Displaying publications 1161 - 1180 of 9863 in total

Abstract:
Sort:
  1. Qin D, Gong Q, Li X, Gao Y, Gopinath SCB, Chen Y, et al.
    Biotechnol Appl Biochem, 2023 Apr;70(2):553-559.
    PMID: 35725894 DOI: 10.1002/bab.2377
    Mycoplasma pneumoniae is a highly infectious bacterium and the major cause of pneumonia especially in school-going children. Mycoplasma pneumoniae affects the respiratory tract, and 25% of patients experience health-related problems. It is important to have a suitable method to detect M. pneumoniae, and gold nanoparticle (GNP)-based colorimetric biosensing was used in this study to identify the specific target DNA for M. pneumoniae. The color of GNPs changes due to negatively charged GNPs in the presence of positively charged monovalent (Na+ ) ions from NaCl. This condition is reversed in the presence of a single-stranded oligonucleotide, as it attracts GNPs but not in the presence of double-stranded DNA. Single standard capture DNA was mixed with optimal target DNA that cannot be adsorbed by GNPs; under this condition, GNPs are not stabilized and aggregate at high ionic strength (from 100 mM). Without capture DNA, the GNPs that were stabilized by capture DNA (from 1 μM) became more stable under high ionic conditions and retaining their red color. The GNPs turned blue in the presence of target DNA at concentrations of 1 pM, and the GNPs retained a red color when there was no target in the solution. This method is useful for the simple, easy, and accurate identification of M. pneumoniae target DNA at higher discrimination and without involving sophisticated equipment, and this method provides a diagnostic for M. pneumoniae.
    Matched MeSH terms: Colorimetry/methods
  2. FinNie O, Aye SA, Krishnappa P, Ravindran R
    Med J Malaysia, 2023 Mar;78(2):202-206.
    PMID: 36988531
    INTRODUCTION: The purpose of tissue processing is to fix the tissue in a solid medium toenable thin sections. Conventional method of tissue processing is the standardized method of tissue processing which has been used for more than 10 decades. However, the conventional method is time-consuming, and the overall turnaround time for the histopathology report is at least two days. The objective of this study is to identify the protocol for tissue processing procedure using domestic microwave oven. To determine the tissue processing time when using domestic microwave oven. To compare the morphological quality of tissue slides made by domestic microwave oven and conventional method using automated tissue processor.

    MATRIALS AND METHODS: The conventional protocol and three microwave protocols of tissue processing were used in this study. A pilot study was done prior to the real run to determine the baseline timing for microwave protocol. The baseline timing was fixed at 2 minutes,30 minutes,5 minutes and 25 minutes. The processing time of the microwave protocol was adjusted from 62 minutes to 70 minutes to 77 minutes by increasing the dehydration and wax impregnation time while the time for tissue fixation and clearing remain the same throughout all the microwave protocols.

    RESULTS: The group 2 microwave protocol produced the sections that is closely comparable to group 1 conventional protocol. The morphological quality of histopathology slides is best observed when the processing time of microwave protocol is 62 minutes.

    CONCLUSION: The most appropriate microwave protocol for tissue processing is group 2 as the morphological quality of histopathology slides are more superior than that of group 1 with an overall percentage of 80% of satisfactory slides in group 2 and 76.68% in group 1.

    Matched MeSH terms: Tissue Fixation/methods
  3. Abisha S, Mutawa AM, Murugappan M, Krishnan S
    PLoS One, 2023;18(4):e0284021.
    PMID: 37018344 DOI: 10.1371/journal.pone.0284021
    Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting the possibility of an accurate diagnosis. This paper proposes an innovative method for identifying and classifying infected brinjal leaves using Deep Convolutional Neural Networks (DCNN) and Radial Basis Feed Forward Neural Networks (RBFNN). We collected 1100 images of brinjal leaf disease that were caused by five different species (Pseudomonas solanacearum, Cercospora solani, Alternaria melongenea, Pythium aphanidermatum, and Tobacco Mosaic Virus) and 400 images of healthy leaves from India's agricultural form. First, the original plant leaf is preprocessed by a Gaussian filter to reduce the noise and improve the quality of the image through image enhancement. A segmentation method based on expectation and maximization (EM) is then utilized to segment the leaf's-diseased regions. Next, the discrete Shearlet transform is used to extract the main features of the images such as texture, color, and structure, which are then merged to produce vectors. Lastly, DCNN and RBFNN are used to classify brinjal leaves based on their disease types. The DCNN achieved a mean accuracy of 93.30% (with fusion) and 76.70% (without fusion) compared to the RBFNN (82%-without fusion, 87%-with fusion) in classifying leaf diseases.
    Matched MeSH terms: Image Processing, Computer-Assisted/methods
  4. Canivet CM, Zheng MH, Qadri S, Vonghia L, Chuah KH, Costentin C, et al.
    Clin Gastroenterol Hepatol, 2023 Nov;21(12):3097-3106.e10.
    PMID: 37031715 DOI: 10.1016/j.cgh.2023.03.032
    BACKGROUND & AIMS: Drug development in nonalcoholic steatohepatitis (NASH) is hampered by a high screening failure rate that reaches 60% to 80% in therapeutic trials, mainly because of the absence of fibrotic NASH on baseline liver histology. MACK-3, a blood test including 3 biomarkers (aspartate aminotransferase, homeostasis model assessment, and cytokeratin 18), recently was developed for the noninvasive diagnosis of fibrotic NASH. We aimed to validate the diagnostic accuracy of this noninvasive test in an international multicenter study.

