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Time-based changes in authorship trend in research-intensive universities in Malaysia

Abu Kassim NL, Mohd Bakri SK, Nusrat F, Salim E, Manjurul Karim M, Rahman MT

Account Res, 2024 Dec;31(1):56-71.
PMID: 35758245 DOI: 10.1080/08989621.2022.2094256

Considering the fact that publications serve as an important criterion to evaluate the scientific accomplishments of an individual within respective fields in academia, there has been an increasing trend to publish scientific articles whereby multiple authors are defined as primary, co-, or corresponding authors according to the roles performed. This article analyzes the authorship pattern in 4,561 papers (including 60 single-authored papers) from 1990 till 2020 of 94 academics who hold a position as professors and are affiliated with the Faculty of Medicine at three different research universities in Malaysia. Only 708 papers (15.5% of 4,561 papers) were authored by less than three authors. In 3,080 papers (67.5% of 4,561 papers), those academics appeared as coauthors. Using different years as cutoff periods, it was observed that the appearance as coauthor in the papers had steeply risen around the years: 2006, 2007, 2008 and onwards. The increased number of authors in the multi-author papers and the appearance of the selected academics as coauthors reflect the extent of boosting of collaborative research in that period which corresponds to the adoption of the "publish or perish policy" by the Ministry of Higher Education in Malaysia.
Fulltext Potential anti-amoebic effects of synthetic 1,4-benzothiazine derivatives against Acanthamoeba castellanii

Alishba, Ahmed U, Taha M, Khan NA, Salar U, Khan KM, et al.

Heliyon, 2024 Jan 15;10(1):e23258.
PMID: 38205285 DOI: 10.1016/j.heliyon.2023.e23258

A rare but lethal central nervous system disease known as granulomatous amoebic encephalitis (GAE) and potentially blinding Acanthamoeba keratitis are diseases caused by free-living Acanthamoeba. Currently, no therapeutic agent can completely eradicate or prevent GAE. Synthetic compounds are a likely source of bioactive compounds for developing new drugs. This study synthesized seventeen 1,4-benzothiazine derivatives (I -XVII) by a base-catalyzed one-pot reaction of 2-amino thiophenol with substituted bromo acetophenones. Different spectroscopic techniques, such as EI-MS, 1H-, and 13C NMR (only for the new compounds), were used for the structural characterization and conformation of compounds. These compounds were assessed for the first time against Acanthamoeba castellanii. All compounds showed anti-amoebic potential in vitro against A. castellanii, reducing its ability to encyst and excyst at 100 μM. Compounds IX, X, and XVI showed the most potent activities among all derivatives and significantly reduced the viability to 5.3 × 104 (p
Fulltext Column-based removal of high concentration microplastics in synthetic wastewater using granular activated carbon

Amirah Mohd Napi NN, Ibrahim N, Adli Hanif M, Hasan M, Dahalan FA, Syafiuddin A, et al.

Bioengineered, 2023 Dec;14(1):2276391.
PMID: 37942779 DOI: 10.1080/21655979.2023.2276391

Microplastic (MP) is an emerging contaminant of concern due to its abundance in the environment. Wastewater treatment plant (WWTP) can be considered as one of the main sources of microplastics in freshwater due to its inefficiency in the complete removal of small MPs. In this study, a column-based MP removal which could serve as a tertiary treatment in WWTPs is evaluated using granular activated carbon (GAC) as adsorbent/filter media, eliminating clogging problems commonly caused by powder form activated carbon (PAC). The GAC is characterized via N2 adsorption-desorption isotherm, field emission scanning electron microscopy, and contact angle measurement to determine the influence of its properties on MP removal efficiency. MPs (40-48 μm) removal up to 95.5% was observed with 0.2 g/L MP, which is the lowest concentration tested in this work, but still higher than commonly used MP concentration in other studies. The performance is reduced with further increase in MP concentration (up to 1.0 g/L), but increasing the GAC bed length from 7.5 to 17.5 cm could lead to better removal efficiencies. MP particles are immobilized by the GAC predominantly by filtration process by being entangled with small GAC particles/chips or stuck between the GAC particles. MPs are insignificantly removed by adsorption process through entrapment in GAC porous structure or attachment onto the GAC surface.
The applications of MicroCT in studying age-related tooth morphological change and dental age estimation: A scoping review

