Displaying publications 1 - 20 of 25 in total

Abstract:
Sort:
  1. Metal-Organic Framework-Based Composites for the Detection and Monitoring of Pharmaceutical Compounds in Biological and Environmental Matrices
    Rizwan M, Selvanathan V, Rasool A, Qureshi MAUR, Iqbal DN, Kanwal Q, et al.
    Water Air Soil Pollut, 2022;233(12):493.
    PMID: 36466935 DOI: 10.1007/s11270-022-05904-2
    The production of synthetic drugs is considered a huge milestone in the healthcare sector, transforming the overall health, aging, and lifestyle of the general population. Due to the surge in production and consumption, pharmaceutical drugs have emerged as potential environmental pollutants that are toxic with low biodegradability. Traditional chromatographic techniques in practice are time-consuming and expensive, despite good precision. Alternatively, electroanalytical techniques are recently identified to be selective, rapid, sensitive, and easier for drug detection. Metal-organic frameworks (MOFs) are known for their intrinsic porous nature, high surface area, and diversity in structural design that provides credible drug-sensing capacities. Long-term reusability and maintaining chemo-structural integrity are major challenges that are countered by ligand-metal combinations, optimization of synthetic conditions, functionalization, and direct MOFs growth over the electrode surface. Moreover, chemical instability and lower conductivities limited the mass commercialization of MOF-based materials in the fields of biosensing, imaging, drug release, therapeutics, and clinical diagnostics. This review is dedicated to analyzing the various combinations of MOFs used for electrochemical detection of pharmaceutical drugs, comprising antibiotics, analgesics, anticancer, antituberculosis, and veterinary drugs. Furthermore, the relationship between the composition, morphology and structural properties of MOFs with their detection capabilities for each drug species is elucidated.
  2. Fulltext Prophylactic potential of honey and Nigella sativa L. against hospital and community-based SARS-CoV-2 spread: a structured summary of a study protocol for a randomised controlled trial
    Ashraf S, Ashraf S, Akmal R, Ashraf M, Kalsoom L, Maqsood A, et al.
    Trials, 2021 Sep 15;22(1):618.
    PMID: 34526081 DOI: 10.1186/s13063-021-05510-3
    OBJECTIVES: Considering the therapeutic potential of honey and Nigella sativa (HNS) in coronavirus disease 2019 (COVID-19) patients, the objective of the study is defined to evaluate the prophylactic role of HNS.

    TRIAL DESIGN: The study is a randomized, placebo-controlled, adaptive clinical trial with parallel group design, superiority framework with an allocation ratio of 1:1 among experimental (HNS) and placebo group. An interim analysis will be done when half of the patients have been recruited to evaluate the need to adapt sample size, efficacy, and futility of the trial.

    PARTICIPANTS: All asymptomatic patients with hospital or community based COVID-19 exposure will be screened if they have had 4 days exposure to a confirmed case. Non-pregnant adults with significant exposure level will be enrolled in the study High-risk exposure (<6 feet distance for >10min without face protection) Moderate exposure (<6 feet distance for >10min with face protection) Subjects with acute or chronic infection, COVID-19 vaccinated, and allergy to HNS will be excluded from the study. Recruitment will be done at Shaikh Zayed Post-Graduate Medical Institute, Ali Clinic and Doctors Lounge in Lahore (Pakistan).

    INTERVENTION AND COMPARATOR: In this clinical study, patients will receive either raw natural honey (0.5 g) and encapsulated organic Nigella sativa seeds (40 mg) per kg body weight per day or empty capsule with and 30 ml of 5% dextrose water as a placebo for 14 days. Both the natural products will be certified for standardization by Government College University (Botany department). Furthermore, each patient will be given standard care therapy according to version 3.0 of the COVID-19 clinical management guidelines by the Ministry of National Health Services of Pakistan.