    METHODS: A total of 1924 patients with biopsy-proven nonalcoholic fatty liver disease from 10 centers in Asia, Australia, and Europe were included. The blood test MACK-3 was calculated for all patients. FibroScan-aspartate aminotransferase score (FAST), an elastography-based test for fibrotic NASH, also was available in a subset of 655 patients. Fibrotic NASH was defined as the presence of NASH on liver biopsy with a Nonalcoholic Fatty Liver Disease Activity Score of 4 or higher and fibrosis stage of F2 or higher according to the NASH Clinical Research Network scoring system.

    RESULTS: The area under the receiver operating characteristic of MACK-3 for fibrotic NASH was 0.791 (95% CI 0.768-0.814). Sensitivity at the previously published MACK-3 threshold of less than 0.135 was 91% and specificity at a greater than 0.549 threshold was 85%. The MACK-3 area under the receiver operating characteristic was not affected by age, sex, diabetes, or body mass index. MACK-3 and FAST results were well correlated (Spearman correlation coefficient, 0.781; P < .001). Except for an 8% higher rate of patients included in the grey zone, MACK-3 provided similar accuracy to that of FAST. Both tests included 27% of patients in their rule-in zone, with 85% specificity and 35% false positives (screen failure rate).

    CONCLUSIONS: The blood test MACK-3 is an accurate tool to improve patient selection in NASH therapeutic trials.

    Matched MeSH terms: Biopsy/methods
  5. Shivaraja TR, Remli R, Kamal N, Wan Zaidi WA, Chellappan K
    Sensors (Basel), 2023 Mar 31;23(7).
    PMID: 37050713 DOI: 10.3390/s23073654
    Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG's signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments.
    Matched MeSH terms: Electroencephalography/methods
  6. Mohanadas HP, Nair V, Doctor AA, Faudzi AAM, Tucker N, Ismail AF, et al.
    Ann Biomed Eng, 2023 Nov;51(11):2365-2383.
    PMID: 37466879 DOI: 10.1007/s10439-023-03322-x
    Additive Manufacturing is noted for ease of product customization and short production run cost-effectiveness. As our global population approaches 8 billion, additive manufacturing has a future in maintaining and improving average human life expectancy for the same reasons that it has advantaged general manufacturing. In recent years, additive manufacturing has been applied to tissue engineering, regenerative medicine, and drug delivery. Additive Manufacturing combined with tissue engineering and biocompatibility studies offers future opportunities for various complex cardiovascular implants and surgeries. This paper is a comprehensive overview of current technological advancements in additive manufacturing with potential for cardiovascular application. The current limitations and prospects of the technology for cardiovascular applications are explored and evaluated.
    Matched MeSH terms: Tissue Engineering/methods
  7. Alwi AR, Mahat NA, Mohd Salleh F, Ishar SM, Kamaluddin MR, Rashid MRA
    J Forensic Sci, 2023 Nov;68(6):2103-2115.
    PMID: 37646344 DOI: 10.1111/1556-4029.15370
    The onus of proof in criminal cases is beyond any reasonable doubt, and the issue on the lack of complete internal validation data can be manipulated when it comes to justifying the validity and reliability of the X-chromosomal short tandem repeats analysis for court representation. Therefore, this research evaluated the efficiency of the optimized 60% reduced volumes for polymerase chain reaction (PCR) amplification using the Qiagen Investigator® Argus X-12 QS Kit, as well as the capillary electrophoresis (CE) sample preparation for blood samples on Flinder's Technology Associates (FTA) cards. Good-quality DNA profile (3000-12,000 RFU) from the purified blood sample on FTA card (1.2 mm) were obtained using the optimized PCR (10.0 μL of PCR reaction volume and 21 cycles) and CE (9.0 μL Hi-Di™ Formamide and 0.3 μL DNA Size Standard 550 [BTO] and 27 s injection time) conditions. The analytical and stochastic thresholds were 100 and 200 RFU, respectively. Hence, the internal validation data supported the use of the optimized 60% reduced PCR amplification reaction volume of the Qiagen Investigator® Argus X-12 QS Kit as well as the CE sample preparation for producing reliable DNA profiles that comply with the quality assurance standards for forensic DNA testing laboratories, while optimizing the analytical cost.
    Matched MeSH terms: Polymerase Chain Reaction/methods
  8. Zaid SM, Hutagalung FD, Bin Abd Hamid HS, Taresh SM
    PLoS One, 2021;16(8):e0256088.
    PMID: 34388181 DOI: 10.1371/journal.pone.0256088
    BACKGROUNDS: Accurate measurement and suitable strategies facilitate people regulate their sadness in an effective manner. Regulating or mitigating negative emotions, particularly sadness, is crucial mainly because constant negative emotions may lead to psychological disorders, such as depression and anxiety. This paper presents an overview of sadness regulation strategies and related measurement.