Zainuddin MZ, Mohamad NS, Su Keng T, Mohd Yusof MYP

J Forensic Sci, 2023 Nov;68(6):2048-2056.
PMID: 37529884 DOI: 10.1111/1556-4029.15352

Conventional dental age estimation relies on destructive methods such as sectioning and staining, which are unpreferable when the tooth is required for evidential or archeological preservation. MicroCT is a non-destructive, high-resolution imaging technique that allows for accurate morphometrical measurement. Although microCT technology has been applied in a variety of dental studies, studies focusing on dental age-related change and dental age estimation based on microCT imaging remain lacking. Based on the question: "How has microCT technology been applied in studying human age-related tooth morphological change and dental age estimation studies?", the authors conducted a scoping review in accordance with the Arksey and O'Malley (2005) and the PRISMA-ScR guidelines. A literature search using five major scientific databases identified 452 articles, with 11 full-text articles being eligible to be included in the scoping review. Furthermore, 6 out of the 11 studies performed dental age estimation modeling. An overview of the parameters used in the selected articles revealed a variety of tooth characteristics, such as pulp cavity to whole tooth volume ratio, secondary dentin, as well as the diameter of root canal orifice. The findings of this scoping review highlight the extent microCT is used in studying dental age-related changes, as well as the effectiveness of microCT in dental age estimation studies. This review serves as a guide for future forensic odontology age estimation studies.
Fundamental properties of smart hydrogels for tissue engineering applications: A review

Khan MUA, Stojanović GM, Abdullah MFB, Dolatshahi-Pirouz A, Marei HE, Ashammakhi N, et al.

Int J Biol Macromol, 2024 Jan;254(Pt 3):127882.
PMID: 37951446 DOI: 10.1016/j.ijbiomac.2023.127882

Tissue engineering is an advanced and potential biomedical approach to treat patients suffering from lost or failed an organ or tissue to repair and regenerate damaged tissues that increase life expectancy. The biopolymers have been used to fabricate smart hydrogels to repair damaged tissue as they imitate the extracellular matrix (ECM) with intricate structural and functional characteristics. These hydrogels offer desired and controllable qualities, such as tunable mechanical stiffness and strength, inherent adaptability and biocompatibility, swellability, and biodegradability, all crucial for tissue engineering. Smart hydrogels provide a superior cellular environment for tissue engineering, enabling the generation of cutting-edge synthetic tissues due to their special qualities, such as stimuli sensitivity and reactivity. Numerous review articles have presented the exceptional potential of hydrogels for various biomedical applications, including drug delivery, regenerative medicine, and tissue engineering. Still, it is essential to write a comprehensive review article on smart hydrogels that successfully addresses the essential challenging issues in tissue engineering. Hence, the recent development on smart hydrogel for state-of-the-art tissue engineering conferred progress, highlighting significant challenges and future perspectives. This review discusses recent advances in smart hydrogels fabricated from biological macromolecules and their use for advanced tissue engineering. It also provides critical insight, emphasizing future research directions and progress in tissue engineering.
Fulltext Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms

Khan M, Khan A, Khan AU, Shakeel M, Khan K, Alabduljabbar H, et al.

