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Fulltext Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes

Uddin MR, Khandaker MU, Ahmed S, Abedin MJ, Hossain SMM, Al Mansur MA, et al.

PLoS One, 2024;19(4):e0300878.
PMID: 38635835 DOI: 10.1371/journal.pone.0300878

Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.

Matched MeSH terms: Environmental Monitoring/methods
Fulltext Translation and trans-cultural adaptation to the Malay version of the COVID-19 vaccine hesitancy questionnaire among healthcare workers in Malaysia

Zaid SNA, Abdul Kadir A, Mohd Noor N, Ahmad B, Yusoff MSB, Ramli AS, et al.

PLoS One, 2024;19(4):e0302237.
PMID: 38630657 DOI: 10.1371/journal.pone.0302237

INTRODUCTION: Healthcare workers play a crucial role in supporting COVID-19 vaccination as they are the most trusted source of information to the public population. Assessing the healthcare workers' hesitancy towards COVID-19 vaccination is pertinent, however, there are limited validated tools to measure their hesitancy on COVID-19 vaccines. This study aims to adapt and validate the first COVID-19 hesitancy scale among healthcare workers in Malaysia.
MATERIALS AND METHODS: This study adapted and translated the Vaccine Hesitancy Scale (VHS) developed by the WHO SAGE Working Group. The scale underwent a sequential validation process, including back-back translation, content, face, and construct validity for Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The reliability was tested using internal consistency (Cronbach's alpha composite reliability (CR) and average variance extracted (AVE)).
RESULTS: The data for EFA and CFA were completed by a separate sample of 125 and 300 HCWs, respectively. The EFA analysis of the C19-VHS-M scale was unidimensional with 10 items. A further CFA analysis revealed a uniform set of nine items with acceptable goodness fit indices (comparative fit index = 0.997, Tucker-Lewis index = 0.995, incremental fit index = 0.997, chi-squared/degree of freedom = 1.352, and root mean square error of approximation = 0.034). The Cronbach's alpha, CR and AVE results were 0.953, 0.95 and 0.70, respectively.
CONCLUSIONS: The questionnaire was valid and reliable for use in the Malay language.

Matched MeSH terms: Psychometrics/methods
Microbubbles: Revolutionizing Biomedical Applications with Tailored Therapeutic Precision

Kumar M, Kumar D, Chopra S, Mahmood S, Bhatia A

Curr Pharm Des, 2023;29(44):3532-3545.
PMID: 38151837 DOI: 10.2174/0113816128282478231219044000

BACKGROUND: Over the past ten years, tremendous progress has been made in microbubble-based research for a variety of biological applications. Microbubbles emerged as a compelling and dynamic tool in modern drug delivery systems. They are employed to deliver drugs or genes to targeted regions of interest, and then ultrasound is used to burst the microbubbles, causing site-specific delivery of the bioactive materials.
OBJECTIVE: The objective of this article is to review the microbubble compositions and physiochemical characteristics in relation to the development of innovative biomedical applications, with a focus on molecular imaging and targeted drug/gene delivery.
METHODS: The microbubbles are prepared by using various methods, which include cross-linking polymerization, emulsion solvent evaporation, atomization, and reconstitution. In cross-linking polymerization, a fine foam of the polymer is formed, which serves as a bubble coating agent and colloidal stabilizer, resulting from the vigorous stirring of a polymeric solution. In the case of emulsion solvent evaporation, there are two solutions utilized in the production of microbubbles. In atomization and reconstitution, porous spheres are created by atomising a surfactant solution into a hot gas. They are encapsulated in primary modifier gas. After the addition of the second gas or gas osmotic agent, the package is placed into a vial and sealed after reconstituting with sterile saline solution.
RESULTS: Microbubble-based drug delivery is an innovative approach in the field of drug delivery that utilizes microbubbles, which are tiny gas-filled bubbles, act as carriers for therapeutic agents. These microbubbles can be loaded with drugs, imaging agents, or genes and then guided to specific target sites.
CONCLUSION: The potential utility of microbubbles in biomedical applications is continually growing as novel formulations and methods. The versatility of microbubbles allows for customization, tailoring the delivery system to various medical applications, including cancer therapy, cardiovascular treatments, and gene therapy.

