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Fulltext Synthesis and Characterization of Carbon and Carbon-Nitrogen Doped Black TiO2 Nanomaterials and Their Application in Sonophotocatalytic Remediation of Treated Agro-Industrial Wastewater

Rahman S, Nawaz R, Khan JA, Ullah H, Irfan M, Glowacz A, et al.

Materials (Basel), 2021 Oct 18;14(20).
PMID: 34683764 DOI: 10.3390/ma14206175

The conventional open ponding system employed for palm oil mill agro-effluent (POME) treatment fails to lower the levels of organic pollutants to the mandatory standard discharge limits. In this work, carbon doped black TiO2 (CB-TiO2) and carbon-nitrogen co-doped black TiO2 (CNB-TiO2) were synthesized via glycerol assisted sol-gel techniques and employed for the remediation of treated palm oil mill effluent (TPOME). Both the samples were anatase phase, with a crystallite size of 11.09-22.18 nm, lower bandgap of 2.06-2.63 eV, superior visible light absorption ability, and a high surface area of 239.99-347.26 m2/g. The performance of CNB-TiO2 was higher (51.48%) compared to only (45.72%) CB-TiO2. Thus, the CNB-TiO2 is employed in sonophotocatalytic reactions. Sonophotocatalytic process based on CNB-TiO2, assisted by hydrogen peroxide (H2O2), and operated at an ultrasonication (US) frequency of 30 kHz and 40 W power under visible light irradiation proved to be the most efficient for chemical oxygen demand (COD) removal. More than 90% of COD was removed within 60 min of sonophotocatalytic reaction, producing the effluent with the COD concentration well below the stipulated permissible limit of 50 mg/L. The electrical energy required per order of magnitude was estimated to be only 177.59 kWh/m3, indicating extreme viability of the proposed process for the remediation of TPOME.
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.
Fulltext Multipotent Cholinesterase Inhibitors for the Treatment of Alzheimer's Disease: Synthesis, Biological Analysis and Molecular Docking Study of Benzimidazole-Based Thiazole Derivatives

Hussain R, Ullah H, Rahim F, Sarfraz M, Taha M, Iqbal R, et al.

Molecules, 2022 Sep 18;27(18).
PMID: 36144820 DOI: 10.3390/molecules27186087

Twenty-four analogues of benzimidazole-based thiazoles (1-24) were synthesized and assessed for their in vitro acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitory potential. All analogues were found to exhibit good inhibitory potential against cholinesterase enzymes, having IC50 values in the ranges of 0.10 ± 0.05 to 11.10 ± 0.30 µM (for AChE) and 0.20 ± 0.050 µM to 14.20 ± 0.10 µM (for BuChE) as compared to the standard drug Donepezil (IC50 = 2.16 ± 0.12 and 4.5 ± 0.11 µM, respectively). Among the series, analogues 16 and 21 were found to be the most potent inhibitors of AChE and BuChE enzymes. The number (s), types, electron-donating or -withdrawing effects and position of the substituent(s) on the both phenyl rings B & C were the primary determinants of the structure-activity relationship (SAR). In order to understand how the most active derivatives interact with the amino acids in the active site of the enzyme, molecular docking studies were conducted. The results obtained supported the experimental data. Additionally, the structures of all newly synthesized compounds were elucidated by using several spectroscopic methods like 13C-NMR, 1H-NMR and HR EIMS.
The immunomodulation potential of the synthetic derivatives of benzothiazoles: Implications in immune system disorders through in vitro and in silico studies

Khan KM, Mesaik MA, Abdalla OM, Rahim F, Soomro S, Halim SA, et al.