Heliyon, 2024 Jan 15;10(1):e23375.
PMID: 38169887 DOI: 10.1016/j.heliyon.2023.e23375

Fiber-reinforced polymers (FRP) are widely utilized to improve the efficiency and durability of concrete structures, either through external bonding or internal reinforcement. However, the response of FRP-strengthened reinforced concrete (RC) members, both in field applications and experimental settings, often deviates from the estimation based on existing code provisions. This discrepancy can be attributed to the limitations of code provisions in fully capturing the nature of FRP-strengthened RC members. Accordingly, machine learning methods, including gene expression programming (GEP) and multi-expression programming (MEP), were utilized in this study to predict the flexural capacity of the FRP-strengthened RC beam. To develop data-driven estimation models, an extensive collection of experimental data on FRP-strengthened RC beams was compiled from the experimental studies. For the assessment of the accuracy of developed models, various statistical indicators were utilized. The machine learning (ML) based models were compared with empirical and conventional linear regression models to substantiate their superiority, providing evidence of enhanced performance. The GEP model demonstrated outstanding predictive performance with a correlation coefficient (R) of 0.98 for both the training and validation phases, accompanied by minimal mean absolute errors (MAE) of 4.08 and 5.39, respectively. In contrast, the MEP model achieved a slightly lower accuracy, with an R of 0.96 in both the training and validation phases. Moreover, the ML-based models exhibited notably superior performances compared to the empirical models. Hence, the ML-based models presented in this study demonstrated promising prospects for practical implementation in engineering applications. Moreover, the SHapley Additive exPlanation (SHAP) method was used to interpret the feature's importance and influence on the flexural capacity. It was observed that beam width, section effective depth, and the tensile longitudinal bars reinforcement ratio significantly contribute to the prediction of the flexural capacity of the FRP-strengthened reinforced concrete beam.
Fulltext Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology

Yang M, Al Mamun A, Gao J, Rahman MK, Salameh AA, Alam SS

Sci Rep, 2024 Jan 03;14(1):339.
PMID: 38172184 DOI: 10.1038/s41598-023-50436-2

Addressing the growing popularity of mobile health (m-Health) technology in the health industry, the current study examined consumers' intention and behaviour related to the usage of digital applications based on the unified theory of acceptance and use of technology (UTAUT). In particular, this study quantitatively assessed the moderating role of perceived product value and mediating role of intention to use m-Health application among Indonesians. This study adopted a cross-sectional design and collected quantitative data from conveniently selected respondents through an online survey, which involved 2068 Telegram users in Indonesia. All data were subjected to the analysis of partial least square- structural equation modeling (PLS-SEM). The obtained results demonstrated the moderating effect of perceived product value on the relationship between intention to use m-Health application (m-health app) and actual usage of m-Health app and the mediating effects of intention to use m-Health app on the relationships of perceived critical mass, perceived usefulness, perceived convenience, perceived technology accuracy, and perceived privacy protection on actual usage of m-Health app. However, the intention to use m-Health app did not mediate the influence of health consciousness and health motivation on the actual usage of m-Health app. Overall, this study's findings on the significance of intention to use m-Health app and perceived product value based on the UTAUT framework serve as insightful guideline to expand the usage of m-Health app among consumers.
Fixed-bed adsorption studies of endocrine-disrupting compounds from water by using novel calcium-based metal-organic frameworks

Sukatis FF, Looi LJ, Lim HN, Abdul Rahman MB, Mohd Zaki MR, Aris AZ

Environ Pollut, 2024 Jan 15;341:122980.
PMID: 37992953 DOI: 10.1016/j.envpol.2023.122980

The presence of emerging water pollutants such as endocrine-disrupting compounds (EDCs), including 17-ethynylestradiol (EE2), bisphenol A (BPA), and perfluorooctanoic acid (PFOA), in contaminated water sources poses significant environmental and health challenges. This study aims to address this issue by investigating the efficiency of novel calcium-based metal-organic frameworks, known as mixed-linker calcium-based metal-organic frameworks (Ca-MIX), in adsorbing these endocrine-disrupting compounds. This study analyzed the influence of influent concentration, bed height, and flow rate on pollutant removal, with bed height emerging as a crucial factor. From the breakthrough curves, it was determined that the column maximum adsorption capacities followed the order of 17-ethynylestradiol (101.52 μg/g; 40%) > bisphenol A (99.07 μg/g; 39%) > perfluorooctanoic acid (81.28 μg/g; 32%). Three models were used to predict the adsorption process, with the Yan model outperforming the other models. This suggests the potential of mixed-linker calcium-based metal-organic frameworks for removing endocrine-disrupting compounds from water, using the Yan model as an effective predictor. Overall, this study provides valuable insights for the development of effective water treatment methods using mixed-linker calcium-based metal-organic frameworks to remove endocrine-disrupting compounds from contaminated water sources.
Greening the workforce in higher educational institutions: The pursuance of environmental performance

