Browse publications by year: 2021

Fulltext A Hybrid Active Neutral Point Clamped Inverter Utilizing Si and Ga2O3 Semiconductors: Modelling and Performance Analysis

Meraj ST, Yahaya NZ, Hossain Lipu MS, Islam J, Haw LK, Hasan K, et al.

Micromachines (Basel), 2021 Nov 27;12(12).
PMID: 34945316 DOI: 10.3390/mi12121466

In this paper, the performance of an active neutral point clamped (ANPC) inverter is evaluated, which is developed utilizing both silicon (Si) and gallium trioxide (Ga2O3) devices. The hybridization of semiconductor devices is performed since the production volume and fabrication of ultra-wide bandgap (UWBG) semiconductors are still in the early-stage, and they are highly expensive. In the proposed ANPC topology, the Si devices are operated at a low switching frequency, while the Ga2O3 switches are operated at a higher switching frequency. The proposed ANPC mitigates the fault current in the switching devices which are prevalent in conventional ANPCs. The proposed ANPC is developed by applying a specified modulation technique and an intelligent switching arrangement, which has further improved its performance by optimizing the loss distribution among the Si/Ga2O3 devices and thus effectively increases the overall efficiency of the inverter. It profoundly reduces the common mode current stress on the switches and thus generates a lower common-mode voltage on the output. It can also operate at a broad range of power factors. The paper extensively analyzed the switching performance of UWBG semiconductor (Ga2O3) devices using double pulse testing (DPT) and proper simulation results. The proposed inverter reduced the fault current to 52 A and achieved a maximum efficiency of 99.1%.
Fulltext Wearable Metamaterial Dual-Polarized High Isolation UWB MIMO Vivaldi Antenna for 5G and Satellite Communications

Alhawari ARH, Saeidi T, Almawgani AHM, Hindi AT, Alghamdi H, Alsuwian T, et al.

Micromachines (Basel), 2021 Dec 14;12(12).
PMID: 34945409 DOI: 10.3390/mi12121559

A low-profile Multiple Input Multiple Output (MIMO) antenna showing dual polarization, low mutual coupling, and acceptable diversity gain is presented by this paper. The antenna introduces the requirements of fifth generation (5G) and the satellite communications. A horizontally (4.8-31 GHz) and vertically polarized (7.6-37 GHz) modified antipodal Vivaldi antennas are simulated, fabricated, and integrated, and then their characteristics are examined. An ultra-wideband (UWB) at working bandwidths of 3.7-3.85 GHz and 5-40 GHz are achieved. Low mutual coupling of less than -22 dB is achieved after loading the antenna with cross-curves, staircase meander line, and integration of the metamaterial elements. The antennas are designed on a denim textile substrate with εr = 1.4 and h = 0.5 mm. A conductive textile called ShieldIt is utilized as conductor with conductivity of 1.8 × 104. After optimizing the proposed UWB-MIMO antenna's characteristics, it is increased to four elements positioned at the four corners of a denim textile substrate to be employed as a UWB-MIMO antenna for handset communications, 5G, Ka and Ku band, and satellite communications (X-band). The proposed eight port UWB-MIMO antenna has a maximum gain of 10.7 dBi, 98% radiation efficiency, less than 0.01 ECC, and acceptable diversity gain. Afterwards, the eight-ports antenna performance is examined on a simulated real voxel hand and chest. Then, it is evaluated and compared on physical hand and chest of body. Evidently, the simulated and measured results show good agreement between them. The proposed UWB-MIMO antenna offers a compact and flexible design, which is suitably wearable for 5G and satellite communications applications.
Fulltext An Improved Moth-Flame Optimization Algorithm with Adaptation Mechanism to Solve Numerical and Mechanical Engineering Problems