    MAIN OUTCOMES: Primary outcome will be Incidence of COVID-19 cases within 14 days of randomisation. Secondary endpoints include incidence of COVID-19-related symptoms, hospitalizations, and deaths along with the severity of COVID-19-related symptoms till 14th day of randomization.

    RANDOMISATION: Participants will be randomized into experimental and control groups (1:1 allocation ratio) via the lottery method. There will be stratification based on high risk and moderate risk exposure.

    BLINDING (MASKING): Quadruple blinding will be ensured for the participants, care providers and outcome accessors. Data analysts will also be blinded to avoid conflict of interest. Site principal investigator will be responsible for ensuring masking.

    NUMBERS TO BE RANDOMISED (SAMPLE SIZE): 1000 participants will be enrolled in the study with 1:1 allocation.

    TRIAL STATUS: The final protocol version 1.4 was approved by institutional review board of Shaikh Zayed Post-Graduate Medical Complex on February 15, 2021. The trial recruitment was started on March 05, 2021, with a trial completion date of February 15, 2022.

    TRIAL REGISTRATION: Clinical trial was registered on February 23, 2021, www.clinicaltrials.gov with registration ID NCT04767087 .

    FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). With the intention of expediting dissemination of this trial, the conventional formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol. The study protocol has been reported in accordance with the Standard Protocol Items: Recommendations for Clinical Interventional Trials (SPIRIT) guidelines.

  3. Tricks and tracks in waste management with a special focus on municipal landfill leachate: Leads and obstacles
    Mohanty SS, Vyas S, Koul Y, Prajapati P, Varjani S, Chang JS, et al.
    Sci Total Environ, 2023 Feb 20;860:160377.
    PMID: 36414054 DOI: 10.1016/j.scitotenv.2022.160377
    Landfilling is the most widely used disposal method for municipal solid waste around the world. The main disadvantage of this strategy is formation of leachate, among other aspects. Landfill leachate contains highly toxic and bio-refractory substances that are detrimental to the environment and human health. Hence, the risk(s) of discharging potentially harmful landfill leachate into the environment need to be assessed and measured in order to make effective choices about landfill leachate management and treatment. In view of this, the present review aims to investigate (a) how landfill leachate is perceived as an emerging concern, and (b) the stakeholders' mid- to long-term policy priorities for implementing technological and integrative solutions to reduce the harmful effects of landfill leachate. Because traditional methods alone have been reported ineffective, and in response to emerging contaminants and stringent regulations, new effective and integrated leachate treatments have been developed. This study gives a forward-thinking of the accomplishments and challenges in landfill leachate treatment during the last decade. It also provides a comprehensive compilation of the formation and characterization of landfill leachate, the geo-environmental challenges that it raises, as well as the resource recovery and industrial linkage associated with it in order to provide an insight into its sustainable management.
  4. A critical review and prospect of NO2 and SO2 pollution over Asia: Hotspots, trends, and sources
    Jion MMMF, Jannat JN, Mia MY, Ali MA, Islam MS, Ibrahim SM, et al.
    Sci Total Environ, 2023 Mar 13;876:162851.
    PMID: 36921864 DOI: 10.1016/j.scitotenv.2023.162851
    Nitrogen dioxide (NO2) and sulfur dioxide (SO2) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO2 and SO2, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO2 and SO2 across Asian countries (e.g., Bangladesh, China, India, Iran, Japan, Pakistan, Malaysia, Kuwait, and Nepal). Based on the findings of the review, NO2 and SO2 pollution are increasing due to industrial activity, fossil fuel burning, biomass burning, heavy traffic movement, electricity generation, and power plants. There is significant concern about health risks associated with NO2 and SO2 emissions in Bangladesh, China, India, Malaysia, and Iran, as they pay less attention to managing and controlling pollution. Even though the lack of quality datasets and adequate research in most Asian countries further complicates the management and control of NO2 and SO2 pollution. This study has NO2 and SO2 pollution scenarios, including hotspots, trends, sources, and their influences on Asian countries. This study highlights the existing research gaps and recommends new research on identifying integrated sources, their variations, spatiotemporal trends, emission characteristics, and pollution level. Finally, the present study suggests a framework for controlling and monitoring these two pollutants' emissions.
