Browse publications by year: 2023

  1. Mohd Sahardi NFN, Jaafar F, Tan JK, Mad Nordin MF, Makpol S
    Nutrients, 2023 Oct 25;15(21).
    PMID: 37960173 DOI: 10.3390/nu15214520
    (1) Background: Muscle loss is associated with frailty and a reduction in physical strength and performance, which is caused by increased oxidative stress. Ginger (Zingiber officinale Roscoe) is a potential herb that can be used to reduce the level of oxidative stress. This study aimed to determine the effect of ginger on the expression of metabolites and their metabolic pathways in the myoblast cells to elucidate the mechanism involved and its pharmacological properties in promoting myoblast differentiation. (2) Methods: The myoblast cells were cultured into three stages (young, pre-senescent and senescent). At each stage, the myoblasts were treated with different concentrations of ginger extract. Then, metabolomic analysis was performed using liquid chromatography-tandem mass spectrometry (LCMS/MS). (3) Results: Nine metabolites were decreased in both the pre-senescent and senescent control groups as compared to the young control group. For the young ginger-treated group, 8-shogaol and valine were upregulated, whereas adipic acid and bis (4-ethyl benzylidene) sorbitol were decreased. In the pre-senescent ginger-treated group, the niacinamide was upregulated, while carnitine and creatine were downregulated. Ginger treatment in the senescent group caused a significant upregulation in 8-shogaol, octadecanamide and uracil. (4) Conclusions: Ginger extract has the potential as a pharmacological agent to reduce muscle loss in skeletal muscle by triggering changes in some metabolites and their pathways that could promote muscle regeneration in ageing.
    MeSH terms: Aging; Humans; Muscles; Plant Extracts/pharmacology; Plant Extracts/chemistry; Myoblasts
  2. Yan S, Su Y, Xiao J, Luo X, Ji Y, Ghazali KHB
    Sensors (Basel), 2023 Oct 24;23(21).
    PMID: 37960380 DOI: 10.3390/s23218680
    Indoor location-based services (LBS) have tremendous practical and social value in intelligent life due to the pervasiveness of smartphones. The magnetic field-based localization method has been an interesting research hotspot because of its temporal stability, ubiquitousness, infrastructure-free nature, and good compatibility with smartphones. However, utilizing discrete magnetic signals may result in ambiguous localization features caused by random noise and similar magnetic signals in complex symmetric and large-scale indoor environments. To address this issue, we propose a deep neural network-based fusion indoor localization system that integrates magnetic and pedestrian dead reckoning (PDR). In this system, we first propose a ResNet-GRU-LSTM neural network model to achieve magnetic localization more accurately. Afterward, we put forward a multifeatured-driven step length estimation. A hierarchy GRU (H-GRU) neural network model is proposed, and a multidimensional dataset using acceleration and a gyroscope is constructed to extract more valid characteristics. Finally, more reliable and accurate pedestrian localization can be achieved under the particle filter framework. Experiments were conducted at two trial sites with two pedestrians and four smartphones. Results demonstrate that the proposed system achieves better accuracy and robustness than other traditional localization algorithms. Moreover, the proposed system exhibits good generality and practicality in real-time localization with low cost and low computational complexity.
  3. Motwakel A, Hashim AHA, Alamro H, Alqahtani H, Alotaibi FA, Sayed A
    Sensors (Basel), 2023 Oct 25;23(21).
    PMID: 37960399 DOI: 10.3390/s23218699
    Wireless Sensor Networks (WSNs) contain several small, autonomous sensor nodes (SNs) able to process, transfer, and wirelessly sense data. These networks find applications in various domains like environmental monitoring, industrial automation, healthcare, and surveillance. Node Localization (NL) is a major problem in WSNs, aiming to define the geographical positions of sensors correctly. Accurate localization is essential for distinct WSN applications comprising target tracking, environmental monitoring, and data routing. Therefore, this paper develops a Chaotic Mapping Lion Optimization Algorithm-based Node Localization Approach (CMLOA-NLA) for WSNs. The purpose of the CMLOA-NLA algorithm is to define the localization of unknown nodes based on the anchor nodes (ANs) as a reference point. In addition, the CMLOA is mainly derived from the combination of the tent chaotic mapping concept into the standard LOA, which tends to improve the convergence speed and precision of NL. With extensive simulations and comparison results with recent localization approaches, the effectual performance of the CMLOA-NLA technique is illustrated. The experimental outcomes demonstrate considerable improvement in terms of accuracy as well as efficiency. Furthermore, the CMLOA-NLA technique was demonstrated to be highly robust against localization error and transmission range with a minimum average localization error of 2.09%.
  4. Khan MJ, Singh PP, Pradhan B, Alamri A, Lee CW
    Sensors (Basel), 2023 Oct 28;23(21).
    PMID: 37960482 DOI: 10.3390/s23218783
    Road network extraction is a significant challenge in remote sensing (RS). Automated techniques for interpreting RS imagery offer a cost-effective solution for obtaining road network data quickly, surpassing traditional visual interpretation methods. However, the diverse characteristics of road networks, such as varying lengths, widths, materials, and geometries across different regions, pose a formidable obstacle for road extraction from RS imagery. The issue of road extraction can be defined as a task that involves capturing contextual and complex elements while also preserving boundary information and producing high-resolution road segmentation maps for RS data. The objective of the proposed Archimedes tuning process quantum dilated convolutional neural network for road Extraction (ATP-QDCNNRE) technology is to tackle the aforementioned issues by enhancing the efficacy of image segmentation outcomes that exploit remote sensing imagery, coupled with Archimedes