Nadimi-Shahraki MH, Fatahi A, Zamani H, Mirjalili S, Abualigah L

Entropy (Basel), 2021 Dec 06;23(12).
PMID: 34945943 DOI: 10.3390/e23121637

Moth-flame optimization (MFO) algorithm inspired by the transverse orientation of moths toward the light source is an effective approach to solve global optimization problems. However, the MFO algorithm suffers from issues such as premature convergence, low population diversity, local optima entrapment, and imbalance between exploration and exploitation. In this study, therefore, an improved moth-flame optimization (I-MFO) algorithm is proposed to cope with canonical MFO's issues by locating trapped moths in local optimum via defining memory for each moth. The trapped moths tend to escape from the local optima by taking advantage of the adapted wandering around search (AWAS) strategy. The efficiency of the proposed I-MFO is evaluated by CEC 2018 benchmark functions and compared against other well-known metaheuristic algorithms. Moreover, the obtained results are statistically analyzed by the Friedman test on 30, 50, and 100 dimensions. Finally, the ability of the I-MFO algorithm to find the best optimal solutions for mechanical engineering problems is evaluated with three problems from the latest test-suite CEC 2020. The experimental and statistical results demonstrate that the proposed I-MFO is significantly superior to the contender algorithms and it successfully upgrades the shortcomings of the canonical MFO.
Fulltext Multilevel Deep Feature Generation Framework for Automated Detection of Retinal Abnormalities Using OCT Images

Barua PD, Chan WY, Dogan S, Baygin M, Tuncer T, Ciaccio EJ, et al.

Entropy (Basel), 2021 Dec 08;23(12).
PMID: 34945957 DOI: 10.3390/e23121651

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.
Fulltext Double-Layer Micro Porous Media Burner from Lean to Rich Fuel Mixture: Analysis of Entropy Generation and Exergy Efficiency

Ismail NC, Abdullah MZ, Mustafa KF, Mazlan NM, Gunnasegaran P, Irawan AP

Entropy (Basel), 2021 Dec 10;23(12).
PMID: 34945969 DOI: 10.3390/e23121663

Porous media burner (PMB) is widely used in a variety of practical systems, including heat exchangers, gas propulsion, reactors, and radiant burner combustion. However, thorough evaluations of the performance of the PMB based on the usefulness of entropy generation, thermal and exergy efficiency aspects are still lacking. In this work, the concept of a double-layer micro PMB with a 23 mm cylindrical shape burner was experimentally demonstrated. The PMB was constructed based on the utilization of premixed butane-air combustion which consists of an alumina and porcelain foam. The tests were designed to cover lean to rich combustion with equivalence ratios ranging from ϕ = 0.6 to ϕ = 1.2. It was found that the maximum thermal and exergy efficiency was obtained at ϕ = 1.2 while the lowest thermal and exergy efficiency was found at ϕ = 0.8. Furthermore, the findings also indicated that the total entropy generation, energy loss, and exergy destroyed yield the lowest values at ϕ = 1.0 with 0.0048 W/K, 98.084 W, and 1.456 W, respectively. These values can be stated to be the suitable operating conditions of the PMB. The findings provided useful information on the design and operation in a double-layer PMB.
Fulltext Enhanced Slime Mould Algorithm for Multilevel Thresholding Image Segmentation Using Entropy Measures

Lin S, Jia H, Abualigah L, Altalhi M

Entropy (Basel), 2021 Dec 20;23(12).
PMID: 34946006 DOI: 10.3390/e23121700

Image segmentation is a fundamental but essential step in image processing because it dramatically influences posterior image analysis. Multilevel thresholding image segmentation is one of the most popular image segmentation techniques, and many researchers have used meta-heuristic optimization algorithms (MAs) to determine the threshold values. However, MAs have some defects; for example, they are prone to stagnate in local optimal and slow convergence speed. This paper proposes an enhanced slime mould algorithm for global optimization and multilevel thresholding image segmentation, namely ESMA. First, the Levy flight method is used to improve the exploration ability of SMA. Second, quasi opposition-based learning is introduced to enhance the exploitation ability and balance the exploration and exploitation. Then, the superiority of the proposed work ESMA is confirmed concerning the 23 benchmark functions. Afterward, the ESMA is applied in multilevel thresholding image segmentation using minimum cross-entropy as the fitness function. We select eight greyscale images as the benchmark images for testing and compare them with the other classical and state-of-the-art algorithms. Meanwhile, the experimental metrics include the average fitness (mean), standard deviation (Std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), feature similarity index (FSIM), and Wilcoxon rank-sum test, which is utilized to evaluate the quality of segmentation. Experimental results demonstrated that ESMA is superior to other algorithms and can provide higher segmentation accuracy.
Fulltext Structure-Function Characteristics of SARS-CoV-2 Proteases and Their Potential Inhibitors from Microbial Sources