Matched MeSH terms: Ultrasonography/methods
Fulltext Classification of Human Daily Activities Using Ensemble Methods Based on Smartphone Inertial Sensors

Ku Abd Rahim KN, Elamvazuthi I, Izhar LI, Capi G

Sensors (Basel), 2018 Nov 26;18(12).
PMID: 30486242 DOI: 10.3390/s18124132

Increasing interest in analyzing human gait using various wearable sensors, which is known as Human Activity Recognition (HAR), can be found in recent research. Sensors such as accelerometers and gyroscopes are widely used in HAR. Recently, high interest has been shown in the use of wearable sensors in numerous applications such as rehabilitation, computer games, animation, filmmaking, and biomechanics. In this paper, classification of human daily activities using Ensemble Methods based on data acquired from smartphone inertial sensors involving about 30 subjects with six different activities is discussed. The six daily activities are walking, walking upstairs, walking downstairs, sitting, standing and lying. It involved three stages of activity recognition; namely, data signal processing (filtering and segmentation), feature extraction and classification. Five types of ensemble classifiers utilized are Bagging, Adaboost, Rotation forest, Ensembles of nested dichotomies (END) and Random subspace. These ensemble classifiers employed Support vector machine (SVM) and Random forest (RF) as the base learners of the ensemble classifiers. The data classification is evaluated with the holdout and 10-fold cross-validation evaluation methods. The performance of each human daily activity was measured in terms of precision, recall, F-measure, and receiver operating characteristic (ROC) curve. In addition, the performance is also measured based on the comparison of overall accuracy rate of classification between different ensemble classifiers and base learners. It was observed that overall, SVM produced better accuracy rate with 99.22% compared to RF with 97.91% based on a random subspace ensemble classifier.

Matched MeSH terms: Biosensing Techniques/methods*
Recent trends and advancement in metal oxide nanoparticles for the degradation of dyes: synthesis, mechanism, types and its application

Senthil Rathi B, Ewe LS, S S, S S, Yew WK, R B, et al.

Nanotoxicology, 2024 May;18(3):272-298.
PMID: 38821108 DOI: 10.1080/17435390.2024.2349304

Synthetic dyes play a crucial role in our daily lives, especially in clothing, leather accessories, and furniture manufacturing. Unfortunately, these potentially carcinogenic substances are significantly impacting our water systems due to their widespread use. Dyes from various sources pose a serious environmental threat owing to their persistence and toxicity. Regulations underscore the urgency in addressing this problem. In response to this challenge, metal oxide nanoparticles such as titanium dioxide (TiO2), zinc oxide (ZnO), and iron oxide (Fe3O4) have emerged as intriguing options for dye degradation due to their unique characteristics and production methods. This paper aims to explore the types of nanoparticles suitable for dye degradation, various synthesis methods, and the properties of nanoparticles. The study elaborates on the photocatalytic and adsorption-desorption activities of metal oxide nanoparticles, elucidating their role in dye degradation and their application potential. Factors influencing degradation, including nanoparticle properties and environmental conditions, are discussed. Furthermore, the paper provides relevant case studies, practical applications in water treatment, and effluent treatment specifically in the textile sector. Challenges such as agglomeration, toxicity concerns, and cost-effectiveness are acknowledged. Future advancements in nanomaterial synthesis, their integration with other materials, and their impact on environmental regulations are potential areas for development. In conclusion, metal oxide nanoparticles possess immense potential in reducing dye pollution, and further research and development are essential to define their role in long-term environmental management.

Matched MeSH terms: Water Purification/methods
Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus

Idris NF, Ismail MA, Jaya MIM, Ibrahim AO, Abulfaraj AW, Binzagr F

PLoS One, 2024;19(5):e0302595.
PMID: 38718024 DOI: 10.1371/journal.pone.0302595

Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient Egypt. The disease is a chronic metabolic disorder that heavily burdens healthcare providers worldwide due to the steady increment of patients yearly. Worryingly, diabetes affects not only the aging population but also children. It is prevalent to control this problem, as diabetes can lead to many health complications. As evolution happens, humankind starts integrating computer technology with the healthcare system. The utilization of artificial intelligence assists healthcare to be more efficient in diagnosing diabetes patients, better healthcare delivery, and more patient eccentric. Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. Hence, this study opts to investigate the potential of stacking ensembles. The aim of this study is to reduce the high complexity inherent in stacking, as this problem contributes to longer training time and reduces the outliers in the diabetes data to improve the classification performance. In addressing this concern, a novel machine learning method called the Stacking Recursive Feature Elimination-Isolation Forest was introduced for diabetes prediction. The application of stacking with Recursive Feature Elimination is to design an efficient model for diabetes diagnosis while using fewer features as resources. This method also incorporates the utilization of Isolation Forest as an outlier removal method. The study uses accuracy, precision, recall, F1 measure, training time, and standard deviation metrics to identify the classification performances. The proposed method acquired an accuracy of 79.077% for PIMA Indians Diabetes and 97.446% for the Diabetes Prediction dataset, outperforming many existing methods and demonstrating effectiveness in the diabetes domain.

Matched MeSH terms: Data Mining/methods
UMobileNetV2 model for semantic segmentation of gastrointestinal tract in MRI scans

Sharma N, Gupta S, Gupta D, Gupta P, Juneja S, Shah A, et al.

PLoS One, 2024;19(5):e0302880.
PMID: 38718092 DOI: 10.1371/journal.pone.0302880

Gastrointestinal (GI) cancer is leading general tumour in the Gastrointestinal tract, which is fourth significant reason of tumour death in men and women. The common cure for GI cancer is radiation treatment, which contains directing a high-energy X-ray beam onto the tumor while avoiding healthy organs. To provide high dosages of X-rays, a system needs for accurately segmenting the GI tract organs. The study presents a UMobileNetV2 model for semantic segmentation of small and large intestine and stomach in MRI images of the GI tract. The model uses MobileNetV2 as an encoder in the contraction path and UNet layers as a decoder in the expansion path. The UW-Madison database, which contains MRI scans from 85 patients and 38,496 images, is used for evaluation. This automated technology has the capability to enhance the pace of cancer therapy by aiding the radio oncologist in the process of segmenting the organs of the GI tract. The UMobileNetV2 model is compared to three transfer learning models: Xception, ResNet 101, and NASNet mobile, which are used as encoders in UNet architecture. The model is analyzed using three distinct optimizers, i.e., Adam, RMS, and SGD. The UMobileNetV2 model with the combination of Adam optimizer outperforms all other transfer learning models. It obtains a dice coefficient of 0.8984, an IoU of 0.8697, and a validation loss of 0.1310, proving its ability to reliably segment the stomach and intestines in MRI images of gastrointestinal cancer patients.

Matched MeSH terms: Image Processing, Computer-Assisted/methods
Radiological impact of 226Ra, 232Th and 40K in fodders from Penang, Malaysia

Alsaffar MS, Kabir NA

Appl Radiat Isot, 2024 Sep;211:111413.
PMID: 38944898 DOI: 10.1016/j.apradiso.2024.111413

The plant acts as an important route for the transfer of radionuclides from the soil to animals, leading to the transfer of radiation to human food products such as beef and milk. Therefore, the level of radioactivity in fodder plays a crucial role in deciding whether cattle may be allowed to graze in a certain area. In this study, the activities of 226Ra, 232Th and 40K were measured via gamma-ray spectrometry on different fodder samples, including napier leaves, rice straw, corn stalks, guinea grass, mixed pasture, palm oil leaves and palm kernel collected from Penang, Malaysia. Theoretical calculations were also conducted to estimate the levels of these radionuclides in caw's products (beef and milk), as well as their potential radiological impact on local consumers. On average, the annual effective dose due to ingestion of radionuclides in milk was 11.39 μSv y-1, whereas in beef it was 5.63 μSv y-1. These values are significantly lower than the worldwide average of 290 μSv y-1. Research confirmed that farmers' usage of the aforementioned feeds did not cause any radiation-related health risks.