optimization algorithm methods (AOA). The findings of this study demonstrate the enhanced road-extraction capabilities achieved by the ATP-QDCNNRE method when used with remote sensing imagery. The ATP-QDCNNRE method employs DL and a hyperparameter tuning process to generate high-resolution road segmentation maps. The basis of this approach lies in the QDCNN model, which incorporates quantum computing (QC) concepts and dilated convolutions to enhance the network's ability to capture both local and global contextual information. Dilated convolutions also enhance the receptive field while maintaining spatial resolution, allowing fine road features to be extracted. ATP-based hyperparameter modifications improve QDCNNRE road extraction. To evaluate the effectiveness of the ATP-QDCNNRE system, benchmark databases are used to assess its simulation results. The experimental results show that ATP-QDCNNRE performed with an intersection over union (IoU) of 75.28%, mean intersection over union (MIoU) of 95.19%, F1 of 90.85%, precision of 87.54%, and recall of 94.41% in the Massachusetts road dataset. These findings demonstrate the superior efficiency of this technique compared to more recent methods.
  5. Ali S, Tan SC, Lee CK, Yusoff Z, Haque MR, Mylonas A, et al.
    Sensors (Basel), 2023 Nov 02;23(21).
    PMID: 37960622 DOI: 10.3390/s23218922
    Software-Defined Networking (SDN), which is used in Industrial Internet of Things, uses a controller as its "network brain" located at the control plane. This uniquely distinguishes it from the traditional networking paradigms because it provides a global view of the entire network. In SDN, the controller can become a single point of failure, which may cause the whole network service to be compromised. Also, data packet transmission between controllers and switches could be impaired by natural disasters, causing hardware malfunctioning or Distributed Denial of Service (DDoS) attacks. Thus, SDN controllers are vulnerable to both hardware and software failures. To overcome this single point of failure in SDN, this paper proposes an attack-aware logical link assignment (AALLA) mathematical model with the ultimate aim of restoring the SDN network by using logical link assignment from switches to the cluster (backup) controllers. We formulate the AALLA model in integer linear programming (ILP), which restores the disrupted SDN network availability by assigning the logical links to the cluster (backup) controllers. More precisely, given a set of switches that are managed by the controller(s), this model simultaneously determines the optimal cost for controllers, links, and switches.
  6. Singh AK, Mahto SK, Sinha R, Alibakhshikenari M, Al-Gburi AJA, Ahmad A, et al.
    Sensors (Basel), 2023 Nov 06;23(21).
    PMID: 37960695 DOI: 10.3390/s23218996
    In this paper, a low-cost resin-coated commercial-photo-paper substrate is used to design a printed reconfigurable multiband antenna. The two PIN diodes are used mainly to redistribute the surface current that provides reconfigurable properties to the proposed antenna. The antenna size of 40 mm × 40 mm × 0.44 mm with a partial ground, covers wireless and mobile bands ranging from 1.91 GHz to 6.75 GHz. The parametric analysis is performed to achieve optimized design parameters of the antenna. The U-shaped and C-shaped emitters are meant to function at 2.4 GHz and 5.9 GHz, respectively, while the primary emitter is designed to operate at 3.5 GHz. The proposed antenna achieved peak gain and radiation efficiency of 3.4 dBi and 90%, respectively. Simulated and measured results of the reflection coefficient, radiation pattern, gain, and efficiency show that the antenna design is in favorable agreement. Since the proposed antenna achieved wideband (1.91-6.75 GHz) using PIN diode configuration, using this technique the need for numerous electronic components to provide multiband frequency is avoided.
  7. Imon RR, Aktar S, Morshed N, Nur SM, Mahtarin R, Rahman FA, et al.
    Medicine (Baltimore), 2023 Nov 10;102(45):e35347.
    PMID: 37960765 DOI: 10.1097/MD.0000000000035347
    Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan, has long been found to be dysregulated in human lung adenocarcinomas (LUADs). Nevertheless, the function, mutational profile, epigenetic regulation, co-expression profile, and clinicopathological significance of the GPC3 gene in LUAD progression are not well understood. In this study, we analyzed cancer microarray datasets from publicly available databases using bioinformatics tools to elucidate the above parameters. We observed significant downregulation of GPC3 in LUAD tissues compared to their normal counterparts, and this downregulation was associated with shorter overall survival (OS) and relapse-free survival (RFS). Nevertheless, no significant differences in the methylation pattern of GPC3 were observed between LUAD and normal tissues, although lower promoter methylation was observed in male patients. GPC3 expression was also found to correlate significantly with infiltration of B cells, CD8+, CD4+, macrophages, neutrophils, and dendritic cells in LUAD. In addition, a total of 11 missense mutations were identified in LUAD patients, and ~1.4% to 2.2% of LUAD patients had copy number amplifications in GPC3. Seventeen genes, mainly involved in dopamine receptor-mediated signaling pathways, were frequently co-expressed with GPC3. We also found 11 TFs and 7 miRNAs interacting with GPC3 and contributing to disease progression. Finally, we identified 3 potential inhibitors of GPC3 in human LUAD, namely heparitin, gemcitabine and arbutin. In conclusion, GPC3 may play an important role in the development of LUAD and could serve as a promising biomarker in LUAD.
    MeSH terms: Humans; Male; Neoplasm Recurrence, Local/genetics; Prognosis; Epigenesis, Genetic; Glypicans/genetics; Glypicans/metabolism
  8. Peters R, Li B, Swinburn B, Allender S, He Z, Lim SY, et al.
    Bull World Health Organ, 2023 Nov 01;101(11):690-706F.
    PMID: 37961057 DOI: 10.2471/BLT.23.289973
    OBJECTIVE: To identify and analyse ongoing nutrition-related surveillance programmes led and/or funded by national authorities in countries in South-East Asian and Western Pacific Regions.

