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  1. Fulltext Generative artificial intelligence in drug discovery: basic framework, recent advances, challenges, and opportunities
    Gangwal A, Ansari A, Ahmad I, Azad AK, Kumarasamy V, Subramaniyan V, et al.
    Front Pharmacol, 2024;15:1331062.
    PMID: 38384298 DOI: 10.3389/fphar.2024.1331062
    There are two main ways to discover or design small drug molecules. The first involves fine-tuning existing molecules or commercially successful drugs through quantitative structure-activity relationships and virtual screening. The second approach involves generating new molecules through de novo drug design or inverse quantitative structure-activity relationship. Both methods aim to get a drug molecule with the best pharmacokinetic and pharmacodynamic profiles. However, bringing a new drug to market is an expensive and time-consuming endeavor, with the average cost being estimated at around $2.5 billion. One of the biggest challenges is screening the vast number of potential drug candidates to find one that is both safe and effective. The development of artificial intelligence in recent years has been phenomenal, ushering in a revolution in many fields. The field of pharmaceutical sciences has also significantly benefited from multiple applications of artificial intelligence, especially drug discovery projects. Artificial intelligence models are finding use in molecular property prediction, molecule generation, virtual screening, synthesis planning, repurposing, among others. Lately, generative artificial intelligence has gained popularity across domains for its ability to generate entirely new data, such as images, sentences, audios, videos, novel chemical molecules, etc. Generative artificial intelligence has also delivered promising results in drug discovery and development. This review article delves into the fundamentals and framework of various generative artificial intelligence models in the context of drug discovery via de novo drug design approach. Various basic and advanced models have been discussed, along with their recent applications. The review also explores recent examples and advances in the generative artificial intelligence approach, as well as the challenges and ongoing efforts to fully harness the potential of generative artificial intelligence in generating novel drug molecules in a faster and more affordable manner. Some clinical-level assets generated form generative artificial intelligence have also been discussed in this review to show the ever-increasing application of artificial intelligence in drug discovery through commercial partnerships.
  2. Fulltext β-Carboline alkaloids induce structural plasticity and inhibition of SARS-CoV-2 nsp3 macrodomain more potently than remdesivir metabolite GS-441524: computational approach
    Ayipo YO, Yahaya SN, Babamale HF, Ahmad I, Patel H, Mordi MN
    Turk J Biol, 2021;45(4):503-517.
    PMID: 34803450 DOI: 10.3906/biy-2106-64
    The nsp3 macrodomain is implicated in the viral replication, pathogenesis and host immune responses through the removal of ADP-ribosylation sites during infections of coronaviruses including the SARS-CoV-2. It has ever been modulated by macromolecules including the ADP-ribose until Ni and co-workers recently reported its inhibition and plasticity enhancement unprecedentedly by remdesivir metabolite, GS-441524, creating an opportunity for investigating other biodiverse small molecules such as β-Carboline (βC) alkaloids. In this study, 1497 βC analogues from the HiT2LEAD chemical database were screened, using computational approaches of Glide XP docking, molecular dynamics simulation and pk-CSM ADMET predictions. Selectively, βC ligands, 129, 584, 1303 and 1323 demonstrated higher binding affinities to the receptor, indicated by XP docking scores of -10.72, -10.01, -9.63 and -9.48 kcal/mol respectively than remdesivir and GS-441524 with -4.68 and -9.41 kcal/mol respectively. Consistently, their binding free energies were -36.07, -23.77, -24.07 and -17.76 kcal/mol respectively, while remdesivir and GS-441524 showed -21.22 and -24.20 kcal/mol respectively. Interestingly, the selected βC ligands displayed better stability and flexibility for enhancing the plasticity of the receptor than GS-441524, especially 129 and 1303. Their predicted ADMET parameters favour druggability and low expressions for toxicity. Thus, they are recommended as promising adjuvant/standalone anti-SARS-CoV-2 candidates for further study.Key words: SARS-CoV-2, nsp3 macrodomain, ADP-ribose, β-carboline, bioinformatics, drug design.
  3. Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review
    Gangwal A, Ansari A, Ahmad I, Azad AK, Wan Sulaiman WMA
    Comput Biol Med, 2024 Jul 03;179:108734.