Ali QM, Nisar QA, Abidin RZU, Qammar R, Abbass K

Environ Sci Pollut Res Int, 2023 Dec;30(60):124474-124487.
PMID: 35349063 DOI: 10.1007/s11356-022-19888-3

The research aims to examine the role of green human resource management (GHRM) in the university's environmental performance. Furthermore, this research also focuses on the mediating effect of green commitment and pro-environmental behavior. It also aims to check how green self-efficacy moderates the relationship between green commitment and pro-environmental behavior. The paper opted for a quantitative design using the convenience sampling technique/approach by collecting the data through a structured questionnaire on 208 academic staff currently employed in the university. The data were collected from August until December 2021 on two campuses (Gujranwala, Jhelum) of the University of Punjab in Pakistan. The current study results give empirical insights that show how green human resource management practices lead to environmental performance at a greater level in a university setting. Study results proposed that change in behavior of employees through human resource management practices can ultimately affect the organization's environmental performance. Further results also demonstrate that green self-efficacy moderates the relationship between green commitment and pro-environmental behavior. This study highlights the role of the university staff's level of commitment and self-efficacy, which are beneficial for enhancing the university's environmental performance. The originality of this study fills the gap in how green commitment mediates the relationship of green human resource management and environmental performance further; it fulfills the gap of green self-efficacy that moderates the relationship of pro-environmental behavior and green commitment. The study sheds light on green human resource management practices in the higher education sector. It emphasizes the vital role of academic staff's environmentally conscious behavior in enhancing a university's environmental performance. The further study highlighted the increasing concept of green human resource management as a set of building the ability, enhancing motivation, and providing opportunities to influence workers' pro-environmental behaviors. The conclusion of the current research was capable of validating the positive concerns of green GHRM, behaviors, and commitments for environmental performance.
Preparation and evaluation of a coated smectite clay-based material modified with epichlorohydrin-dimethylamine for the diclofenac removal

Shamsudin MS, Taib MHA, Azha SF, Bonilla-Petriciolet A, Ismail S

Environ Sci Pollut Res Int, 2023 Dec;30(60):124596-124609.
PMID: 35608765 DOI: 10.1007/s11356-022-20815-9

This study reports the analysis of diclofenac removal from aqueous solution using a novel adsorbent coating with amphoteric surface. This adsorbent coating was improved using a new amphoteric ratio to increase its performance for the removal of pharmaceuticals such as diclofenac. The adsorbent coating was formulated using acrylic polymer emulsion, smectite-based clay powder and epichlorohydrin-dimethylamine to obtain a layer form via the implementation of a facile synthesis method. In a previous study, this adsorbent coating was successful to remove cationic and anionic dyes. Therefore, this research aimed to further investigate and test its application in the removal of other emerging water pollutants like pharmaceuticals. SEM, EDX, and FTIR analyses were carried out for the characterization of this novel adsorbent. The effects of adsorbent composition, diclofenac concentration, temperature, and solution pH were studied and modeled. The best conditions to improve the diclofenac adsorption was 303 K and pH 3 where the adsorption capacity was 25.59 mg/g. Adsorption isotherms and kinetics were quantified and modeled, and the corresponding adsorption mechanism was also analyzed. Diclofenac adsorption with this novel material was exothermic and spontaneous. This alternative adsorbent is promising for diclofenac removal from industrial wastewater systems.
Job stressors and turnover intention of IT executives in Malaysia: The mediating role of employee well-being