    METHODS: We systematically searched for publications in PubMed® and Scopus, manually searched the grey literature and consulted with national health and nutrition officials, with no restrictions on publication type or language. We included low- and middle-income countries in the World Health Organization South-East Asia Region, and the Association of Southeast Asian Nations and China. We analysed the included programmes by adapting the United States Centers for Disease Control and Prevention's public health surveillance evaluation framework.

    FINDINGS: We identified 82 surveillance programmes in 18 countries that repeatedly collect, analyse and disseminate data on nutrition and/or related indicators. Seventeen countries implemented a national periodic survey that exclusively collects nutrition-outcome indicators, often alongside internationally linked survey programmes. Coverage of different subpopulations and monitoring frequency vary substantially across countries. We found limited integration of food environment and wider food system indicators in these programmes, and no programmes specifically monitor nutrition-sensitive data across the food system. There is also limited nutrition-related surveillance of people living in urban deprived areas. Most surveillance programmes are digitized, use measures to ensure high data quality and report evidence of flexibility; however, many are inconsistently implemented and rely on external agencies' financial support.

    CONCLUSION: Efforts to improve the time efficiency, scope and stability of national nutrition surveillance, and integration with other sectoral data, should be encouraged and supported to allow systemic monitoring and evaluation of malnutrition interventions in these countries.

    MeSH terms: Asia, Southeastern/epidemiology; China; Humans; Nutritional Status*; Surveys and Questionnaires; Public Health Surveillance*
  9. Hasan S, Chew KS, Balang RV, Wong SSL
    BMC Womens Health, 2023 Nov 13;23(1):596.
    PMID: 37953265 DOI: 10.1186/s12905-023-02734-0
    BACKGROUND: As breast cancer incidence rises among younger women, there is a knowledge gap regarding the emotional, physical, and social effects of mastectomy, specifically in a crisis-affected country such as Syria. This study aimed to explore these effects on young women with breast cancer in Syria, taking into consideration the cultural significance of a woman's breast as part of her feminine identity.