    PMID: 38964243 DOI: 10.1016/j.compbiomed.2024.108734
    Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This development has been further accelerated with the increasing use of machine learning (ML), mainly deep learning (DL), and computing hardware and software advancements. As a result, initial doubts about the application of AI in drug discovery have been dispelled, leading to significant benefits in medicinal chemistry. At the same time, it is crucial to recognize that AI is still in its infancy and faces a few limitations that need to be addressed to harness its full potential in drug discovery. Some notable limitations are insufficient, unlabeled, and non-uniform data, the resemblance of some AI-generated molecules with existing molecules, unavailability of inadequate benchmarks, intellectual property rights (IPRs) related hurdles in data sharing, poor understanding of biology, focus on proxy data and ligands, lack of holistic methods to represent input (molecular structures) to prevent pre-processing of input molecules (feature engineering), etc. The major component in AI infrastructure is input data, as most of the successes of AI-driven efforts to improve drug discovery depend on the quality and quantity of data, used to train and test AI algorithms, besides a few other factors. Additionally, data-gulping DL approaches, without sufficient data, may collapse to live up to their promise. Current literature suggests a few methods, to certain extent, effectively handle low data for better output from the AI models in the context of drug discovery. These are transferring learning (TL), active learning (AL), single or one-shot learning (OSL), multi-task learning (MTL), data augmentation (DA), data synthesis (DS), etc. One different method, which enables sharing of proprietary data on a common platform (without compromising data privacy) to train ML model, is federated learning (FL). In this review, we compare and discuss these methods, their recent applications, and limitations while modeling small molecule data to get the improved output of AI methods in drug discovery. Article also sums up some other novel methods to handle inadequate data.
  4. Fulltext Efficacy and Safety of Pioglitazone Monotherapy in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomised Controlled Trials
    Alam F, Islam MA, Mohamed M, Ahmad I, Kamal MA, Donnelly R, et al.
    Sci Rep, 2019 Mar 29;9(1):5389.
    PMID: 30926892 DOI: 10.1038/s41598-019-41854-2
    Pioglitazone, the only thiazolidinedione drug in clinical practice is under scrutiny due to reported adverse effects, it's unique insulin sensitising action provides rationale to remain as a therapeutic option for managing type 2 diabetes mellitus (T2DM). We conducted a systematic review and meta-analysis comparing pioglitazone monotherapy with monotherapies of other oral antidiabetic drugs for assessing its efficacy and safety in T2DM patients. Mean changes in glycated haemoglobin (HbA1c), and mean changes in fasting blood sugar (FBS) level, body weight (BW) and homeostasis model assessment-insulin resistance (HOMA-IR) were primary and secondary outcomes, respectively. Safety outcomes were changes in lipid parameters, blood pressure and incidences of adverse events. Metafor package of R software and RevMan software based on random-effects model were used for analyses. We included 16 randomised controlled trials. Pioglitazone monotherapy showed equivalent efficacy as comparators in reducing HbA1c by 0.05% (95% CI: -0.21 to 0.11) and greater efficacy in reducing FBS level by 0.24 mmol/l (95% CI: -0.48 to -0.01). Pioglitazone showed similar efficacy as comparators in reducing HOMA-IR (WMD: 0.05, 95% CI: -0.49 to 0.59) and increasing high-density lipoprotein level (WMD: 0.02 mmol/l, 95% CI: -0.06 to 0.10). Improved blood pressure (WMD: -1.05 mmHg, 95% CI: -4.29 to 2.19) and triglycerides level (WMD: -0.71 mmol/l, 95% CI: -1.70 to 0.28) were also observed with pioglitazone monotherapy. There was a significant association of pioglitazone with increased BW (WMD: 2.06 kg, 95% CI: 1.11 to 3.01) and risk of oedema (RR: 2.21, 95% CI: 1.48 to 3.31), though the risk of hypoglycaemia was absolutely lower (RR: 0.51, 95% CI: 0.33 to 0.80). Meta-analysis supported pioglitazone as an effective treatment option for T2DM patients to ameliorate hyperglycaemia, adverse lipid metabolism and blood pressure. Pioglitazone is suggested to prescribe following individual patient's needs. It can be a choice of drug for insulin resistant T2DM patients having dyslipidaemia, hypertension or history of cardiovascular disease.
  5. Shape Dependent Therapeutic Potential of Nanoparticulate System: Advance Approach for Drug Delivery
    Verma S, Malviya R, Srivastava S, Ahmad I, Singh B, Almontasheri R, et al.