Razali R, Asis H, Budiman C

Microorganisms, 2021 Nov 30;9(12).
PMID: 34946083 DOI: 10.3390/microorganisms9122481

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is considered the greatest challenge to the global health community of the century as it continues to expand. This has prompted immediate urgency to discover promising drug targets for the treatment of COVID-19. The SARS-CoV-2 viral proteases, 3-chymotrypsin-like protease (3CLpro) and papain-like cysteine protease (PLpro), have become the promising target to study due to their essential functions in spreading the virus by RNA transcription, translation, protein synthesis, processing and modification, virus replication, and infection of the host. As such, understanding of the structure and function of these two proteases is unavoidable as platforms for the development of inhibitors targeting this protein which further arrest the infection and spread of the virus. While the abundance of reports on the screening of natural compounds such as SARS-CoV-2 proteases inhibitors are available, the microorganisms-based compounds (peptides and non-peptides) remain less studied. Indeed, microorganisms-based compounds are also one of the potent antiviral candidates against COVID-19. Microbes, especially bacteria and fungi, are other resources to produce new drugs as well as nucleosides, nucleotides, and nucleic acids. Thus, we have compiled various reported literature in detail on the structures, functions of the SARS-CoV-2 proteases, and potential inhibitors from microbial sources as assistance to other researchers working with COVID-19. The compounds are also compared to HIV protease inhibitors which suggested the microorganisms-based compounds are advantageous as SARS-CoV2 proteases inhibitors. The information should serve as a platform for further development of COVID-19 drug design strategies.
Fulltext An Overview of Helicobacter pylori Survival Tactics in the Hostile Human Stomach Environment

Cheok YY, Lee CYQ, Cheong HC, Vadivelu J, Looi CY, Abdullah S, et al.

Microorganisms, 2021 Dec 03;9(12).
PMID: 34946105 DOI: 10.3390/microorganisms9122502

Helicobacter pylori is well established as a causative agent for gastritis, peptic ulcer, and gastric cancer. Armed with various inimitable virulence factors, this Gram-negative bacterium is one of few microorganisms that is capable of circumventing the harsh environment of the stomach. The unique spiral structure, flagella, and outer membrane proteins accelerate H. pylori movement within the viscous gastric mucosal layers while facilitating its attachment to the epithelial cells. Furthermore, secretion of urease from H. pylori eases the acidic pH within the stomach, thus creating a niche for bacteria survival and replication. Upon gaining a foothold in the gastric epithelial lining, bacterial protein CagA is injected into host cells through a type IV secretion system (T4SS), which together with VacA, damage the gastric epithelial cells. H. pylori does not only establishes colonization in the stomach, but also manipulates the host immune system to permit long-term persistence. Prolonged H. pylori infection causes chronic inflammation that precedes gastric cancer. The current review provides a brief outlook on H. pylori survival tactics, bacterial-host interaction and their importance in therapeutic intervention as well as vaccine development.
Fulltext Mining the Genome of Bacillus velezensis VB7 (CP047587) for MAMP Genes and Non-Ribosomal Peptide Synthetase Gene Clusters Conferring Antiviral and Antifungal Activity

R S, Nakkeeran S, Saranya N, Senthilraja C, Renukadevi P, Krishnamoorthy AS, et al.

Microorganisms, 2021 Dec 03;9(12).
PMID: 34946111 DOI: 10.3390/microorganisms9122511