    METHODS: A qualitative design, using semi-structured in-depth interviews with 10 young women with breast cancer who underwent mastectomy, was conducted between June to December 2022.

    RESULTS: Thematic analysis was used to analyze the data, and five main themes were identified: (1) psychological and emotional well-being (altered self-esteem and femininity, impact on sexual life and relationships, psychological distress associated with mastectomy, mirror trauma and the need for psychological care); (2) body image and breast reconstruction (the dilemma over reconstruction decision, body image and clothing and lack of access to prosthetic information/services); (3) social and interpersonal factors (lack of marriage choices and society's view and stigma); (4) coping mechanisms with mastectomy effects (family support; faith in god almighty; comparing their situation to others and use of prosthetics) and (5) physical health and functioning (physical effects on mobility and function).

    CONCLUSION: Mastectomy has significant physical, emotional, and social consequences on young women with breast cancer, particularly in crisis-affected Syria where access to breast reconstruction is limited. It is crucial for healthcare professionals to understand these impacts, to raise awareness, encourage early detection, and promote less aggressive treatments to improve women's quality of life.

    MeSH terms: Body Image/psychology; Cicatrix/surgery; Female; Humans; Mastectomy/psychology; Quality of Life/psychology
  10. Bautista JAL, Lin CY, Lu CT, Lo LW, Lin YJ, Chang SL, et al.
    Front Cardiovasc Med, 2023;10:1265890.
    PMID: 37953760 DOI: 10.3389/fcvm.2023.1265890
    BACKGROUND: Atrial fibrillation (AF) and mitral regurgitation (MR) have a complex interplay. Catheter ablation (CA) of AF may be a potential method to improve the severity of MR in AF patients.

    METHODS: Patients with symptomatic AF and moderate to severe MR who underwent catheter ablation from 2011 to 2021 were retrospectively included in the study. Patients' baseline characteristics and electrophysiological features were examined. These patients were classified as group 1 with improved MR and group 2 with refractory MR after CA.

    RESULTS: Fifty patients (age 60.2 ± 11.6 years, 29 males) were included in the study (32 in group 1 and 18 in group 2). Group 1 patients had a lower CHA2DS2-VASc score (1.7 ± 1.5 vs. 2.7 ± 1.5, P = 0.005) and had a lower incidence of hypertension (28.1% vs. 66.7%, P = 0.007) and diabetes mellitus (3.1% vs. 22.2%, P = 0.031) as compared to group 2 patients. Electroanatomic three-dimensional (3D) mapping showed that group 1 patients demonstrated less scars on the posterior bottom of the left atrium compared to group 2 patients (12.5% vs. 66.7%, P 

  11. Wan Hussin WAS, Mohd Matore MEE
    Front Psychol, 2023;14:1239933.
    PMID: 37954184 DOI: 10.3389/fpsyg.2023.1239933
    INTRODUCTION: Procrastination is a complex psychological and behavioral construct that is strongly influenced by certain personality traits. In mathematics learning, students find it difficult to master the concepts because of less exposure to learning styles. Poor knowledge of mathematical concepts leads to academic procrastination in the subject of Mathematics among students. Therefore, this study aims to identify students' learning styles in Mathematics, identify the stages of students' academic procrastination in Mathematics, and determine whether there is a significant influence of learning styles (visual, auditory, and kinesthetic) on academic procrastination among secondary school students in Mathematics.

    METHODS: A quantitative approach with a survey was applied. A total of 500 Form Two and Form Four students in five national secondary schools in the Kota Bharu district, Kelantan, were selected using simple random sampling. The duration of data gathering started from 4 October 2022 until 31 January 2023. The Learning Styles Questionnaire and the Academic Procrastination Questionnaire were adapted and verified by eight experts in psychology and counseling. Descriptive and multiple regression tests were carried out using IBM SPSS version 26.0.

    RESULTS: The results revealed that the visual learning style was the most dominant learning style among students in the subject of Mathematics, followed by auditory and kinesthetic. The level of students' academic procrastination in Mathematics was low. Besides, multiple regression showed that visual and kinesthetic learning styles were significant contributors or predictors, which amounted to 14.1% of the variation in students' academic procrastination in Mathematics.