Bioorg Chem, 2016 Feb;64:21-8.
PMID: 26637945 DOI: 10.1016/j.bioorg.2015.11.004

Benzothiazole and its natural or synthetic derivatives have been used as precursors for several pharmacological agents for neuroprotective, anti-bacterial, and anti-allergic activities. The objective of the present study was to evaluate effects of benzothiazole analogs (compounds 1-26) for their immunomodulatory activities. Eight compounds (2, 4, 5, 8-10, 12, and 18) showed potent inhibitory activity on PHA-activated peripheral blood mononuclear cells (PBMCs) with IC50 ranging from 3.7 to 11.9 μM compared to that of the standard drug, prednisolone <1.5 μM. Some compounds (2, 4, 8, and 18) were also found to have potent inhibitory activities on the production of IL-2 on PHA/PMA-stimulated PBMCs with IC50 values ranging between <4.0 and 12.8 μM. The binding interaction of these compounds was performed through silico molecular docking. Compounds 2, 8, 9, and 10 significantly suppressed oxidative burst ROS production in phagocytes with IC50 values between <4.0 and 15.2 μM. The lipopolysaccharide (LPS)-induced nitrites in murine macrophages cell line J774 were found to be inhibited by compounds 4, 8, 9, and 18 at a concentration of 25 μg/mL by 56%, 91%, 58%, and 78%, respectively. Furthermore, compounds 5, 8, 12, and 18 showed significant (P<0.05) suppressive activity on Th-2 cytokine, interleukin 4 (IL-4) with an IC50 range of <4.0 to 40.3 μM. Interestingly compound 4 has shown a selective inhibitory activity on IL-2 and T cell proliferation (naïve T cell proliferation stage) rather than on IL-4 cytokine, while compound 12 displayed an interference with T-cell proliferation and IL-4 generation. Moreover compound 8 and 18 exert non-selective inhibition on both IL-2 and IL-4 cytokines, indicating a better interference with stage leading to humoral immune response and hence possible application in autoimmune diseases.
A hysteresis-free perovskite transistor with exceptional stability through molecular cross-linking and amine-based surface passivation

Kim HP, Vasilopoulou M, Ullah H, Bibi S, Ximim Gavim AE, Macedo AG, et al.

Nanoscale, 2020 Apr 14;12(14):7641-7650.
PMID: 32207472 DOI: 10.1039/c9nr10745b

Organo-metal halide perovskite field-effect transistors present serious challenges in terms of device stability and hysteresis in the current-voltage characteristics. Migration of ions located at grain boundaries and surface defects in the perovskite film are the main reasons for instability and hysteresis issues. Here, we introduce a perovskite grain molecular cross-linking approach combined with amine-based surface passivation to address these issues. Molecular cross-linking was achieved through hydrogen bond interactions between perovskite halogens and dangling bonds present at grain boundaries and a hydrophobic cross-linker, namely diethyl-(12-phosphonododecyl)phosphonate, added to the precursor solution. With our approach, we obtained smooth and compact perovskite layers composed of tightly bound grains hence significantly suppressing the generation and migration of ions. Moreover, we achieved efficient surface passivation of the perovskite films upon surface treatment with an amine-bearing polymer, namely polyethylenimine ethoxylated. With our synergistic grain and surface passivation approach, we were able to demonstrate the first perovskite transistor with a complete lack of hysteresis and unprecedented stability upon continuous operation under ambient conditions. Added to the merits are its ambipolar transport of opposite carriers with balanced hole and electron mobilities of 4.02 and 3.35 cm2 V-1 s-1, respectively, its high Ion/Ioff ratio >104 and the lowest sub-threshold swing of 267 mV dec-1 reported to date for any perovskite transistor. These remarkable achievements obtained through a cost-effective molecular cross-linking of grains combined with amine-based surface passivation of the perovskite films open a new era and pave the way for the practical application of perovskite transistors in low-cost electronic circuits.
Self-healing epoxy coating synthesis by embedment of metal 2-methyl imidazole and acetylacetonate complexes with microcapsules

Ullah H, Qureshi KS, Khan U, Zaffar M, Yang YJ, Rabat NE, et al.

Chemosphere, 2021 Dec;285:131492.
PMID: 34273691 DOI: 10.1016/j.chemosphere.2021.131492

The restoration of mechanical properties is desired for creating the self-healing coatings with no corrosion capabilities. The encapsulation of epoxy resins is limited by various factors in urea and melamine formaldehyde microcapsules. An improved method was developed, where epoxy resin was encapsulated by individual wrapping of poly(melamine-formaldehyde) and poly(urea-formaldehyde) shell around emulsified epoxy droplets via oil-in-water emulsion polymerization method. The synthesized materials were characterized analytically. The curing of the epoxy was achieved by adding the [Ni/Co(2-MI)6].2NO3 as a latent hardener and iron acetylacetonate [Fe(acac)3] as a latent accelerator. Isothermal and non-isothermal differential scanning calorimetric analysis revealed lower curing temperature (Tonset = 116 °C) and lower activation energies (Ea ≈ 69-75 kJ/mol). The addition of microcapsules and complexes did not adversely alter the flexural strength and flexural modulus of the epoxy coatings. The adhesion strength of neat coating decreased from 6310.8 ± 31 to 4720.9 ± 60 kPa and percent healing increased from 50.83 to 67.45% in the presence of acetylacetonate complex at 10 wt% of microcapsules.
Fulltext The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Singla RK, De R, Efferth T, Mezzetti B, Sahab Uddin M, Sanusi, et al.

Phytomedicine, 2023 Jan;108:154520.
PMID: 36334386 DOI: 10.1016/j.phymed.2022.154520

BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.
METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.
RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.