Chemical pesticides have an immense role in curbing the infection of plant viruses and soil-borne pathogens of high valued crops. However, the usage of chemical pesticides also contributes to the development of resistance among pathogens. Hence, attempts were made in this study to identify a suitable bacterial antagonist for managing viral and fungal pathogens infecting crop plants. Based on our earlier investigations, we identified Bacillus amyloliquefaciens VB7 as a potential antagonist for managing Sclerotinia sclerotiorum infecting carnation, tobacco streak virus infecting cotton and groundnut bud necrosis infecting tomato. Considering the multifaceted action of B. amyloliquefaciens VB7, attempts were made for whole-genome sequencing to assess the antiviral activity against tomato spotted wilt virus infecting chrysanthemum and antifungal action against Fusarium oxysporum f. sp. cubense (Foc). Genome annotation of the isolate B. amyloliquefaciens VB7 was confirmed as B. velezensis VB7 with accession number CP047587. Genome analysis revealed the presence of 9,231,928 reads with an average read length of 149 bp. Assembled genome had 1 contig, with a total length of 3,021,183 bp and an average G+C content of 46.79%. The protein-coding sequences (CDS) in the genome was 3090, transfer RNA (tRNA) genes were 85 with 29 ribosomal RNA (rRNA) genes and 21 repeat regions. The genome of B. velezensis VB7 had 506 hypothetical proteins and 2584 proteins with functional assignments. VB7 genome had the presence of flagellin protein FlaA with 987 nucleotides and translation elongation factor TU (Ef-Tu) with 1191 nucleotides. The identified ORFs were 3911 with 47.22% GC content. Non ribosomal pepide synthetase cluster (NRPS) gene clusters in the genome of VB7, coded for the anti-microbial peptides surfactin, butirosin A/butirosin B, fengycin, difficidin, bacillibactin, bacilysin, and mersacidin the Ripp lanthipeptide. Antiviral action of VB7 was confirmed by suppression of local lesion formation of TSWV in the local lesion host cowpea (Co-7). Moreover, combined application of B. velezensis VB7 with phyto-antiviral principles M. Jalapa and H. cupanioides increased shoot length, shoot diameter, number of flower buds per plant, flower diameter, and fresh weight of chrysanthemum. Further, screening for antifungal action of VB7 expressed antifungal action against Foc in vitro by producing VOC/NVOC compounds, including hexadecanoic acid, linoelaidic acid, octadecanoic acid, clindamycin, formic acid, succinamide, furanone, 4H-pyran, nonanol and oleic acid, contributing to the total suppression of Foc apart from the presence of NRPS gene clusters. Thus, our study confirmed the scope for exploring B. velezensis VB7 on a commercial scale to manage tomato spotted wilt virus, groundnut bud necrosis virus, tobacco streak virus, S. sclerotiorum, and Foc causing panama wilt of banana.
Fulltext Isolation and Identification of Wild Yeast from Malaysian Grapevine and Evaluation of Their Potential Antimicrobial Activity against Grapevine Fungal Pathogens

Sabaghian S, Braschi G, Vannini L, Patrignani F, Samsulrizal NH, Lanciotti R

Microorganisms, 2021 Dec 13;9(12).
PMID: 34946182 DOI: 10.3390/microorganisms9122582

Pathogenic fungi belonging to the genera Botrytis, Phaeomoniella, Fusarium, Alternaria and Aspergillus are responsible for vines diseases that affect the growth, grapevine yield and organoleptic quality. Among innovative strategies for in-field plant disease control, one of the most promising is represented by biocontrol agents, including wild epiphytic yeast strains of grapevine berries. Twenty wild yeast, isolated and molecularly identified from three different Malaysian regions (Perlis, Perak and Pahang), were evaluated in a preliminary screening test on agar to select isolates with inhibition against Botrytis cinerea. On the basis of the results, nine yeasts belonging to genera Hanseniaspora, Starmerella, Metschnikowia, Candida were selected and then tested against five grape berry pathogens: Aspergillus carbonarius, Aspergillus ochraceus, Fusarium oxysporum, Alternaria alternata and Phaeomoniella chlamydospora.Starmerella bacillaris FE08.05 and Metschnikowia pulcherrima GP8 and Hanseniaspora uvarum GM19 showed the highest effect on inhibiting mycelial growth, which ranged between 15.1 and 4.3 mm for the inhibition ring. The quantitative analysis of the volatile organic compound profiles highlighted the presence of isoamyl and phenylethyl alcohols and an overall higher presence of low-chain fatty acids and volatile ethyl esters. The results of this study suggest that antagonist yeasts, potentially effective for the biological control of pathogenic moulds, can be found among the epiphytic microbiota associated with grape berries.
Fulltext A Qualitative Study of Pictorial Health Warnings on Malaysian Cigarette Packs: How Do the Adults Understand Them?