    DISCUSSION: The implications of this study highlight the possibility to improve programs in schools by exposing students to suitable learning styles so that they can practice effective learning styles in Mathematics and consequently overcome academic procrastination. Further research can be carried out by identifying other factors that encourage academic procrastination in the subject of Mathematics in order to increase students' motivation and self-efficacy.

  12. Abdelhafez MA, Ahmed KM, Ahmed NM, Ismail M, Mohd Daud MNB, Ping NPT, et al.
    Heliyon, 2023 Nov;9(11):e20958.
    PMID: 37954333 DOI: 10.1016/j.heliyon.2023.e20958
    BACKGROUND: Women of reproductive age frequently suffer from psychiatric disorders. The risk of developing anxiety, bipolar, and depressive disorders is especially significant during the perinatal period.

    OBJECTIVES: This article aims to identify and discuss the different psychiatric conditions that might affect pregnant women and update the mother's carers about the recent and updated bidirectional relationship between psychiatric disease and adverse pregnancy outcomes, As well as the most updates in diagnostic and management strategies.

    METHODS: A thorough analysis of the literature was conducted using database searches in EMBASE, Science Direct, Google Scholar, Scopus, and PubMed to obtain the objectives and aim of the study.

    RESULTS: The presence of maternal mental illness during pregnancy has been linked to preterm delivery, newborn hypoglycemia, poor neurodevelopmental outcomes, and disturbed attachment. Placental anomalies, small-for-gestational-age foetuses, foetal discomfort, and stillbirth are among more undesirable perinatal outcomes.

    CONCLUSIONS: Pregnancy-related psychiatric disorders are frequent. The outcomes for pregnant women, infants, and women's health are all improved by proper diagnosis and treatment of psychiatric problems.