  5. Time-domain reconstruction using sensitivity coefficients for limited view ultrawide band tomography
    Abdullah MZ, Yin W, Bilal M, Armitage DW, Mackin R, Peyton AJ
    Rev Sci Instrum, 2007 Aug;78(8):084703.
    PMID: 17764343
    This article addresses time-domain ultrawide band (UWB) electromagnetic tomography for reconstructing the unknown spatial characteristic of an object from observations of the arrivals of short electromagnetic (EM) pulses. Here, the determination of the first peak arrival of the EM traces constitutes the forward problem, and the inverse problem aims to reconstruct the EM property distribution of the media. In this article, the finite-difference time-domain method implementing a perfectly matched layer is used to solve the forward problem from which the system sensitivity maps are determined. Image reconstruction is based on the combination of a linearized update and regularized Landweber minimization algorithm. Experimental data from a laboratory UWB system using targets of different contrasts, sizes, and shapes in an aqueous media are presented. The results show that this technique can accurately detect and locate unknown targets in spite of the presence of significant levels of noise in the data.
  6. Fulltext The Effect of 4-hydroxybenzaldehyde on the γ-aminobutyric Acid Type A Receptor
    Zhang J, Mohamad H, Wong JH, Bilal M, Ismail AHB, Lloyd AJ, et al.
    Malays J Med Sci, 2017 Mar;24(2):94-99.
    PMID: 28894409 DOI: 10.21315/mjms2017.24.2.12
    The α1β2γ2 subtype of GABAA receptors is the most commonly found GABAA receptor subtype in the mammalian cortex and hippocampus. It is expressed heterologously in the Xenopus laevis oocyte as a α1β2γ2S/L subtype for application as an in vitro model for the screening of compounds that modulate receptor activities. In fact, 4-hydroxybenzaldehyde (4-HB) has been identified as one of the major components in Dendrocalamus asper bamboo shoots in our previous study, and the current study showed that at 101.7 μM, 4-HB significantly reduced the GABA-induced chloride current of GABAA receptors expressed on Xenopus oocytes, indicating a possible GABAergic antagonistic effect at high concentrations.
  7. Fulltext Improved Reconstruction of MR Scanned Images by Using a Dictionary Learning Scheme
    Ikram S, Shah JA, Zubair S, Qureshi IM, Bilal M
    Sensors (Basel), 2019 Apr 23;19(8).
    PMID: 31018597 DOI: 10.3390/s19081918
    The application of compressed sensing (CS) to biomedical imaging is sensational since it permits a rationally accurate reconstruction of images by exploiting the image sparsity. The quality of CS reconstruction methods largely depends on the use of various sparsifying transforms, such as wavelets, curvelets or total variation (TV), to recover MR images. As per recently developed mathematical concepts of CS, the biomedical images with sparse representation can be recovered from randomly undersampled data, provided that an appropriate nonlinear recovery method is used. Due to high under-sampling, the reconstructed images have noise like artifacts because of aliasing. Reconstruction of images from CS involves two steps, one for dictionary learning and the other for sparse coding. In this novel framework, we choose Simultaneous code word optimization (SimCO) patch-based dictionary learning that updates the atoms simultaneously, whereas Focal underdetermined system solver (FOCUSS) is used for sparse representation because of a soft constraint on sparsity of an image. Combining SimCO and FOCUSS, we propose a new scheme called SiFo. Our proposed alternating reconstruction scheme learns the dictionary, uses it to eliminate aliasing and noise in one stage, and afterwards restores and fills in the k-space data in the second stage. Experiments were performed using different sampling schemes with noisy and noiseless cases of both phantom and real brain images. Based on various performance parameters, it has been shown that our designed technique outperforms the conventional techniques, like K-SVD with OMP, used in dictionary learning based MRI (DLMRI) reconstruction.