Hamzah AM, Saub R, Marhazlinda J

Healthcare (Basel), 2021 Dec 02;9(12).
PMID: 34946395 DOI: 10.3390/healthcare9121669

The WHO recommended pictorial health warnings (PHWs) on cigarette packs in 2003 to educate and warn the public of smoking effects. Malaysia too has implemented this policy since 2009. This study explored the public's understanding of the gazetted PHWs depicted on cigarette packs available in Malaysia. A qualitative study using four focus group discussions (FGDs) was conducted among smokers and non-smokers aged 18-40 in Malacca, Peninsular Malaysia. Thematic analyses were performed using the Atlas Ti version 8.0 software. Six themes have emerged reflecting the public's understanding of the existing PHWs in Malaysia, namely, (i) awareness and exposures, (ii) recall and attention, (iii) perceived goals, (iv) perceived target groups, (v) attitude in understanding, and (vi) knowledge and meaning of PHWs. All participants were aware of the PHWs depicted on legal cigarettes but not seen on most illicit cigarettes. PHWs were perceived to give awareness and warning about the smoking effects targeting smokers and non-smokers. Participants understood the lung and oral health-related images easily than other body parts such as gangrene foot, miscarriages, etc. Besides enforcement on illicit cigarettes without PHWs, policymakers or relevant authorities should emphasize creating relevant and clear pictorial messages in educating the public to avoid confusion affecting the public's understanding of the PHWs.
Fulltext A Comprehensive Survey of Image-Based Food Recognition and Volume Estimation Methods for Dietary Assessment

Tahir GA, Loo CK

Healthcare (Basel), 2021 Dec 03;9(12).
PMID: 34946400 DOI: 10.3390/healthcare9121676

Dietary studies showed that dietary problems such as obesity are associated with other chronic diseases, including hypertension, irregular blood sugar levels, and increased risk of heart attacks. The primary cause of these problems is poor lifestyle choices and unhealthy dietary habits, which are manageable using interactive mHealth apps. However, traditional dietary monitoring systems using manual food logging suffer from imprecision, underreporting, time consumption, and low adherence. Recent dietary monitoring systems tackle these challenges by automatic assessment of dietary intake through machine learning methods. This survey discusses the best-performing methodologies that have been developed so far for automatic food recognition and volume estimation. Firstly, the paper presented the rationale of visual-based methods for food recognition. Then, the core of the study is the presentation, discussion, and evaluation of these methods based on popular food image databases. In this context, this study discusses the mobile applications that are implementing these methods for automatic food logging. Our findings indicate that around 66.7% of surveyed studies use visual features from deep neural networks for food recognition. Similarly, all surveyed studies employed a variant of convolutional neural networks (CNN) for ingredient recognition due to recent research interest. Finally, this survey ends with a discussion of potential applications of food image analysis, existing research gaps, and open issues of this research area. Learning from unlabeled image datasets in an unsupervised manner, catastrophic forgetting during continual learning, and improving model transparency using explainable AI are potential areas of interest for future studies.
Fulltext Hospital Facebook Reviews Analysis Using a Machine Learning Sentiment Analyzer and Quality Classifier

Rahim AIA, Ibrahim MI, Chua SL, Musa KI

Healthcare (Basel), 2021 Dec 03;9(12).
PMID: 34946405 DOI: 10.3390/healthcare9121679

While experts have recognised the significance and necessity of social media integration in healthcare, no systematic method has been devised in Malaysia or Southeast Asia to include social media input into the hospital quality improvement process. The goal of this work is to explain how to develop a machine learning system for classifying Facebook reviews of public hospitals in Malaysia by using service quality (SERVQUAL) dimensions and sentiment analysis. We developed a Machine Learning Quality Classifier (MLQC) based on the SERVQUAL model and a Machine Learning Sentiment Analyzer (MLSA) by manually annotated multiple batches of randomly chosen reviews. Logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and other methods were used to train the classifiers. The performance of each classifier was tested using 5-fold cross validation. For topic classification, the average F1-score was between 0.687 and 0.757 for all models. In a 5-fold cross validation of each SERVQUAL dimension and in sentiment analysis, SVM consistently outperformed other methods. The study demonstrates how to use supervised learning to automatically identify SERVQUAL domains and sentiments from patient experiences on a hospital's Facebook page. Malaysian healthcare providers can gather and assess data on patient care via the use of these content analysis technology to improve hospital quality of care.
Fulltext Challenges and Innovations Brought about by the COVID-19 Pandemic Regarding Medical and Pharmacy Education Especially in Africa and Implications for the Future

Etando A, Amu AA, Haque M, Schellack N, Kurdi A, Alrasheedy AA, et al.