Langove N, Javaid MU, Ayyasamy RK, Ibikunle AK, Sabir AA

Work, 2024;77(1):295-305.
PMID: 37483056 DOI: 10.3233/WOR-230103

BACKGROUND: Fear of losing psychological resources can lead to stress, impacting psychological health and behavioral outcomes like burnout, absenteeism, service sabotage, and turnover.
OBJECTIVE: The study examined the impact of job stressors (time pressure, role ambiguity, role conflict) on employee well-being and turnover intentions. The study also investigated the mediating role of employee well-being between job stressors and turnover intention based on the conservation of resources (COR) theory.
METHODS: Data from 396 IT executives in Malaysian IT firms were analyzed using the Partial Least Squares - Structural Equation Modeling (PLS-SEM) technique.
RESULTS: Results confirmed a significant negative correlation between time pressure (-0.296), role ambiguity (-0.423), role conflict (-0.104), and employee well-being. Similarly, employee well-being showed a significant negative relationship with turnover intentions (-0.410). The mediation analysis revealed that employee well-being mediates the relationship between time pressure (0.121), role ambiguity (0.173), role conflict (0.043), and turnover intentions.
CONCLUSION: This paper aims to manifest the importance of designing employee well-being policies by firms to retain employees. Findings reflect the role of the managerial approach towards ensuring employee well-being for employee retention, thereby reducing recruitment and re-training costs.
68Ga-prostate specific membrane antigen-11 PET/CT versus multiparametric MRI in the detection of primary prostate cancer: A systematic review and head-to-head comparative meta-analysis

Ren X, Nur Salihin Yusoff M, Hartini Mohd Taib N, Zhang L, Wang K

Eur J Radiol, 2024 Jan;170:111274.
PMID: 38147764 DOI: 10.1016/j.ejrad.2023.111274

PURPOSE: The goal of this study was to evaluate the effectiveness of two diagnostic methods, 68Ga-PSMA-11 PET/CT and mpMRI, in detecting primary prostate cancer without limitations on the Gleason score.
METHODS: We conducted a comprehensive literature review, searching databases such as PubMed, Embase, and Web of Science until June 2023. Our objective was to identify studies that compared the efficacy of 68Ga-PSMA-11 PET/CT and mpMRI in detecting primary prostate cancer. To determine heterogeneity, the I2 statistic was used. Meta-regression analysis and leave-one-out sensitivity analysis were conducted to identify potential sources of heterogeneity.
RESULTS: Initially, 1286 publications were found, but after careful evaluation, only 16 studies involving 1227 patients were analyzed thoroughly. The results showed that the 68Ga-PSMA-11 PET/CT method had a pooled sensitivity and specificity of 0.87 (95 % CI: 0.80-0.92) and 0.80 (95 % CI: 0.69-0.89), respectively, for diagnosing prostatic cancer. Similarly, the values for mpMRI were determined as 0.84 (95 % CI: 0.75-0.92) and 0.74 (95 % CI: 0.61-0.86), respectively. There were no significant differences in diagnostic effectiveness observed when comparing two primary prostate cancer methodologies (pooled sensitivity P = 0.62, pooled specificity P = 0.50). Despite this, the funnel plots showed symmetry and the Egger test results (P values > 0.05) suggested there was no publication bias.
CONCLUSIONS: After an extensive meta-analysis, it was found that both 68Ga-PSMA-11 PET/CT and mpMRI demonstrate similar diagnostic effectiveness in detecting primary prostate cancer. Future larger prospective studies are warranted to investigate this issue further.
Fulltext Machine Learning Models for Predicting Stroke Mortality in Malaysia: An Application and Comparative Analysis