    METHOD: Upon adhering to five-step scoping review, this study combed through articles that looked into sadness regulation retrieved from eight databases.

    RESULTS: As a result of reviewing 40 selected articles, 110 strategies were identified to regulate emotions, particularly sadness. Some of the most commonly reported strategies include expressive suppression, cognitive reappraisal, distraction, seeking social or emotional support, and rumination. The four types of measures emerged from the review are self-reported, informant report (parents or peers), open-ended questions, and emotion regulation instructions. Notably, most studies had tested psychometric properties using Cronbach's alpha alone, while only a handful had assessed validity (construct and factorial validity) and reliability (Cronbach's alpha or test-retest) based on responses captured from questionnaire survey.

    CONCLUSION: Several sadness regulation strategies appeared to vary based on gender, age, and use of strategy. Despite the general measurement of emotion regulation, only one measure was developed to measure sadness regulation exclusively for children. Future studies may develop a comprehensive battery of measures to assess sadness regulation using multi-component method.

    Matched MeSH terms: Psychometrics/methods*
  9. Biswas K, Nazir A, Rahman MT, Khandaker MU, Idris AM, Islam J, et al.
    PLoS One, 2022;17(1):e0261427.
    PMID: 35085239 DOI: 10.1371/journal.pone.0261427
    Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO's exploration phase is enhanced, and the SHO's hunting mechanisms are modified with PSO's velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization.
    Matched MeSH terms: Conservation of Energy Resources/methods*
  10. Fijasri NH, Muhammad Asri NA, Mohd Shah MS, Abd Samad MR, Omar N
    Afr J Paediatr Surg, 2023;20(3):245-248.
    PMID: 37470566 DOI: 10.4103/ajps.AJPS_10_21
    Congenital pulmonary airway malformation (CPAM) together with oesophageal atresia and tracheoesophageal fistula (TOF) is a very rare condition in neonates. We presented a case of an infant with Gross type C oesophageal atresia with TOF coexisting with Stocker Type III CPAM in our centre. It is interesting to know that TOF associated with type III CPAM has never been reported in the literature. The child was delivered through caesarean section, and because of respiratory distress post-delivery, endotracheal intubation was carried out immediately. CPAM was diagnosed by a suspicious finding from the initial chest X-ray and the diagnosis was confirmed through computed tomography scan of the chest. The patient was initially stabilised in a neonatal intensive care unit (NICU), and after the successful ligation of fistula and surgical repair of TOF, lung recruitment was started by high flow oscillatory ventilation. The patient recovered well without complications and able to maintain good saturation without oxygen support through the stay in the neonatal unit. Early recognition of this rare association is essential for immediate transfer to NICU, the intervention of any early life-threatening complications, and for vigilant monitoring in the postoperative period.
    Matched MeSH terms: Tomography, X-Ray Computed/methods
  11. Schepaschenko D, Chave J, Phillips OL, Lewis SL, Davies SJ, Réjou-Méchain M, et al.
    Sci Data, 2019 10 10;6(1):198.
    PMID: 31601817 DOI: 10.1038/s41597-019-0196-1
    Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
    Matched MeSH terms: Environmental Monitoring/methods
  12. Husain SF, Chiang SK, Vasu AA, Goh CP, McIntyre RS, Tang TB, et al.
    J Atten Disord, 2023 Nov;27(13):1448-1459.
    PMID: 37341192 DOI: 10.1177/10870547231180111
    OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) provides direct and quantitative assessment of cortical hemodynamic response. It has been used to identify neurophysiological alterations in medication-naïve adults with attention-deficit/hyperactivity disorder (ADHD). Hence, this study aimed to distinguish both medication-naïve and medicated adults with ADHD from healthy controls (HC).

