, thereby highlighting the disparities in their ability to withstand adversity. Consequently, scholars have been fervently engaging in discussions and research to identify the most effective paths of green development, enabling enterprises to enhance their resilience and adeptly navigate through crises. This study employs questionnaires to scrutinize the influence of environmental regulation, environment social and government performance, and technological innovation on enterprise resilience by constructing structural equations that encompass both external constraints and internal corporate management. The findings demonstrate that environmental regulations can stimulate technological innovation for the purpose of promoting sustainable development, thereby bolstering enterprise resilience; By incorporating environment social and government principles into their operations, enterprises can instil a culture of environmental consciousness and proactively incentivize innovative solutions, ultimately enhancing their capacity to adapt swiftly and recover from crises; The practice of environmental regulation and the incorporation of environment social and government concepts serve as a catalyst for enterprises to engage in technological innovation, thereby promoting technological advancement and enhancing corporate resilience.
  16. Fulltext Implementation of machine learning in DNA barcoding for determining the plant family taxonomy
    Riza LS, Zain MI, Izzuddin A, Prasetyo Y, Hidayat T, Abu Samah KAF
    Heliyon, 2023 Oct;9(10):e20161.
    PMID: 37767518 DOI: 10.1016/j.heliyon.2023.e20161
    The DNA barcoding approach has been used extensively in taxonomy and phylogenetics. The differences in certain DNA sequences are able to differentiate and help classify organisms into taxa. It has been used in cases of taxonomic disputes where morphology by itself is insufficient. This research aimed to utilize hierarchical clustering, an unsupervised machine learning method, to determine and resolve disputes in plant family taxonomy. We take a case study of Leguminosae that historically some classify into three families (Fabaceae, Caesalpiniaceae, and Mimosaceae) but others classify into one family (Leguminosae). This study is divided into several phases, which are: (i) data collection, (ii) data preprocessing, (iii) finding the best distance method, and (iv) determining disputed family. The data used are collected from several sources, including National Center for Biotechnology Information (NCBI), journals, and websites. The data for validation of the methods were collected from NCBI. This was used to determine the best distance method for differentiating families or genera. The data for the case study in the Leguminosae group was collected from journals and a website. From the experiment that we have conducted, we found that the Pearson method is the best distance method to do clustering ITS sequence of plants, both in accuracy and computational cost. We use the Pearson method to determine the disputed family between Leguminosae. We found that the case study of Leguminosae should be grouped into one family based on our research.
  17. HLA-B*57:01 typing in a Malaysian cohort: implications of abacavir hypersensitivity in people living with HIV
    Kalidasan V, Kunalan I, Rajasuriar R, Subbiah VK, Das KT
    Pharmacogenomics, 2023 Sep;24(14):761-769.
    PMID: 37767641 DOI: 10.2217/pgs-2023-0136
    Background: Abacavir (ABC) in combination with other antiretroviral drugs, is used to treat people living with HIV (PLWH). However, it is linked to a fatal hypersensitivity reaction in susceptible individuals, and is strongly associated with the HLA-B*57:01 allele. Materials & methods: A total of 152 patients, 50 PLWH and 102 HIV-1 negative patients, were assessed for the HLA-B*57:01 allele through a sequence-specific primer PCR. Results: All PLWH tested negative for the HLA-B*57:01 allele, but two HIV-negative patients were found to have HLA-B*57, with one of them expressing the HLA-B*57:01 allele. Conclusion: Given the low prevalence of this risk allele in the population, testing for the presence of HLA-B*57:01 in PLWH may not provide significant benefit for the reported population.
  18. Structure-function Studies of GABA (A) Receptors and Related computer-aided Studies
    Mohamad FH, Mohamad Jamali MA, Che Has AT
    J Mol Neurosci, 2023 Oct;73(9-10):804-817.
    PMID: 37750966 DOI: 10.1007/s12031-023-02158-3
    The γ-aminobutyric acid type A receptor (GABA (A) receptor) is a membrane protein activated by the neurotransmitter GABA. Structurally, this major inhibitory neurotransmitter receptor in the human central nervous system is a pentamer that can be built from a selection of 19 subunits consisting of α(1,2,3,4,5 or 6), β (1,2 or 3), γ (1,2 or 3), ρ (1,2 or 3), and δ, π, θ, and ε. This creates several possible pentameric arrangements, which also influence the pharmacological and physiological properties of the receptor. The complexity and heterogeneity of the receptors are further increased by the addition of short and long splice variants in several subunits and the existence of multiple allosteric binding sites and expansive ligands that can bind to the receptors. Therefore, a comprehensive understanding of the structure and function of the receptors is required to gain novel insights into the consequences of receptor dysfunction and subsequent drug development studies. Notably, advancements in computational-aided studies have facilitated the elucidation of residual interactions and exploring energy binding, which may otherwise be challenging to investigate. In this review, we aim to summarize the current understanding of the structure and function of GABA (A) receptors obtained from advancements in computational-aided applications.
    MeSH terms: Allosteric Site; Binding Sites; gamma-Aminobutyric Acid; Humans
  19. Fulltext Scoping review of modelling studies assessing the impact of disruptions to essential health services during COVID-19
    Veettil SK, Schwerer L, Kategeaw W, Toth D, Samore MH, Hutubessy R, et al.
    BMJ Open, 2023 Sep 26;13(9):e071799.
    PMID: 37751952 DOI: 10.1136/bmjopen-2023-071799
    BACKGROUND: Studies assessing the indirect impact of COVID-19 using mathematical models have increased in recent years. This scoping review aims to identify modelling studies assessing the potential impact of disruptions to essential health services caused by COVID-19 and to summarise the characteristics of disruption and the models used to assess the disruptions.