Matched MeSH terms: Radiation Monitoring/methods
Fully Endoscopic Retrosigmoid Approach for Cerebellopontine Angle Tumors

Saied M, Najibullah M, Shabbir Z, Saleem A, Ali A, Azab WA

Adv Tech Stand Neurosurg, 2024;52:229-244.
PMID: 39017797 DOI: 10.1007/978-3-031-61925-0_16

BACKGROUND: Fully endoscopic or endoscope-controlled approaches are essentially keyhole approaches in which rigid endoscopes are the sole visualization tools used during the whole procedure. At the early attempts of endoscope-assisted cranial surgery, it was noted that rigid endoscopes enabled overcoming the problem of suboptimal visualization when small exposures are used. The technical specifications and design of the currently available rigid endoscopes are associated with a group of unique features that define the endoscopic view and lay the basis for its superiority over the microscopic view during brain surgery. Fully endoscopic retrosigmoid approach for cerebellopontine angle tumors is a minimally invasive approach that is not routinely practiced by neurosurgeons, with few series published so far. Unfamiliarity with the technique, steep learning curve, and concerns about inadequate exposure, neurovascular injury, and decreased visibility may explain this fact. In this chapter we elaborate on the surgical technique and nuances of the fully endoscopic retrosigmoid approach and present an overview of the published series.
METHODS: From a prospective database of endoscopic procedures maintained by the senior author, clinical data, imaging studies, operative charts, and videos of cases undergoing fully endoscopic retrosigmoid approach for cerebellopontine angle tumors were retrieved and analyzed. The pertinent literature was also reviewed.
RESULTS: The surgical technique of the fully endoscopic retrosigmoid approach was formulated.
CONCLUSION: The endoscopic technique has many advantages over the conventional procedures. In our hands, the technique has proven to be feasible, efficient, and minimally invasive with excellent results.

Matched MeSH terms: Neuroendoscopy/methods
Colorimetric strategies applicable for loop-mediated isothermal amplification

Saifuddin SA, Rashid R, Nor Azmi NJ, Mohamad S

J Microbiol Methods, 2024 Aug;223:106981.
PMID: 38945305 DOI: 10.1016/j.mimet.2024.106981

In recent years, loop-mediated isothermal amplification (LAMP) has gained popularity for detecting various pathogen-specific genes due to its superior sensitivity and specificity compared to conventional polymerase chain reaction (PCR). The simplicity and flexibility of naked-eye detection of the amplicon make LAMP an ideal rapid and straightforward diagnostic tool, especially in resource-limited laboratories. Colorimetric detection is one of the simplest and most straightforward among all detection methods. This review will explore various colorimetric dyes used in LAMP techniques, examining their reaction mechanisms, advantages, limitations and latest applications.

Matched MeSH terms: Polymerase Chain Reaction/methods
A premium for positive social interest and attractive voices in the acceptability of unfair offers? An ERP study

Yuan Y, Shang J, Gao C, Sommer W, Li W

Eur J Neurosci, 2024 Jul;60(2):4078-4094.
PMID: 38777332 DOI: 10.1111/ejn.16422

Although the attractiveness of voices plays an important role in social interactions, it is unclear how voice attractiveness and social interest influence social decision-making. Here, we combined the ultimatum game with recording event-related brain potentials (ERPs) and examined the effect of attractive versus unattractive voices of the proposers, expressing positive versus negative social interest ("I like you" vs. "I don't like you"), on the acceptance of the proposal. Overall, fair offers were accepted at significantly higher rates than unfair offers, and high voice attractiveness increased acceptance rates for all proposals. In ERPs in response to the voices, their attractiveness and expressed social interests yielded early additive effects in the N1 component, followed by interactions in the subsequent P2, P3 and N400 components. More importantly, unfair offers elicited a larger Medial Frontal Negativity (MFN) than fair offers but only when the proposer's voice was unattractive or when the voice carried positive social interest. These results suggest that both voice attractiveness and social interest moderate social decision-making and there is a similar "beauty premium" for voices as for faces.

Matched MeSH terms: Electroencephalography/methods
Fulltext Classification of Motor Functions from Electroencephalogram (EEG) Signals Based on an Integrated Method Comprised of Common Spatial Pattern and Wavelet Transform Framework