  13. Gnanasagaran CL, Ramachandran K, Jamadon NH, Kumar VH, Muchtar A, Pazhani A, et al.
    Heliyon, 2023 Nov;9(11):e21705.
    PMID: 37954343 DOI: 10.1016/j.heliyon.2023.e21705
    This paper reports the microstructural characteristics and mechanical properties of yttria-stabilized zirconia prepared via fused deposition modelling and slip casting. X-Ray Diffraction peaks indicated that yttria-stabilized zirconia crystallized in tetragonal structure for both slip casted(SC) and fused deposition modelled(FDM) samples. Further, scanning electron microscopy of slip casted sample showcased closely packed structure with fine grains and an average grain size of ∼65 nm whilst fused deposition modelled samples showcased non-homogeneous pores with ∼20 nm grain size. Average relative density of slip casted samples was ∼99.4 % while that of fused deposition modelled sample exhibited ∼96.2 %. The Vickers Hardness of slip casted (∼15.26 ± 0.4 GPa) was ∼10 % higher than the fused deposition modelled samples (∼13.79 ± 0.3 GPa). Likewise, indentation fracture toughness of slip casted (5.78 ± 0.5 MPa m1/2) was 14 % higher than fused deposition modelled samples which could have been due to the change in grain size as well as porosity of the ceramics. Compressive strength of the fused deposition modelled samples was 32 % less than slip casted samples (∼510 ± 10 MPa) due to its non-homogenous pores which led to weakening van der Waals force of attraction.
  14. Abu Hassan MS, Elias NA, Hassan M, Rahmah S, Wan Ismail WI, Harun NA
    Heliyon, 2023 Nov;9(11):e21663.
    PMID: 37954386 DOI: 10.1016/j.heliyon.2023.e21663
    Gold nanoparticles (AuNPs) have emerged as a promising application in aquaculture. Their nano-sized dimensions, comparable to pathogens offer potential solutions for combating antibiotic resistance. In this study, AuNPs were synthesized by using polychaetes, Marphysa moribidii as the bio-reducing agent. Modifications were made to reduce agglomeration in green-synthesized AuNPs through ultrasonication. The antibacterial activities of AuNPs against V. parahaemolyticus were evaluated. The physicochemical characteristics of the green synthesized AuNPs were comprehensively investigated. The successful formation of AuNPs was confirmed by the appearance of a red ruby colour and the presence of surface Plasmon resonance (SPR) absorption peaks at 530 nm as observed from UV-vis spectroscopy. Scanning electron microscopy (SEM) revealed spherical-shaped AuNPs with some agglomerations. Transmission electron microscopy (TEM) showed particle size of AuNPs ranging from 10 nm to 60 nm, meanwhile dynamic light scattering (DLS) analysis indicated an average particle size of 24.36 nm. X-ray diffraction (XRD) analysis confirmed the high crystallinity of AuNPs, and no AuNPs were detected in the polychaetes extracts prior to synthesis. A brief ultrasonication significantly reduced the tendencies for AuNPs to coalesce. The green-synthesized AuNPs demonstrated a remarkable antibacterial efficacy against V. parahaemolyticus. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) tests revealed that a concentration of 0.3 g/ml of AuNPs effectively inhibited V. parahaemolyticus. These findings highlighted the potential of green-synthesized AuNPs as antibacterial agents for the prevention and management of AHPND in aquaculture.
  15. Hassan MS, Islam MA, Yusof MF, Nasir H
    Heliyon, 2023 Nov;9(11):e21130.
    PMID: 37954394 DOI: 10.1016/j.heliyon.2023.e21130
    The emergence of fintech services in the insurance industry has been a transformative force, reshaping how insurance companies operate, how policies are sold, and how customers interact with their insurers. Financial technology developments, also known as "fintech," are changing how financial services are offered, presenting novel possibilities for the insurance industry worldwide. However, in the Malaysian insurance and takaful industry a good number of customers are still dependent on conventional channels like agents and brokers continue to be important sources for purchases and payments related to insurance instead of using Fintech services. The insurance industry's success and growth are highly dependent on adopting technological services offered by companies to make the process efficient and profitable. So, this study aimed to empirically identify the determinants influencing Malaysia's insurance and takaful industry customers to accept the fintech services for insurance-related transactions and activities. The research combined two prominent technology adoption models UTAUT2, and Delone and Mclean IS Success, and proposed a new research framework. The data for the research has been collected from the insurance and takaful industry customers through Google Forms. Finally, 350 responses were received. The PLS-SEM method was utilized to investigate the data by Smart PLS 3.2.9 software. The result of the study revealed that effort expectancy, information quality, service quality, system quality, and perceived risk impact behavioral intention to use fintech services (BI). In addition, the actual use of fintech services is impacted by behavioral intention. Nevertheless, no impact was found in the case of performance expectancy and social influence on BI. The findings of the study are helpful for academicians, researchers, and insurance companies to explore determinants for fintech services acceptance.
  16. Abdallah S, Sharifa M, I Kh Almadhoun MK, Khawar MM, Shaikh U, Balabel KM, et al.
    Cureus, 2023 Oct;15(10):e46860.
    PMID: 37954711 DOI: 10.7759/cureus.46860
    Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.
  17. Raman H, Jamil A, Rasheed A, Abdulrahman Jairoun A, Lua PL, Ibrahim UI, et al.
    Cureus, 2023 Oct;15(10):e46761.
    PMID: 37954738 DOI: 10.7759/cureus.46761
    INTRODUCTION: Declaration of human monkeypox(HMPX) virus as Public Health Emergency of International Concern (PHEIC) by World Health Organisation (WHO) has raised concerns among the public andlack of knowledge is a prominent challenge in curbing this outbreak. Therefore, assessment ofknowledge level on this outbreak among the medical students is also necessary due to the fact that they are the future healthcare practitioners who will be directly involved in the disease management as well as a major source of knowledge dissemination to the public.

    AIM: The main objective of this study is to assess the knowledge level of medical students at Universiti Sultan Zainal Abidin (UniSZA) regarding the emergence of HMPX. Additionally, the study aims to investigate potential associations between socio-demographic characteristics and knowledge levels, while also identifying factors that predict a high level of knowledge in this context..

    METHODS: A descriptive cross-sectional study was conducted among UniSZA undergraduatemedical students from Year 1 to Year 5. A validated questionnaire comprising six socio-demographic variables and 27 knowledge items was shared online. Descriptive statistics, non-parametric tests and multivariate logistic regression were performed using SPSS software.

    RESULTS: A total of 138 medical students out of 300 participated in this study. Overall, the average knowledge score was 73.95% ±4.43, which indicates that the medical students have moderate knowledge level. Nearly half of them had good knowledge level (n= 68; 49.3%), 43 of them had moderate knowledge level (31.2%), and 27 of them had poor knowledge level (19.6%). There was a significant association between knowledge level and two factors: receiving information on HMPX during their education and seniority (P-value < 0.01 and P-value < 0.05, respectively). Besides, received information on HMPX during their education was a significant predicting factor of good knowledge level (P-value = 0.002).