  8. Multi-Objective Task-Aware Offloading and Scheduling Framework for Internet of Things Logistics
    Umer A, Ali M, Jehangiri AI, Bilal M, Shuja J
    Sensors (Basel), 2024 Apr 09;24(8).
    PMID: 38675998 DOI: 10.3390/s24082381
    IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon is called task offloading. Researchers have developed efficient task offloading and scheduling mechanisms for IoT devices to reduce energy consumption and response time. However, most research has not considered fault-tolerance-based job allocation for IoT logistics trucks, task and data-aware scheduling, priority-based task offloading, or multiple-parameter-based fog node selection. To overcome the limitations, we proposed a Multi-Objective Task-Aware Offloading and Scheduling Framework for IoT Logistics (MT-OSF). The proposed model prioritizes the tasks into delay-sensitive and computation-intensive tasks using a priority-based offloader and forwards the two lists to the Task-Aware Scheduler (TAS) for further processing on fog and cloud nodes. The Task-Aware Scheduler (TAS) uses a multi-criterion decision-making process, i.e., the analytical hierarchy process (AHP), to calculate the fog nodes' priority for task allocation and scheduling. The AHP decides the fog nodes' priority based on node energy, bandwidth, RAM, and MIPS power. Similarly, the TAS also calculates the shortest distance between the IoT-enabled vehicle and the fog node to which the IoT tasks are assigned for execution. A task-aware scheduler schedules delay-sensitive tasks on nearby fog nodes while allocating computation-intensive tasks to cloud data centers using the FCFS algorithm. Fault-tolerant manager is used to check task failure; if any task fails, the proposed system re-executes the tasks, and if any fog node fails, the proposed system allocates the tasks to another fog node to reduce the task failure ratio. The proposed model is simulated in iFogSim2 and demonstrates a 7% reduction in response time, 16% reduction in energy consumption, and 22% reduction in task failure ratio in comparison to Ant Colony Optimization and Round Robin.
  9. Fulltext The non-Newtonian maxwell nanofluid flow between two parallel rotating disks under the effects of magnetic field
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Oct 13;10(1):17088.
    PMID: 33051520 DOI: 10.1038/s41598-020-74096-8
    The main feature of the present numerical model is to explore the behavior of Maxwell nanoliquid moving within two horizontal rotating disks. The disks are stretchable and subjected to a magnetic field in axial direction. The time dependent characteristics of thermal conductivity have been considered to scrutinize the heat transfer phenomena. The thermophoresis and Brownian motion features of nanoliquid are studied with Buongiorno model. The lower and upper disk's rotation for both the cases, same direction as well as opposite direction of rotation is investigated. The subsequent arrangement of the three dimensional Navier Stoke's equations along with energy, mass and Maxwell equations are diminished to a dimensionless system of equations through the Von Karman's similarity framework. The comparative numerical arrangement of modeled equations is further set up by built-in numerical scheme "boundary value solver" (Bvp4c) and Runge Kutta fourth order method (RK4). The various physical constraints, such as Prandtl number, thermal conductivity, magnetic field, thermal radiation, time relaxation, Brownian motion and thermophoresis parameters and their impact are presented and discussed briefly for velocity, temperature, concentration and magnetic strength profiles. In the present analysis, some vital characteristics such as Nusselt and Sherwood numbers are considered for physical and numerical investigation. The outcomes concluded that the disk stretching action opposing the flow behavior. With the increases of magnetic field parameter [Formula: see text] the fluid velocity decreases, while improving its temperature. We show a good agreement of the present work by comparing with those published in literature.
  10. Fulltext Numerical analysis of thermal conductive hybrid nanofluid flow over the surface of a wavy spinning disk
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Nov 02;10(1):18776.