Healthcare (Basel), 2021 Dec 13;9(12).
PMID: 34946448 DOI: 10.3390/healthcare9121722

BACKGROUND: Multiple measures introduced early to restrict COVID-19 have dramatically impacted the teaching of medical and pharmacy students, exacerbated by the lack of infrastructure and experience with e-learning at the start of the pandemic. In addition, the costs and reliability of the Internet across Africa pose challenges alongside undertaking clinical teaching and practical programmes. Consequently, there is a need to understand the many challenges and how these were addressed, given increasingly complex patients, to provide future direction.
METHOD: An exploratory study was conducted among senior-level medical and pharmacy educators across Africa, addressing four key questions, including the challenges resulting from the pandemic and how these were dealt with.
RESULTS: Staff and student members faced multiple challenges initially, including adapting to online learning. In addition, concerns with the lack of equipment (especially among disadvantaged students), the costs of Internet bundles, and how to conduct practicals and clinical teaching. Multiple activities were undertaken to address these challenges. These included training sessions, developing innovative approaches to teaching, and seeking ways to reduce Internet costs. Robust approaches to practicals, clinical teaching, and assessments have been developed.
CONCLUSIONS: Appreciable difficulties to teaching arising from the pandemic are being addressed across Africa. Research is ongoing to improve education and assessments.
Fulltext Comparison of Mean Glandular Dose between Full-Field Digital Mammography and Digital Breast Tomosynthesis

Teoh KC, Manan HA, Mohd Norsuddin N, Rizuana IH

Healthcare (Basel), 2021 Dec 19;9(12).
PMID: 34946484 DOI: 10.3390/healthcare9121758

Early detection of breast cancer is diagnosed using mammography, the gold standard in breast screening. However, its increased use also provokes radiation-induced breast malignancy. Thus, monitoring and regulating the mean glandular dose (MGD) is essential. The purpose of this study was to determine MGD for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in the radiology department of a single centre. We also analysed the exposure factors as a function of breast thickness. A total of 436 patients underwent both FFDM and DBT. MGD was auto calculated by the mammographic machine for each projection. Patients' data included compressed breast thickness (CBT), peak kilovoltage (kVp), milliampere-seconds (mAs) and MGD (mGy). Result analysis showed that there is a significant difference in MGD between the two systems, namely FFDM and DBT. However, the MGD values in our centre were comparable to other centres, as well as the European guideline (<2.5 mGy) for a standard breast. Although DBT improves the clinical outcome and quality of diagnosis, the risk of radiation-induced carcinogenesis should not be neglected. Regular quality control testing on mammography equipment must be performed for dose monitoring in women following a screening mammography in the future.
Fulltext MHD Stagnation Point on Nanofluid Flow and Heat Transfer of Carbon Nanotube over a Shrinking Surface with Heat Sink Effect

Othman MN, Jedi A, Bakar NAA

Molecules, 2021 Dec 08;26(24).
PMID: 34946524 DOI: 10.3390/molecules26247441

This study is to investigate the magnetohydrodynamic (MHD) stagnation point flow and heat transfer characteristic nanofluid of carbon nanotube (CNTs) over the shrinking surface with heat sink effects. Similarity equations deduced from momentum and energy equation of partial differential equations are solved numerically. This study looks at the different parameters of the flow and heat transfer using first phase model which is Tiwari-Das. The parameter discussed were volume fraction nanoparticle, magnetic parameter, heat sink/source parameters, and a different type of nanofluid and based fluids. Present results revealed that the rate of nanofluid (SWCNT/kerosene) in terms of flow and heat transfer is better than (MWCNT/kerosene) and (CNT/water) and regular fluid (water). Graphically, the variation results of dual solution exist for shrinking parameter in range λc
Fulltext Application of the Metabolomics Approach in Food Authentication

Selamat J, Rozani NAA, Murugesu S

Molecules, 2021 Dec 14;26(24).
PMID: 34946647 DOI: 10.3390/molecules26247565

The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.

MeSH terms: Food*; Food Analysis*; Food Handling*; Metabolomics*; Food Quality*
Fulltext Metabolite Fingerprinting Using 1H-NMR Spectroscopy and Chemometrics for Classification of Three Curcuma Species from Different Origins

Nurani LH, Rohman A, Windarsih A, Guntarti A, Riswanto FDO, Lukitaningsih E, et al.