    METHOD: 75 HCs, 75 medication-naïve, and 45 medicated patients took part in this study. fNIRS signals during a verbal fluency task (VFT) were acquired using a 52-channel system and relative oxy-hemoglobin changes in the prefrontal cortex were quantified.

    RESULTS: Prefrontal cortex hemodynamic response was lower in patients than HCs (p ≤ ≤.001). Medication-naïve and medicated patients did not differ in hemodynamic response or symptom severity (p > .05). fNIRS measurements were not associated with any clinical variables (p > .05). 75.8% patients and 76% HCs were correctly classified using hemodynamic response.

    CONCLUSION: fNIRS may be a potential diagnostic tool for adult ADHD. These findings need to be replicated in larger validation studies.

    Matched MeSH terms: Spectroscopy, Near-Infrared/methods
  13. Alhelou Y, Hamdan M, Razali N, Adenan N, Ali J
    BMC Pregnancy Childbirth, 2023 Sep 28;23(1):698.
    PMID: 37770819 DOI: 10.1186/s12884-023-06025-2
    BACKGROUND: Previous studies looked into the connections between pregnancy and the Zona Pellucida (ZP) thickness and Zona Pellucida Thickness Variation (ZPTV), as well as the embryo's radius, circumference, perimeter and global symmetry. However, no research has linked embryo implantation and pregnancy to the percentage of ZP thinning, the reduction in ooplasm volume, and the increase in perivitelline space (PVS) volume. Our objective is to correlate the percentage of ZP thinning, the percentage of ooplasm volume shrinkage and the percentage of PVS increase to the implantation. These data will be used for embryo selection as well as it can be put into a software that will assist embryo selection.

    MATERIALS AND METHODS: Retrospective study included 281 patients, all of them had 2 embryos transferred, 149 patients got pregnant with two gestation sacs and 132 patients did not get pregnant. All of the transferred embryos had the ZP thickness measured several times from time of ICSI till Embryo Transfer (ET), the ooplasm volume was calculated from time of ICSI till two Pronuclei (2PN) fading and the PVS was calculated from the ICSI time till the 2PN fading.

    RESULTS: The first characteristic is the change in the average ZP thickness that decreased by 32.7% + 5.3% at 70 h for the implanted embryos (Group 1) versus 23.6% + 4.8% for non-implanted embryos (Group 2) p = 0.000. The second characteristic is the average reduction in the volume of the ooplasm which is 20.5% + 4.3% in Group 1 versus 15.1% + 5.2% in Group 2, p = 0.000. The third characteristic is the increase in the volume of the PVS which was 38.1% + 7.6% in Group 1 versus 31.6% + 9.7% in Group 2 p = 0.000.

    CONCLUSION: The implanted embryos showed higher percent of ZP thinning, higher percent of ooplasm reduction and higher percent of PVS increase.

    Matched MeSH terms: Embryo Transfer/methods
  14. Jiang C, Zhu Y, Luo Y, Tan CS, Mastrotheodoros S, Costa P, et al.
    BMC Psychol, 2023 Oct 18;11(1):345.
    PMID: 37853499 DOI: 10.1186/s40359-023-01293-1
    BACKGROUND: The 10-item Rosenberg Self-Esteem Scale (RSES) is a widely used tool for individuals to self-report their self-esteem; however, the factorial structures of translated versions of the RSES vary across different languages. This study aimed to validate the Chinese version of the RSES in the Chinese mainland using a longitudinal design.