Yahya N, Musa H, Ong ZY, Elamvazuthi I

Sensors (Basel), 2019 Nov 08;19(22).
PMID: 31717412 DOI: 10.3390/s19224878

In this work, an algorithm for the classification of six motor functions from an electroencephalogram (EEG) signal that combines a common spatial pattern (CSP) filter and a continuous wavelet transform (CWT), is investigated. The EEG data comprise six grasp-and-lift events, which are used to investigate the potential of using EEG as input signals with brain computer interface devices for controlling prosthetic devices for upper limb movement. Selected EEG channels are the ones located over the motor cortex, C3, Cz and C4, as well as at the parietal region, P3, Pz and P4. In general, the proposed algorithm includes three main stages, band pass filtering, CSP filtering, and wavelet transform and training on GoogLeNet for feature extraction, feature learning and classification. The band pass filtering is performed to select the EEG signal in the band of 7 Hz to 30 Hz while eliminating artifacts related to eye blink, heartbeat and muscle movement. The CSP filtering is applied on two-class EEG signals that will result in maximizing the power difference between the two-class dataset. Since CSP is mathematically developed for two-class events, the extension to the multiclass paradigm is achieved by using the approach of one class versus all other classes. Subsequently, continuous wavelet transform is used to convert the band pass and CSP filtered signals from selected electrodes to scalograms which are then converted to images in grayscale format. The three scalograms from the motor cortex regions and the parietal region are then combined to form two sets of RGB images. Next, these RGB images become the input to GoogLeNet for classification of the motor EEG signals. The performance of the proposed classification algorithm is evaluated in terms of precision, sensitivity, specificity, accuracy with average values of 94.8%, 93.5%, 94.7%, 94.1%, respectively, and average area under the receiver operating characteristic (ROC) curve equal to 0.985. These results indicate a good performance of the proposed algorithm in classifying grasp-and-lift events from EEG signals.

Matched MeSH terms: Electroencephalography/methods*
Advances in artificial intelligence for drug delivery and development: A comprehensive review

Gholap AD, Uddin MJ, Faiyazuddin M, Omri A, Gowri S, Khalid M

Comput Biol Med, 2024 Aug;178:108702.
PMID: 38878397 DOI: 10.1016/j.compbiomed.2024.108702

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.

Matched MeSH terms: Drug Discovery/methods
Stringent criteria needed for germline genome editing of human IVF embryos

Chin AHB, Nguma JB, Ahmad MF

J Assist Reprod Genet, 2024 Jul;41(7):1727-1731.
PMID: 38695986 DOI: 10.1007/s10815-024-03125-6

Germline genome editing of IVF embryos is controversial because it is not directly health or lifesaving but is intended to prevent genetic diseases in yet-unborn future offspring. The following criteria are thus proposed for future clinical trials: (i) Due to medical risks, there should be cautious and judicious application while avoiding any non-essential usage, with rigorous patient counseling. (ii) Genome editing should only be performed on the entire batch of IVF embryos without initial PGT screening if all of them are expected to be affected by genetic disease. (iii) When there is a fair chance that some IVF embryos will not be affected by genetic diseases, initial PGT screening must be performed to identify unaffected embryos for transfer. (iv) IVF embryos with carrier status should not undergo germline genome editing. (v) If patients fail to conceive after the transfer of unaffected embryos, they should undergo another fresh IVF cycle rather than opt for genome editing of their remaining affected embryos. (vi) Only if the patient is unable to produce any more unaffected embryos in a fresh IVF cycle due to advanced maternal age or diminished ovarian reserves, can the genome editing of remaining affected embryos be permitted as a last resort.

Matched MeSH terms: Embryo Transfer/methods
Fulltext Heat and mass transfer on MHD squeezing flow of Jeffrey nanofluid in horizontal channel through permeable medium

Mat Noor NA, Shafie S, Admon MA

PLoS One, 2021;16(5):e0250402.
PMID: 33956793 DOI: 10.1371/journal.pone.0250402

The heat and mass transfer on time dependent hydrodynamic squeeze flow of Jeffrey nanofluid across two plates over permeable medium in the slip condition with heat generation/absorption, thermal radiation and chemical reaction are investigated. The impacts of Brownian motion and thermophoresis is examined in the Buongiorno's nanofluid model. Conversion of the governing partial differential equations to the ordinary differential equations is conducted via similarity transformation. The dimensionless equations are solved by imposing numerical method of Keller-box. The outputs are compared with previous reported works in the journals for the validation of the present outputs and found in proper agreement. The behavior of velocity, temperature, and nanoparticles concentration profiles by varying the pertinent parameters are examined. Findings portray that the acceleration of the velocity profile and the wall shear stress is due to the squeezing of plates. Furthermore, the velocity, temperature and concentration profile decline with boost in Hartmann number and ratio of relaxation to retardation times. It is discovered that the rate of heat transfer and temperature profile increase when viscous dissipation, thermophoresis and heat source/sink rises. In contrast, the increment of thermal radiation reduces the temperature and enhances the heat transfer rate. Besides, the mass transfer rate decelerates for increasing Brownian motion in nanofluid, while it elevates when chemical reaction and thermophoresis increases.