Che Nawi CMNH, Mohd Hairon S, Wan Yahya WNN, Wan Zaidi WA, Musa KI

Cureus, 2023 Dec;15(12):e50426.
PMID: 38222138 DOI: 10.7759/cureus.50426

Background Stroke is a significant public health concern characterized by increasing mortality and morbidity. Accurate long-term outcome prediction for acute stroke patients, particularly stroke mortality, is vital for clinical decision-making and prognostic management. This study aimed to develop and compare various prognostic models for stroke mortality prediction. Methods In a retrospective cohort study from January 2016 to December 2021, we collected data from patients diagnosed with acute stroke from five selected hospitals. Data contained variables on demographics, comorbidities, and interventions retrieved from medical records. The cohort comprised 950 patients with 20 features. Outcomes (censored vs. death) were determined by linking data with the Malaysian National Mortality Registry. We employed three common survival modeling approaches, the Cox proportional hazard regression (Cox), support vector machine (SVM), and random survival forest (RSF), while enhancing the Cox model with Elastic Net (Cox-EN) for feature selection. Models were compared using the concordance index (C-index), time-dependent area under the curve (AUC), and discrimination index (D-index), with calibration assessed by the Brier score. Results The support vector machine (SVM) model excelled among the four, with three-month, one-year, and three-year time-dependent AUC values of 0.842, 0.846, and 0.791; a D-index of 5.31 (95% CI: 3.86, 7.30); and a C-index of 0.803 (95% CI: 0.758, 0.847). All models exhibited robust calibration, with three-month, one-year, and three-year Brier scores ranging from 0.103 to 0.220, all below 0.25. Conclusion The support vector machine (SVM) model demonstrated superior discriminative performance, suggesting its efficacy in developing prognostic models for stroke mortality. This study enhances stroke mortality prediction and supports clinical decision-making, emphasizing the utility of the support vector machine method.
Revolutionizing lignocellulosic biomass: A review of harnessing the power of ionic liquids for sustainable utilization and extraction

Norfarhana AS, Ilyas RA, Ngadi N, Othman MHD, Misenan MSM, Norrrahim MNF

Int J Biol Macromol, 2024 Jan;256(Pt 1):128256.
PMID: 38000585 DOI: 10.1016/j.ijbiomac.2023.128256

The potential for the transformation of lignocellulosic biomass into valuable commodities is rapidly growing through an environmentally sustainable approach to harness its abundance, cost-effectiveness, biodegradability, and environmentally friendly nature. Ionic liquids (ILs) have received considerable and widespread attention as a promising solution for efficiently dissolving lignocellulosic biomass. The fact that ILs can act as solvents and reagents contributes to their widespread recognition. In particular, ILs are desirable because they are inert, non-toxic, non-flammable, miscible in water, recyclable, thermally and chemically stable, and have low melting points and outstanding ionic conductivity. With these characteristics, ILs can serve as a reliable replacement for traditional biomass conversion methods in various applications. Thus, this comprehensive analysis explores the conversion of lignocellulosic biomass using ILs, focusing on main components such as cellulose, hemicellulose, and lignin. In addition, the effect of multiple parameters on the separation of lignocellulosic biomass using ILs is discussed to emphasize their potential to produce high-value products from this abundant and renewable resource. This work contributes to the advancement of green technologies, offering a promising avenue for the future of biomass conversion and sustainable resource management.
Heat and Wheat: Adaptation strategies with respect to heat shock proteins and antioxidant potential; an era of climate change

Abasi F, Raja NI, Mashwani ZU, Ehsan M, Ali H, Shahbaz M

Int J Biol Macromol, 2024 Jan;256(Pt 1):128379.
PMID: 38000583 DOI: 10.1016/j.ijbiomac.2023.128379