    METHODS: A group of healthcare university students completed the RSES across three waves: baseline, 1-week follow-up, and 15-week follow-up. A total of 481 valid responses were collected through the three-wave data collection process. Exploratory factor analysis (EFA) was performed on the baseline data to explore the potential factorial structure, while confirmatory factor analysis (CFA) was performed on the follow-up data to determine the best-fit model. Additionally, the cross-sectional and longitudinal measurement invariances were tested to assess the measurement properties of the RSES for different groups, such as gender and age, as well as across different time points. Convergent validity was assessed against the Self-Rated Health Questionnaire (SRHQ) using Spearman's correlation. Internal consistency was examined using Cronbach's alpha and McDonald's omega coefficients, while test-retest reliability was assessed using intraclass correlation coefficient.

    RESULTS: The results of EFA revealed that Items 5, 8, and 9 had inadequate or cross-factor loadings, leading to their removal from further analysis. Analysis of the remaining seven items using EFA suggested a two-factor solution. A comparison of several potential models for the 10-item and 7-item RSES using CFA showed a preference for the 7-item form (RSES-7) with two factors. Furthermore, the RSES-7 exhibited strict invariance across different groups and time points, indicating its stability and consistency. The RSES-7 also demonstrated adequate convergent validity, internal consistency, and test-retest reliability, which further supported its robustness as a measure of self-esteem.

    CONCLUSIONS: The findings suggest that the RSES-7 is a psychometrically sound and brief self-report scale for measuring self-esteem in the Chinese context. More studies are warranted to further verify its usability.

    Matched MeSH terms: Psychometrics/methods
  15. Zango ZU, Ethiraj B, Al-Mubaddel FS, Alam MM, Lawal MA, Kadir HA, et al.
    Environ Res, 2023 Aug 15;231(Pt 2):116102.
    PMID: 37196688 DOI: 10.1016/j.envres.2023.116102
    Perfluoroalkyl carboxylic acids (PFCAs) are sub-class of perfluoroalkyl substances commonly detected in water matrices. They are persistent in the environment, hence highly toxic to living organisms. Their occurrence at trace amount, complex nature and prone to matrix interference make their extraction and detection a challenge. This study consolidates current advancements in solid-phase extraction (SPE) techniques for the trace-level analysis of PFCAs from water matrices. The advantages of the methods in terms of ease of applications, low-cost, robustness, low solvents consumption, high pre-concentration factors, better extraction efficiency, good selectivity and recovery of the analytes have been emphasized. The article also demonstrated effectiveness of some porous materials for the adsorptive removal of the PFCAs from the water matrices. Mechanisms of the SPE/adsorption techniques have been discussed. The success and limitations of the processes have been elucidated.
    Matched MeSH terms: Solid Phase Extraction/methods
  16. Liew WC, Muhamad II, Chew JW, Karim KJA
    Int J Biol Macromol, 2023 Dec 31;253(Pt 6):127288.
    PMID: 37813215 DOI: 10.1016/j.ijbiomac.2023.127288
    Incorporating two different nanoparticles in nanocomposite films is promising as their synergistic effects could significantly enhance polymer performance. Our previous work conferred the remarkable antimicrobial (AM) properties of the polylactic acid (PLA)-based film using optimal formulations of synergistic graphene oxide (GO)/zinc oxide (ZnO) nanocomposites. This study further explores the release profile of GO/ZnO nanocomposite and their impact on the antimicrobial properties. A fixed 1.11 wt% GO and different ZnO concentrations were well dispersed in the PLA matrix. Increasing ZnO concentrations tended to increase agglomeration, as evident in rougher surfaces. Agglomeration inhibited water penetration, leading to a significant reduction in water permeability (46.3 %), moisture content (31.6 %) but an improvement in Young's Modulus (52.6 %). The overall and specific migration of GO/ZnO nanocomposites was found to be within acceptable limits. It is inferred that the release of Zn2+ ions followed pseudo-Fickian behavior with an initial burst effect. AM film with the highest concentration of ZnO (1.25 wt%) exhibited the highest inhibition rate against Escherichia coli (68.0 %), Bacillus cereus (66.5 %), Saccharomyces cerevisiae (70.9 %). Results suggest that GO/ZnO nanocomposites with optimal ZnO concentrations have the potential to serve as promising antimicrobial food packaging materials, offering enhanced barrier, antimicrobial properties and a controlled release system.
    Matched MeSH terms: Food Packaging/methods
  17. Shiammala PN, Duraimutharasan NKB, Vaseeharan B, Alothaim AS, Al-Malki ES, Snekaa B, et al.
    Methods, 2023 Nov;219:82-94.
    PMID: 37778659 DOI: 10.1016/j.ymeth.2023.09.010
    Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.
    Matched MeSH terms: Drug Discovery/methods
  18. Erdogan A, Rao SS, Gulley D, Jacobs C, Lee YY, Badger C
    Neurogastroenterol Motil, 2015 Aug;27(8):1192-3.
    PMID: 26220649 DOI: 10.1111/nmo.12603
    Matched MeSH terms: Breath Tests/methods*
  19. Lin GSS, Chin YJ, Chong RS, Baharin F, Syed Saadun Tarek Wafa SWW, Dziaruddin N
    BMC Oral Health, 2023 Jul 05;23(1):452.
    PMID: 37407955 DOI: 10.1186/s12903-023-03130-8
    BACKGROUND: Paediatric dentistry is a branch of dental specialty that focuses on dental care for children from infancy through adolescence. However, there is no standardised national undergraduate paediatric dental curriculum in Malaysia. The present study aimed to identify relevant topics for undergraduate paediatric dental curricula and to determine the appropriate cognitive and psychomotor levels for each topic based on the consensus among paediatric dental experts.