    PMID: 33139760 DOI: 10.1038/s41598-020-75905-w
    A three dimensional (3D) numerical solution of unsteady, Ag-MgO hybrid nanoliquid flow with heat and mass transmission caused by upward/downward moving of wavy spinning disk has been scrutinized. The magnetic field has been also considered. The hybrid nanoliquid has been synthesized in the presence of Ag-MgO nanoparticles. The purpose of the study is to improve the rate of thermal energy transmission for several industrial purposes. The wavy rotating surface increases the heat transmission rate up to 15%, comparatively to the flat surface. The subsequent arrangement of modeled equations is diminished into dimensionless differential equation. The obtained system of equations is further analytically expounded via Homotopy analysis method HAM and the numerical Parametric continuation method (PCM) method has been used for the comparison of the outcomes. The results are graphically presented and discussed. It has been presumed that the geometry of spinning disk positively affects the velocity and thermal energy transmission. The addition of hybrid nanoparticles (silver and magnesium-oxide) significantly improved thermal property of carrier fluid. It uses is more efficacious to overcome low energy transmission. Such as, it provides improvement in thermal performance of carrier fluid, which play important role in power generation, hyperthermia, micro fabrication, air conditioning and metallurgical field.
  11. Fulltext The impact of PEG-induced drought stress on seed germination and seedling growth of different bread wheat (Triticum aestivum L.) genotypes
    Mahpara S, Zainab A, Ullah R, Kausar S, Bilal M, Latif MI, et al.
    PLoS One, 2022;17(2):e0262937.
    PMID: 35148345 DOI: 10.1371/journal.pone.0262937
    Wheat is an important crop, used as staple food in numerous countries around the world. However, wheat productivity is low in the developing world due to several biotic and abiotic stresses, particularly drought stress. Non-availability of drought-tolerant wheat genotypes at different growth stages is the major constraint in improving wheat productivity in the developing world. Therefore, screening/developing drought-tolerant genotypes at different growth stages could improve the productivity of wheat. This study assessed seed germination and seedling growth of eight wheat genotypes under polyethylene glycol (PEG)-induced stress. Two PEG-induced osmotic potentials (i.e., -0.6 and -1.2 MPa) were included in the study along with control (0 MPa). Wheat genotypes included in the study were 'KLR-16', 'B6', 'J10', '716', 'A12', 'Seher', 'KTDH-16', and 'J4'. Data relating to seed germination percentage, root and shoot length, fresh and dry weight of roots and shoot, root/shoot length ratio and chlorophyll content were recorded. The studied parameters were significantly altered by individual and interactive effects of genotypes and PEG-induced osmotic potentials. Seed germination and growth parameters were reduced by osmotic potentials; however, huge differences were noted among genotypes. A reduction of 32.83 to 53.50% was recorded in seed germination, 24.611 to 47.75% in root length, 37.83 to 53.72% in shoot length, and 53.35 to 65.16% in root fresh weight. The genotypes, 'J4', 'KLR-16' and 'KTDH-16', particularly 'J4' better tolerated increasing osmotic potentials compared to the rest of the genotypes included in the study. Principal component analysis segregated these genotypes from the rest of the genotypes included in the study indicated that these can be used in the future studies to improve the drought tolerance of wheat crop. The genotype 'J4' can be used as a breeding material to develop drought resistant wheat genotypes.
  12. Fulltext Green photosensitisers for the degradation of selected pesticides of high risk in most susceptible food: A safer approach
    Baig A, Zubair M, Sumrra SH, Rashid U, Zafar MN, Ahmad F, et al.
    PLoS One, 2021;16(10):e0258864.