Extreme changes in weather including heat-wave and high-temperature fluctuations are predicted to increase in intensity and duration due to climate change. Wheat being a major staple crop is under severe threat of heat stress especially during the grain-filling stage. Widespread food insecurity underscores the critical need to comprehend crop responses to forthcoming climatic shifts, pivotal for devising adaptive strategies ensuring sustainable crop productivity. This review addresses insights concerning antioxidant, physiological, molecular impacts, tolerance mechanisms, and nanotechnology-based strategies and how wheat copes with heat stress at the reproductive stage. In this study stress resilience strategies were documented for sustainable grain production under heat stress at reproductive stage. Additionally, the mechanisms of heat resilience including gene expression, nanomaterials that trigger transcription factors, (HSPs) during stress, and physiological and antioxidant traits were explored. The most reliable method to improve plant resilience to heat stress must include nano-biotechnology-based strategies, such as the adoption of nano-fertilizers in climate-smart practices and the use of advanced molecular approaches. Notably, the novel resistance genes through advanced molecular approach and nanomaterials exhibit promise for incorporation into wheat cultivars, conferring resilience against imminent adverse environmental conditions. This review will help scientific communities in thermo-tolerance wheat cultivars and new emerging strategies to mitigate the deleterious impact of heat stress.
Fulltext Therapeutic potentials of iridoids derived from Rubiaceae against in vitro and in vivo inflammation: A scoping review

Jaafar A, Zulkipli MA, Mohd Hatta FH, Jahidin AH, Abdul Nasir NA, Hazizul Hasan M

Saudi Pharm J, 2024 Jan;32(1):101876.
PMID: 38226349 DOI: 10.1016/j.jsps.2023.101876

Acute inflammation may develop into chronic, life-threatening inflammation-related diseases if left untreated or if there are persistent triggering factors. Cancer, diabetes mellitus, stroke, cardiovascular diseases, and neurodegenerative disorders are some of the inflammation-related diseases affecting millions of people worldwide. Despite that, conventional medical therapy such as non-steroidal anti-inflammatory drugs (NSAIDs) is associated with serious adverse effects; hence, there is an urgent need for a newer and safer therapeutic alternative from natural sources. Iridoids are naturally occurring heterocyclic monoterpenoids commonly found in Rubiaceae plants. Plant extracts from the Rubiaceae family were demonstrated to have medicinal benefits against neurodegeneration, inflammation, oxidative stress, hyperglycaemia, and cancer. However, the therapeutic effects of natural iridoids derived from Rubiaceae as well as their prospective impacts on inflammation in vitro and in vivo have not been thoroughly explored. The databases of PubMed, Scopus, and Web of Science were searched for pertinent articles in accordance with PRISMA-ScR guidelines. A total of 31 pertinent articles from in vitro and in vivo studies on the anti-inflammatory potentials of iridoids from Rubiaceae were identified. According to current research, genipin, geniposide, and monotropein are the most researched iridoids from Rubiaceae that reduce inflammation. These iridoids primarily act by attenuating inflammatory cytokines and mediators via inhibition of the NF-κB signalling pathway in various disease models. A comprehensive overview of the current research on the anti-inflammatory properties of iridoids from the Rubiaceae family is presented in this review, highlighting the characteristics of the experimental models used as well as the mechanisms of action of these iridoids. To develop an alternative therapeutic agent from iridoids, more studies are needed to elucidate the effects and mechanism of action of iridoids in a wide variety of experimental models as well as in clinical studies pertaining to inflammation-related diseases.
Salmonella serovars trend in poultry Malaysia from 2011 to 2020

Ibrahim MM, Jusoh MB, Rose FZC, Azami MM, Roslee R

Vet Res Commun, 2024 Jan 19.
PMID: 38238509 DOI: 10.1007/s11259-024-10303-5

Data and geographical trend of Salmonella serovars infecting poultry in Malaysia is limited. In this study, the trend of Salmonella serovars infection was presented for the past ten years from 2011 to 2020 and the predominant serovars were mapped based on geographical distribution. Analysis of passive surveillance data demonstrated a shift of Salmonella serovars that infected poultry in Malaysia. The Salmonella serovars varied within ten years of registered cases with the Veterinary Research Institute, Ipoh, Malaysia involving samples from live and dead birds. Total number of cases found from the year 2011 to 2020 were 391 cases, involving 73 Salmonella serovars with an additional one group of unclassified serovars known as Salmonella spp. Further analysis revealed that eight serovars were found predominant throughout the ten-year period. These included S. Albany, S. Braenderup, S. Brancaster, S. Corvallis, S. Enteritidis, S. Kentucky, S. Typhimurium and S. Weltevreden. Salmonella spp. (Salmonella that is incapable to be identified based on serotyping) were also one of the major groups observed throughout the years. This study could help the authorities to improvise policies for better disease control programs through the establishment of diagnostic tools for rapid Salmonella screening in poultry.
Fulltext Inflammatory endobronchial polyps unleashing recurrent pneumothorax: A case report