    METHODS: Potential relevant undergraduate paediatric dentistry topics were initially drafted and revised according to the revised national competency statement. The final draft included 65 topics clustered under 18 domains. A fuzzy Delphi method was used and experts who fulfilled the inclusion criteria were invited to anonymously ranked the importance of relevant topics using a five-point Likert scale and proposed suitable cognitive and psychomotor levels for each topic. Fuzzy evaluation was then performed, and experts were considered to have reached a consensus if the following three conditions were achieved: (a). the difference between the average and expert rating data was ≤ 0.2; (b). the average expert consensus was ˃70%; and (c). the average fuzzy number was ≥ 0.5. Subsequently, the mean ratings were used to determine the cognitive and psychomotor levels.

    RESULTS: 20 experts participated in the survey. 64 out of 65 paediatric dentistry topics were deemed acceptable. The average fuzzy number ranged from 0.36 to 0.85, while the average Likert score ranged from 3.05 to 5.00. The topic "Dental amalgam" was rejected based on expert consensus since the average fuzzy number was 0.36. The most significant topic was "Pit and fissure sealant", followed by "Preventive advice", "Early childhood caries", "Dental caries in children & adolescent", "Management of dental caries in paediatric patients", and "Consent" which were equally ranked as the second most important topics. According to Bloom's and Simpson's taxonomies, most of the paediatric dentistry topics were rated adequate for undergraduate students at the cognitive level of "Apply" (C3) and a psychomotor level of "Guided response" (P3).

    CONCLUSION: The current study successfully identified relevant undergraduate paediatric dentistry topics using the fuzzy Delphi method, which can facilitate future educators to improve existing Malaysian undergraduate paediatric dental curricula.

    Matched MeSH terms: Education, Dental/methods
  20. Salih SQ, Alsewari AA, Wahab HA, Mohammed MKA, Rashid TA, Das D, et al.
    PLoS One, 2023;18(7):e0288044.
    PMID: 37406006 DOI: 10.1371/journal.pone.0288044
    The retrieval of important information from a dataset requires applying a special data mining technique known as data clustering (DC). DC classifies similar objects into a groups of similar characteristics. Clustering involves grouping the data around k-cluster centres that typically are selected randomly. Recently, the issues behind DC have called for a search for an alternative solution. Recently, a nature-based optimization algorithm named Black Hole Algorithm (BHA) was developed to address the several well-known optimization problems. The BHA is a metaheuristic (population-based) that mimics the event around the natural phenomena of black holes, whereby an individual star represents the potential solutions revolving around the solution space. The original BHA algorithm showed better performance compared to other algorithms when applied to a benchmark dataset, despite its poor exploration capability. Hence, this paper presents a multi-population version of BHA as a generalization of the BHA called MBHA wherein the performance of the algorithm is not dependent on the best-found solution but a set of generated best solutions. The method formulated was subjected to testing using a set of nine widespread and popular benchmark test functions. The ensuing experimental outcomes indicated the highly precise results generated by the method compared to BHA and comparable algorithms in the study, as well as excellent robustness. Furthermore, the proposed MBHA achieved a high rate of convergence on six real datasets (collected from the UCL machine learning lab), making it suitable for DC problems. Lastly, the evaluations conclusively indicated the appropriateness of the proposed algorithm to resolve DC issues.
    Matched MeSH terms: Data Mining/methods
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links