    PMID: 34710164 DOI: 10.1371/journal.pone.0258864
    Pesticides are the leading defence against pests, but their unsafe use reciprocates the pesticide residues in highly susceptible food and is becoming a serious risk for human health. In this study, mint extract and riboflavin were tested as photosensitisers in combination with light irradiation of different frequencies, employed for various time intervals to improve the photo-degradation of deltamethrin (DM) and lambda cyhalothrin (λ-CHT) in cauliflower. Different source of light was studied, either in ultraviolet range (UV-C, 254 nm or UV-A, 320-380 nm) or sunlight simulator (> 380-800 nm). The degradation of the pesticides varied depending on the type of photosensitiser and light source. Photo-degradation of the DM and λ-CHT was enhanced by applying the mint extracts and riboflavin and a more significant degradation was achieved with UV-C than with either UV-A or sunlight, reaching a maximum decrement of the concentration by 67-76%. The light treatments did not significantly affect the in-vitro antioxidant activity of the natural antioxidants in cauliflower. A calculated dietary risk assessment revealed that obvious dietary health hazards of DM and λ-CHT pesticides when sprayed on cauliflower for pest control. The use of green chemical photosensitisers (mint extract and riboflavin) in combination with UV light irradiation represents a novel, sustainable, and safe approach to pesticide reduction in produce.
  13. Fulltext Total Synthesis of Terpenes and Their Biological Significance: A Critical Review
    Kanwal A, Bilal M, Rasool N, Zubair M, Shah SAA, Zakaria ZA
    Pharmaceuticals (Basel), 2022 Nov 11;15(11).
    PMID: 36422521 DOI: 10.3390/ph15111392
    Terpenes are a group of natural products made up of molecules with the formula (C5H8)n that are typically found in plants. They are widely employed in the medicinal, flavor, and fragrance industries. The total synthesis of terpenes as well as their origin and biological potential are discussed in this review.
  14. N-([1,1'-biaryl]-4-yl)-1-naphthamide-based scaffolds synthesis, their cheminformatics analyses, and screening as bacterial biofilm inhibitor
    Ejaz S, Zubair M, Rasool N, Ahmed F, Bilal M, Ahmad G, et al.
    J Basic Microbiol, 2021 Nov 01.
    PMID: 34724237 DOI: 10.1002/jobm.202100288
    Naphthamides have pharmacological potential as they express strong activities against microorganisms. The commercially available naphthoyl chloride and 4-bromoaniline were condensed in dry dichloromethane (DCM) in the presence of Et3 N to form N-(4-bromophenyl)-1-naphthamide (86%) (3). Using a Pd(0) catalyzed Suzuki-Miyaura Cross-Coupling reaction of (3) and various boronic acids, a series of N-([1,1'-biaryl]-4-yl)-1-naphthamide derivatives (4a-h) were synthesized in moderate to good yields. The synthesized derivatives were evaluated for cytotoxicity haemolytic assay and biofilm inhibition activity through in silico and in vitro studies. Molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity risk, and other cheminformatics predict synthesized molecules as biologically active moieties, further validated through in vitro studies in which compounds (4c) and (4f) showed significant haemolytic activity whereas (4e) exhibited an efficient biofilm inhibition activity against Gram-negative bacteria Escherichia coli and Gram-positive bacteria Bacillus subtilis. When forming biofilms, bacteria become resistant to various antimicrobial treatments. Currently, research is focused on the development of agents that inhibit biofilm formation, thus the present work is valuable for preventing future drug resistance.
  15. Fulltext Respiratory Motion Correction for Compressively Sampled Free Breathing Cardiac MRI Using Smoothl1-Norm Approximation
    Bilal M, Shah JA, Qureshi IM, Kadir K
    Int J Biomed Imaging, 2018;2018:7803067.
    PMID: 29610569 DOI: 10.1155/2018/7803067
    Transformed domain sparsity of Magnetic Resonance Imaging (MRI) has recently been used to reduce the acquisition time in conjunction with compressed sensing (CS) theory. Respiratory motion during MR scan results in strong blurring and ghosting artifacts in recovered MR images. To improve the quality of the recovered images, motion needs to be estimated and corrected. In this article, a two-step approach is proposed for the recovery of cardiac MR images in the presence of free breathing motion. In the first step, compressively sampled MR images are recovered by solving an optimization problem using gradient descent algorithm. TheL1-norm based regularizer, used in optimization problem, is approximated by a hyperbolic tangent function. In the second step, a block matching algorithm, known as Adaptive Rood Pattern Search (ARPS), is exploited to estimate and correct respiratory motion among the recovered images. The framework is tested for free breathing simulated andin vivo2D cardiac cine MRI data. Simulation results show improved structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean square error (MSE) with different acceleration factors for the proposed method. Experimental results also provide a comparison betweenk-tFOCUSS with MEMC and the proposed method.