    CONCLUSION: The knowledge level among the medical students was relatively inadequate.

  18. Borhan MK, Vethakkan SR, Sarvanandan T, Paramasivam SS
    JCEM Case Rep, 2023 Nov;1(6):luad134.
    PMID: 37954835 DOI: 10.1210/jcemcr/luad134
    Lactation ketoacidosis is a rare yet severe metabolic emergency that has been reported in breastfeeding mothers. Reduced carbohydrate intake during breastfeeding has been reported as a common trigger for ketoacidosis. We report the case of a 31-year-old mother without diabetes who presented with life-threatening lactation ketoacidosis after following a ketogenic diet while exclusively breastfeeding her newborn baby. She was managed in the intensive care unit with dextrose and insulin infusion to reverse ketoacidosis. With prompt treatment, the patient's ketoacidosis resolved within 24 hours, and she was discharged well 3 days later. We further discuss the underlying increased metabolic demand in lactating women that puts them at risk of ketoacidosis, underlining the importance of early recognition of lactation ketoacidosis and nutritional education for lactating women.
  19. Prananda AT, Dalimunthe A, Harahap U, Simanjuntak Y, Peronika E, Karosekali NE, et al.
    Front Pharmacol, 2023;14:1288618.
    PMID: 37954853 DOI: 10.3389/fphar.2023.1288618
    Phyllanthus emblica Linn, a prominent member of the euphorbiaceae family, exhibits extensive distribution across a multitude of tropical and subtropical nations. Referred to as "Balakka" in Indonesia, this plant assumes various names across regions, such as "kimalaka," "balakka," "metengo," "malaka," and "kemloko" in North Sumatra, Ternate, Sundanese, and Java respectively. Phyllanthus emblica thrives in tropical locales like Indonesia, Malaysia, and Thailand, while also making its presence felt in subtropical regions like India, China, Uzbekistan, and Sri Lanka. The fruits of Balakka are enriched with bioactive constituents recognized for their wide-ranging benefits, including antioxidant, anti-aging, anti-cholesterol, anti-diabetic, immunomodulatory, antipyretic, analgesic, anti-inflammatory, chemoprotective, hepatoprotective, cardioprotective, antimutagenic, and antimicrobial properties. Comprising a spectrum of phenolic compounds (such as tannins, phenolic acids, and flavonoids), alkaloids, phytosterols, terpenoids, organic acids, amino acids, and vitamins, the bioactive components of Malacca fruit offer a diverse array of health-promoting attributes. In light of these insights, this review aims to comprehensively examine the pharmacological activities associated with P. emblica and delve into the intricate composition of its phytochemical constituents.
  20. Collaboration for Research, Implementation and Training in Critical Care in Asia and Africa (CCAA), Rashan A, Beane A, Ghose A, Dondorp AM, Kwizera A, et al.
    Wellcome Open Res, 2023;8:29.
    PMID: 37954925 DOI: 10.12688/wellcomeopenres.18710.3
    BACKGROUND: Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions. Therefore, successful design and implementation of improvement interventions requires understanding of the behavioural, organisational, and external factors that determine care delivery and the likelihood of achieving sustained improvement. We aim to identify care processes that contribute to suboptimal clinical outcomes in ICUs located in LMICs and to establish barriers and enablers for improving the care processes.

    METHODS: Using rapid evaluation methods, we will use four data collection methods: 1) registry embedded indicators to assess quality of care processes and their associated outcomes; 2) process mapping to provide a preliminary framework to understand gaps between current and desired care practices; 3) structured observations of processes of interest identified from the process mapping and; 4) focus group discussions with stakeholders to identify barriers and enablers influencing the gap between current and desired care practices. We will also collect self-assessments of readiness for quality improvement. Data collection and analysis will be led by local stakeholders, performed in parallel and through an iterative process across eight countries: Kenya, India, Malaysia, Nepal, Pakistan, South Africa, Uganda and Vietnam.

    CONCLUSIONS: The results of our study will provide essential information on where and how care processes can be improved to facilitate better quality of care to critically ill patients in LMICs; thus, reduce preventable mortality and morbidity in ICUs. Furthermore, understanding the rapid evaluation methods that will be used for this study will allow other researchers and healthcare professionals to carry out similar research in ICUs and other health services.

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