Matched MeSH terms: Nanotechnology/methods
Fulltext Preliminary Evaluation of Supercritical Carbon Dioxide Extracted Dabai Pulp Oleoresin as a New Alternative Fat

Kadir NAAA, Azlan A, Abas F, Ismail IS

Molecules, 2021 Sep 13;26(18).
PMID: 34577016 DOI: 10.3390/molecules26185545

There has been growing interest among food scientists in producing a toxin-free fat as an end product with varying physical or nutritional properties of interest to the food industry. Oleoresin is a rich source of bioactive compounds which consumers can easily add to a large variety of food. Dabai (Canarium odontophyllum) pulp oleoresin (DPL) was extracted using supercritical carbon dioxide (SC-CO2) extraction, a green extraction technology. This study investigates the quality of SC-CO2 extracted DPL in discovering its potential as a new alternative fat. The extraction experiment was carried out at a pressure of 40 MPa and a temperature of 40 °C. DPL is a saturated fatty acid (SFA)-rich fat due to its high SFA composition (47.72 ± 0.01%). In addition, the low content of peroxide value (PV) (5.60 ± 0.09 mEq/kg) and free fatty acids (FFA) (3.40 ± 0.03%) indicate the quality and stability of DPL for various applications besides food consumption. DPL also has a low slip melting point (SMP) (20.20 ± 0.03 °C), and HPLC-FID revealed that DPL contained 0.13 ± 0.02 mg/100 g of vitamin E (α-tocopherol), indicating its potential application as a solid fat with a bioactive compound. This present work demonstrates the possible prospect of DPL in the formulation of end products for food industries.

Matched MeSH terms: Chromatography, Supercritical Fluid/methods
Fulltext Exceptional performance with minimal data using a generative adversarial network for alzheimer's disease classification

Wong PC, Abdullah SS, Shapiai MI

Sci Rep, 2024 Jul 24;14(1):17037.
PMID: 39043757 DOI: 10.1038/s41598-024-66874-5

The classification of Alzheimer's disease (AD) using deep learning models is hindered by the limited availability of data. Medical image datasets are scarce due to stringent regulations on patient privacy, preventing their widespread use in research. Moreover, although open-access databases such as the Open Access Series of Imaging Studies (OASIS) are available publicly for providing medical image data for research, they often suffer from imbalanced classes. Thus, to address the issue of insufficient data, this study proposes the integration of a generative adversarial network (GAN) that can achieve comparable accuracy with a reduced data requirement. GANs are unsupervised deep learning networks commonly used for data augmentation that generate high-quality synthetic data to overcome data scarcity. Experimental data from the OASIS database are used in this research to train the GAN model in generating synthetic MRI data before being included in a pretrained convolutional neural network (CNN) model for multistage AD classification. As a result, this study has demonstrated that a multistage AD classification accuracy above 80% can be achieved even with a reduced dataset. The exceptional performance of GANs positions them as a solution for overcoming the challenge of insufficient data in AD classification.

Matched MeSH terms: Magnetic Resonance Imaging/methods
Towards a better future for DNA barcoding: Evaluating monophyly- and distance-based species identification using COI gene fragments of Dacini fruit flies

Doorenweerd C, San Jose M, Leblanc L, Barr N, Geib SM, Chung AYC, et al.

Mol Ecol Resour, 2024 Aug;24(6):e13987.
PMID: 38956928 DOI: 10.1111/1755-0998.13987

The utility of a universal DNA 'barcode' fragment (658 base pairs of the Cytochrome C Oxidase I [COI] gene) has been established as a useful tool for species identification, and widely criticized as one for understanding the evolutionary history of a group. Large amounts of COI sequence data have been produced that hold promise for rapid species identification, for example, for biosecurity. The fruit fly tribe Dacini holds about a thousand species, of which 80 are pests of economic concern. We generated a COI reference library for 265 species of Dacini containing 5601 sequences that span most of the COI gene using circular consensus sequencing. We compared distance metrics versus monophyly assessments for species identification and although we found a 'soft' barcode gap around 2% pairwise distance, the exceptions to this rule dictate that a monophyly assessment is the only reliable method for species identification. We found that all fragments regularly used for Dacini fruit fly identification >450 base pairs long provide similar resolution. 11.3% of the species in our dataset were non-monophyletic in a COI tree, which is mostly due to species complexes. We conclude with recommendations for the future generation and use of COI libraries. We revise the generic assignment of Dacus transversus stat. rev. Hardy 1982, and Dacus perpusillus stat. rev. Drew 1971 and we establish Dacus maculipterus White 1998 syn. nov. as a junior synonym of Dacus satanas Liang et al. 1993.