  16. Sustainable Hydrates for Enhanced Carbon Dioxide Capture from an Integrated Gasification Combined Cycle in a Fixed Bed Reactor
    Abu Hassan MH, Sher F, Fareed B, Ali U, Zafar A, Bilal M, et al.
    Ind Eng Chem Res, 2021 Aug 04;60(30):11346-11356.
    PMID: 34475634 DOI: 10.1021/acs.iecr.1c01174
    An increase in temperature of up to 2 °C occurs when the amount of CO2 reaches a range of 450 ppm. The permanent use of mineral oil is closely related to CO2 emissions. Maintaining the sustainability of fossil fuels and eliminating and reducing CO2 emissions is possible through carbon capture and storage (CCS) processes. One of the best ways to maintain CCS is hydrate-based gas separation. Selected type T1-5 (0.01 mol % sodium dodecyl sulphate (SDS) + 5.60 mol % tetrahydrofuran (THF), with the help of this silica gel promotion was strongly stimulated. A pressure of 36.5 bar of CO2 is needed in H2O to investigate the CO2 hydrate formation. Therefore, ethylene glycol monoethyl ether (EGME at 0.10 mol %) along with SDS (0.01 mol %) labeled as T1A-2 was used as an alternative to THF at the comparable working parameters in which CO2 uptake of 5.45 mmol of CO2/g of H2O was obtained. Additionally, it was found that with an increase in tetra-n-butyl ammonium bromide (TBAB) supplementation of CO2, the hydrate and operating capacity of the process increased. When the bed height was reduced from 3 cm to 2 cm with 0.1 mol % TBAB and 0.01% SDS (labelled as T3-2) in fixed bed reactor (FBR), the outcomes demonstrated a slight expansion in gas supply to 1.54 mmol of CO2/g of H2O at working states of 283 K and 70 bar. The gas selectivity experiment by using the high-pressure volume analysis through hydrate formation was performed in which the highest CO2 uptake for the employment of silica contacts with water in fuel gas mixture was observed in the non-IGCC conditions. Thus, two types of reactor configurations are being proposed for changing the process from batch to continuous with the employment of macroporous silica contacts with new consolidated promoters to improve the formation of CO2 hydrate in the IGCC conditions. Later, much work should be possible on this with an assortment of promoters and specific performance parameters. It was reported in previous work that the repeatability of equilibrium moisture content and gas uptake attained for the sample prepared by the highest rates of stirring was the greatest with the CIs of ±0.34 wt % and ±0.19 mmol of CO2/g of H2O respectively. This was due to the amount of water occluded inside silica gel pores was not an issue or in other words, vigorous stirring increased the spreadability. The variation of pore size to improve the process can be considered for future work.
  17. Biocatalytic remediation of pharmaceutically active micropollutants for environmental sustainability
    Bilal M, Lam SS, Iqbal HMN
    Environ Pollut, 2022 Jan 15;293:118582.