Molecules, 2021 Dec 16;26(24).
PMID: 34946709 DOI: 10.3390/molecules26247626

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. 1H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the 1H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R2 value more than 0.8) and good predictivity (Q2 value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R2 and Q2. It can be concluded that metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

MeSH terms: Plant Extracts/analysis*; Nuclear Magnetic Resonance, Biomolecular*; Curcuma/classification*; Curcuma/chemistry*
Fulltext Botanical Origin Differentiation of Malaysian Stingless Bee Honey Produced by Heterotrigona itama and Geniotrigona thoracica Using Chemometrics

Ng WJ, Sit NW, Ooi PA, Ee KY, Lim TM

Molecules, 2021 Dec 16;26(24).
PMID: 34946710 DOI: 10.3390/molecules26247628

Stingless bee honey, specifically honeydew honey, is generally valued for its better health benefits than those of most blossom types. However, scientific studies about the differentiation of stingless bee honey based on honeydew and blossom origins are very limited. In this study, 13C NMR spectroscopy was employed to quantify the seven major sugar tautomers in stingless bee honey samples, and the major sugar compositions of both honeydew and blossom types were found not significantly different. However, several physicochemical properties of honeydew honey including moisture content, free acidity, electrical conductivity, ash content, acetic acid, diastase, hydrogen peroxide, and mineral elements levels were significantly higher; while total soluble solid, proline, and hydroxymethylfurfural were significantly lower than blossom honey. Greater antioxidant capacity in honeydew honey was proven with higher total phenolic compounds, ABTS, DPPH, superoxide radical scavenging activities, peroxyl radical inhibition, iron chelation, and ferric reducing power. Using principal component analysis (PCA), two clusters of stingless bee honey from the honeydew and blossom origin were observed. PCA also revealed that the differentiation between honeydew and blossom origin of stingless bee honey is possible with certain physicochemical and antioxidant parameters. The combination of NMR spectroscopy and chemometrics are suggested to be useful to determine the authenticity and botanical origin of stingless bee honey.

MeSH terms: Animals; Antioxidants/chemistry*; Bees*; Carbohydrates/chemistry*; Honey/analysis*; Malaysia; Phenols/chemistry*; Nuclear Magnetic Resonance, Biomolecular*
Fulltext Comparative Phylogeography and Phylogeny of Pennah Croakers (Teleostei: Sciaenidae) in Southeast Asian Waters

Lim HC, Habib A, Chen WJ

Genes (Basel), 2021 11 29;12(12).
PMID: 34946874 DOI: 10.3390/genes12121926

A broad-scale comparative phylogeographic and phylogenetic study of pennah croakers, mainly Pennahia anea, P. macrocephalus, and P. ovata was conducted to elucidate the mechanisms that may have driven the diversification of marine organisms in Southeast Asian waters. A total of 316 individuals from the three species, and an additional eight and six individuals of P. argentata and P. pawak were employed in this study. Two genetically divergent lineages each of P. argentata and P. anea (lineages L1 and L2) were respectively detected from the analyses based on mitochondrial cytochrome b gene data. Historical biogeography analysis with a multi-gene dataset revealed that Pennahia species most likely originated in the South China Sea and expanded into the eastern Indian Ocean, East China Sea, and northwestern Pacific Ocean through three separate range expansions. The main diversifications of Pennahia species occurred during Miocene and Pliocene periods, and the occurrences of lineage divergences within P. anea and P. argentata were during the Pleistocene, likely as a consequence of cyclical glaciations. The population expansions that occurred after the sea level rise might be the reason for the population homogeneity observed in P. macrocephalus and most P. anea L2 South China Sea populations. The structure observed between the two populations of P. ovata, and the restricted distributions of P. anea lineage L1 and P. ovata in the eastern Indian Ocean, might have been hampered by the northward flowing ocean current at the Malacca Strait and by the distribution of coral reefs or rocky bottoms. While our results support S. Ekman's center-of-origin hypothesis taking place in the South China Sea, the Malacca Strait serving as the center of overlap is a supplementary postulation for explaining the present-day high diversity of pennah croakers centered in these waters.

MeSH terms: Animals; Asia, Southeastern; Pacific Ocean; Perciformes/classification*; Perciformes/genetics; Phylogeny; Genetic Variation; Indian Ocean; Phylogeography

External Links