    METHODS: Eligible studies were included if they used any models to assess the impact of COVID-19 disruptions on any health services. Articles published from January 2020 to December 2022 were identified from PubMed, Embase and CINAHL, using detailed searches with key concepts including COVID-19, modelling and healthcare disruptions. Two reviewers independently extracted the data in four domains. A descriptive analysis of the included studies was performed under the format of a narrative report.

    RESULTS: This scoping review has identified a total of 52 modelling studies that employed several models (n=116) to assess the potential impact of disruptions to essential health services. The majority of the models were simulation models (n=86; 74.1%). Studies covered a wide range of health conditions from infectious diseases to non-communicable diseases. COVID-19 has been reported to disrupt supply of health services, demand for health services and social change affecting factors that influence health. The most common outcomes reported in the studies were clinical outcomes such as mortality and morbidity. Twenty-five studies modelled various mitigation strategies; maintaining critical services by ensuring resources and access to services are found to be a priority for reducing the overall impact.

    CONCLUSION: A number of models were used to assess the potential impact of disruptions to essential health services on various outcomes. There is a need for collaboration among stakeholders to enhance the usefulness of any modelling. Future studies should consider disparity issues for more comprehensive findings that could ultimately facilitate policy decision-making to maximise benefits to all.

    MeSH terms: Delivery of Health Care; Health Services; Humans; Models, Theoretical; Policy Making
  20. Cognitive frailty and its association with depression, anxiety and stress during the COVID-19 pandemic among older adults in the transforming cognitive frailty into later-life self-sufficiency (AGELESS) study
    Aravindhan K, Morgan K, Mat S, Hamid TA, Ibrahim R, Saedon NI, et al.
    Psychogeriatrics, 2023 Nov;23(6):1071-1082.
    PMID: 37752079 DOI: 10.1111/psyg.13031
    BACKGROUND: Cognitive frailty describes the co-occurrence of cognitive impairment and physical frailty and is classified into reversible and irreversible phenotypes. Data on the impact of COVID-19 pandemic imposed lockdowns, locally known as the Movement Control Order (MCO), on the psychological status of cognitively frail older adults remain scarce. Therefore, this study aimed to determine the relationship between depression, anxiety, stress and cognitive frailty among older adults during the MCO.

    METHOD: Participants aged above 60 years from three ageing cohorts in Malaysia were interviewed virtually. The Fatigue, Resistance, Ambulation, Illness and Loss of Weight scale, blind Montreal Cognitive Assessment, 15-item Geriatric Depression Scale, anxiety subscale of Depression, Anxiety and Stress Scale and four-item Perceived Stress Scale measured frailty, mild cognitive impairment (MCI), depression, anxiety and stress, respectively.

    RESULTS: Cognitive frailty data were available for 870 participants, age (mean ± SD) = 73.44 ± 6.32 years and 55.6% were women. Fifty-seven (6.6%) were robust, 24 (2.8%) had MCI, 451 (51.8%) were pre-frail, 164 (18.9%) were pre-frail+MCI, 119 (13.7%) were frail and 55 (6.3%) were frail+MCI. There were significant differences in depression and anxiety scores between the controlled MCO and recovery MCO. Using multinomial logistic regression, pre-frail (mean difference (95% confidence interval, CI) = 1.16 (0.932, 1.337), frail (1.49 (1.235, 1.803) and frail+MCI (1.49 (1.225, 1.822)) groups had significantly higher depression scores, frail (1.19 (1.030, 1.373)) and frail+MCI (1.24 (1.065, 1.439)) had significantly higher anxiety scores and pre-frail (1.50 (1.285, 1.761)), frail (1.74 (1.469, 2.062)) and frail+MCI (1.81 (1.508, 2.165)) had significantly higher stress scores upon adjustments for the potential confounders. The MCO was a potential confounder in the relationship between depression and prefrail+MCI (1.08 (0.898, 1.340)).

    CONCLUSION: Frail individuals with or without MCI had significantly higher depression, anxiety and stress than those who were robust. Increased depression and stress were also observed in the pre-frail group. Interventions to address psychological issues in older adults during the COVID-19 pandemic could target prefrail and frail individuals and need further evaluation.

    MeSH terms: Aged; Anxiety/epidemiology; Cognition; Communicable Disease Control; Depression/epidemiology; Female; Humans; Male; Geriatric Assessment; Frail Elderly/psychology; Pandemics
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