    PMID: 34856243 DOI: 10.1016/j.envpol.2021.118582
    The discharge of an alarming number of recalcitrant pollutants from various industrial activities presents a serious threat to environmental sustainability and ecological integrity. Bioremediation has gained immense interest around the world due to its environmentally friendly and cost-effective nature. In contrast to physical and chemical methods, the use of microbial enzymes, particularly immobilized biocatalysts, has been demonstrated as a versatile approach for the sustainable mitigation of environmental pollution. Considerable attention is now devoted to developing novel enzyme engineering approaches and state-of-the-art bioreactor design for ameliorating the overall bio-catalysis and biodegradation performance of enzymes. This review discusses the contemporary and state of the art technical and scientific progress regarding applying oxidoreductase enzyme-based biocatalytic systems to remediate a vast number of pharmaceutically active compounds from water and wastewater bodies. A comprehensive insight into enzyme immobilization, the role of mediators, bioreactors designing, and transformation products of pharmaceuticals and their associated toxicity is provided. Additional studies are necessary to elucidate enzymatic degradation mechanisms, monitor the toxicity levels of the resulting degraded metabolites and optimize the entire bio-treatment strategy for technical and economical affordability.
  18. Fulltext An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal
    Ullah H, Heyat MBB, Akhtar F, Muaad AY, Ukwuoma CC, Bilal M, et al.
    Diagnostics (Basel), 2022 Dec 28;13(1).
    PMID: 36611379 DOI: 10.3390/diagnostics13010087
    The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan-Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.
  19. Social Profiling: A Review, Taxonomy, and Challenges
    Bilal M, Gani A, Lali MIU, Marjani M, Malik N
    Cyberpsychol Behav Soc Netw, 2019 Jul;22(7):433-450.
    PMID: 31074639 DOI: 10.1089/cyber.2018.0670
    Social media has taken an important place in the routine life of people. Every single second, users from all over the world are sharing interests, emotions, and other useful information that leads to the generation of huge volumes of user-generated data. Profiling users by extracting attribute information from social media data has been gaining importance with the increasing user-generated content over social media platforms. Meeting the user's satisfaction level for information collection is becoming more challenging and difficult. This is because of too much noise generated, which affects the process of information collection due to explosively increasing online data. Social profiling is an emerging approach to overcome the challenges faced in meeting user's demands by introducing the concept of personalized search while keeping in consideration user profiles generated using social network data. This study reviews and classifies research inferring users social profile attributes from social media data as individual and group profiling. The existing techniques along with utilized data sources, the limitations, and challenges are highlighted. The prominent approaches adopted include Machine Learning, Ontology, and Fuzzy logic. Social media data from Twitter and Facebook have been used by most of the studies to infer the social attributes of users. The studies show that user social attributes, including age, gender, home location, wellness, emotion, opinion, relation, influence, and so on, still need to be explored. This review gives researchers insights of the current state of literature and challenges for inferring user profile attributes using social media data.
  20. Cytokine storm and neuropathological alterations in patients with neurological manifestations of COVID-19
    Tsagkaris C, Bilal M, Aktar I, Aboufandi Y, Tas A, Aborode AT, et al.
    Curr Alzheimer Res, 2022 Sep 08.
    PMID: 36089786 DOI: 10.2174/1567205019666220908084559
    The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2), a respiratory pathogen with neuroinvasive potential. Neurological COVID-19 manifestations include loss of smell and taste, headache, dizziness, stroke, and potentially fatal encephalitis. Several studies found elevated proinflammatory cytokines such as TNF-α, IFN-γ, IL-6 IL-8, IL-10 IL-16, IL-17A, and IL-18 in severely and critically ill COVID-19 patients, which may persist even after apparent recovery from infection. Biomarker studies on CSF and plasma and serum from COVID-19 patients have also shown a high level of IL-6, intrathecal IgG, neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), and tau protein. Emerging evidence on the matter has established the concept of COVID-19 associated neuroinflammation, in the context of COVID-19 associated cytokine storm. While the short-term implications of this condition are extensively documented, its long-term implications are yet to be understood. The association of the aforementioned cytokines with the pathogenesis of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, and amyotrophic lateral sclerosis, may increase COVID-19 patients' risk to develop neurodegenerative diseases. Analysis of proinflammatory cytokines and CSF biomarkers in patients with COVID-19 can contribute to the early detection of the disease's exacerbation, monitoring the neurological implications of the disease and devising risk scales, and identifying treatment targets.
Related Terms
Filters
Contact Us

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

External Links