Matched MeSH terms: Sequence Analysis, DNA/methods
Evaluating the properties that affect the quality of the charcoal product, determining the limits of toxic emissions during combustion, and studying their impact on human health

Alzahrani A, Hassan MA, Alsubaie S

Environ Geochem Health, 2024 Jul 09;46(8):295.
PMID: 38980526 DOI: 10.1007/s10653-024-02065-5

This research focuses on examining the potential impact of charcoal briquettes and lumps on human health due to the emissions they release, and verifying their quality standards. Quality assessment was conducted using a device capable of measuring toxic gases to identify contaminants from various sources such as biomass, synthetic resins, coal, metals, and mineral matter. Toxicity assessments were carried out on five types of briquettes and two varieties of lump charcoal. All charcoal samples were subjected to elemental analysis (SEM/EDAX), including the examination of Ca, Al, Cr, V, Cu, Fe, S, Sr, Si, Ba, Pb, P, Mn, Rb, K, Ti, and Zn. The results showed that burning lump charcoal had toxicity indexes ranging from 2.5 to 5, primarily due to NOx emissions. Briquettes, on the other hand, exhibited higher toxicity indices between 3.5 and 6.0, with CO2 being the main contributor to toxicity. The average 24-h CO content of all charcoal samples exceeded the World Health Organization's 24-h Air Quality Guideline of 6.34 ppm, with a measurement of 37 ppm. The data indicates that most of the products tested did not meet the prevailing quality standard (EN 1860-2:2005 (E) in Appliances, solid fuels and firelighters for barbecuing-Part 2: Barbecue charcoal and barbecue charcoal briquettes-Requirements and test method, 2005), which specifies a maximum of 1% contaminants, with some products containing as much as 21% impurities. The SEM analysis revealed irregularly shaped grains with an uneven distribution of particles, and the average particle size distribution is quite broad at 5 μm. Malaysia Charcoal had the highest calorific value at 32.80 MJ/Kg, with the value being influenced by the fixed carbon content-higher carbon content resulting in a higher calorific value.

Matched MeSH terms: Environmental Monitoring/methods
Fulltext Diagnostic performance of Xpert MTB/RIF ultra in detecting Mycobacterium tuberculosis and Rifampicin Resistance in AFB Smear-negative Pulmonary and Extrapulmonary Tuberculosis samples in Malaysia

Noor AM, Ghazali SM, Bakar ZA, Ruzan IN

Diagn Microbiol Infect Dis, 2024 Jun;109(2):116230.
PMID: 38507965 DOI: 10.1016/j.diagmicrobio.2024.116230

Rapid and highly accurate diagnostic tools are critically needed to diagnose Mycobacterium tuberculosis and rifampicin resistance in AFB smear-negative samples. In this study, we evaluated the diagnostic performance of Xpert MTB/RIF Ultra (Ultra) as a rapid test to diagnose tuberculosis in smear-negative cases in Malaysia. A retrospective study of 1960 smear-negative pulmonary and extrapulmonary samples obtained from patients was conducted. Culture was used as the reference standard for the study. The overall sensitivity and specificity of Ultra on the tested samples were 88.7 % and 77.2 %, respectively, while the PPV was 32.3 % and the NPV was 98.2 %. Ultra showed slightly higher sensitivity in pulmonary (89.9 %) compared to extrapulmonary samples (86.1 %). The overall accuracy of Ultra was 78.5 % (kappa=0.37; 95 %CI: 0.32,0.42). Ultra showed good diagnostic accuracy for detecting MTB and rifampicin resistance in various AFB smear-negative samples. Ultra also had excellent capability in rifampicin resistance detection.

Matched MeSH terms: Molecular Diagnostic Techniques/methods

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