Daut UN, Faisal Thena MH, Hui-Xin T, Nasaruddin MZ, Abdul Rahaman JA

Respirol Case Rep, 2024 Jan;12(1):e01278.
PMID: 38239333 DOI: 10.1002/rcr2.1278

Inflammatory endobronchial polyps (IEPs) are rare benign lesions that originate from the bronchial mucosa. While pneumothorax is a well-known complication of various pulmonary conditions, its association with IEPs is exceedingly uncommon and poorly understood. This case report presents a unique and explosive encounter of a patient with an inflammatory endobronchial polyp who experienced a pneumothorax, shedding light on the clinical presentation, diagnostic challenges, and management strategies for this rare entity.
Three-dimensional surface area analyses of developing maxillary second premolar root apices for age estimation using CBCT images

Gohain M, Asif MK, Nambiar P, Mohd Noor NS, Hidayah Reduwan N, Ibrahim N

Leg Med (Tokyo), 2024 Feb;66:102391.
PMID: 38211402 DOI: 10.1016/j.legalmed.2024.102391

Three-dimensional surface area analyses of developing root apices for age estimation in children and young adults have shown promising results. The current study aimed to apply this three-dimensional method to develop a regression model for estimating age in Malaysian children aged 7 to 14 using developing maxillary second premolars. A training sample of 155 cone-beam computed tomography scans (83 Malays and 72 Chinese) was analysed, and the formula was subsequently validated on an independent sample of 92 cone-beam computed tomography scans (45 Malays and 47 Chinese). The results showed a strong correlation (r = 94 %) between the chronological age as a dependent variable and the predictor variables, including root surface area of the apex, sex, ethnicity, and root development status (open/closed apices). For this model, the predictor variables accounted for 88.4 % of the variation in age except sex and ethnicity. A mean absolute error value of 0.42 indicated that this model can be reliably used for Malaysian children. In conclusion, this study recognises the method of three-dimensional surface area analyses as a valuable tool for age estimation in forensic and clinical practice. Further studies are highly recommended to assess its effectiveness across different demographic groups.
Fulltext The evolution of smart hotels: A bibliometric review of the past, present and future trends

Liu X, Wider W, Fauzi MA, Jiang L, Udang LN, Hossain SFA

Heliyon, 2024 Feb 29;10(4):e26472.
PMID: 38420486 DOI: 10.1016/j.heliyon.2024.e26472

This study provides a bibliometric analysis of smart hotel research, drawing from 613 publications in the Web of Science (WoS) database to examine scholarly trends and developments in this dynamic field. Smart hotels, characterized by integrating advanced technologies such as AI, IoT, cloud computing, and big data, aim to redefine customer experiences and operational efficiency. Utilizing co-citation and co-word analysis techniques, the research delves into the depth of literature from past to future trends. In co-citation analysis, clusters including "Sustainable Hotel and Green Hotel", "Theories Integration in Smart Hotel Research", and "Consumers' Decisions about Green Hotels" underscore the pivotal areas of past and current research. Co-word analysis further reveals emergent trend clusters: "The New Era of Sustainable Tourism", "Elevating Standards and Guest Loyalty", and "Hotels' New Sustainable Blueprint in Modern Travel". These clusters reflect the industry's evolving focus on sustainability and technology-enhanced guest experiences. Theoretically, this research bridges gaps in smart hotel literature, proposing new frameworks for understanding customer decisions amid technological advancements and environmental responsibilities. Practically, it offers valuable insights for hotel managers, guiding technology integration strategies for enhanced efficiency and customer loyalty while underscoring the critical role of green strategies and sustainability.

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