    Curr Pharm Des, 2024 Jul 18.
    PMID: 39034725 DOI: 10.2174/0113816128314618240628110218
    Drug delivery systems rely heavily on nanoparticles because they provide a targeted and monitored release of pharmaceuticals that maximize therapeutic efficacy and minimize side effects. To maximize drug internalization, this review focuses on comprehending the interactions between biological systems and nanoparticles. The way that nanoparticles behave during cellular uptake, distribution, and retention in the body is determined by their shape. Different forms, such as mesoporous silica nanoparticles, micelles, and nanorods, each have special properties that influence how well drugs are delivered to cells and internalized. To achieve the desired particle morphology, shape-controlled nanoparticle synthesis strategies take into account variables like pH, temperatures, and reaction time. Top-down techniques entail dissolving bulk materials to produce nanoparticles, whereas bottom-up techniques enable nanostructures to self-assemble. Comprehending the interactions at the bio-nano interface is essential to surmounting biological barriers and enhancing the therapeutic efficacy of nanotechnology in drug delivery systems. In general, drug internalization and distribution are greatly influenced by the shape of nanoparticles, which presents an opportunity for tailored and efficient treatment plans in a range of medical applications.
  6. Cardiovascular Disease and Thrombosis: Intersections with the Immune System, Inflammation, and the Coagulation System
    Rajput S, Malviya R, Srivastava S, Ahmad I, Obaidur Rab S, Uniyal P
    Ann Pharm Fr, 2024 Aug 17.
    PMID: 39159826 DOI: 10.1016/j.pharma.2024.08.005
    The coagulation and immune system, both essential physiological systems in the human body, are intricately interconnected and play a critical role in determining the overall health of patients. These systems collaborate via various shared regulatory pathways, such as the Tissue Factor (TF) Pathway. Immunological cells that express TF and generate pro-inflammatory cytokines have the ability to affect coagulation. Conversely, coagulation factors and processes have a reciprocal effect on immunological responses by stimulating immune cells and regulating their functions. These interconnected pathways play a role in both preserving well-being and contributing to a range of pathological disorders. The close relationship between blood clotting and inflammation in the development of vascular disease has become a central focus of clinical study. This research specifically examines the crucial elements of this interaction within the contexts of cardiovascular disease and acute coronary syndrome. Tissue factor, the primary trigger of the extrinsic coagulation pathway, has a crucial function by inducing a proinflammatory reaction through the activation of coagulation factors. This, in turn, initiates coagulation and subsequent cellular signalling pathways. Protease-activated receptors establish the molecular connection between coagulation and inflammation by interacting with activated clotting factors II, X, and VII. Thrombosis, a condition characterised by the formation of blood clots, is the most dreaded consequence of cardiovascular disorders and a leading cause of death globally. Consequently, it poses a significant challenge to healthcare systems. Antithrombotic treatments efficiently target platelets and the coagulation cascade, but they come with the inherent danger of causing bleeding. Furthermore, antithrombotics are unable to fully eliminate thrombotic events, highlighting a treatment deficiency caused by a third mechanism that has not yet been sufficiently addressed, namely inflammation. Understanding these connections may aid in the development of novel approaches to mitigate the harmful mutual exacerbation of inflammation and coagulation. Gaining a comprehensive understanding of the intricate interaction among these systems is crucial for the management of diseases and the creation of efficacious remedies. Through the examination of these prevalent regulatory systems, we can discover novel therapeutic approaches that specifically target these complex illnesses. This paper provides a thorough examination of the reciprocal relationship between the coagulation and immune systems, emphasising its importance in maintaining health and understanding disease processes. This review examines the interplay between inflammation and thrombosis and its role in the development of thrombotic disorders.
  7. 3D Printed Nanosensors for Cancer Diagnosis: Advances and Future Perspective
    Gupta B, Malviya R, Srivastava S, Ahmad I, Rab SO, Singh DP
    Curr Pharm Des, 2024 Aug 16.
    PMID: 39161144 DOI: 10.2174/0113816128322300240725052530
    Cancer is the leading cause of mortality worldwide, requiring continuous advancements in diagnosis and treatment. Traditional methods often lack sensitivity and specificity, leading to the need for new methods. 3D printing has emerged as a transformative tool in cancer diagnosis, offering the potential for precise and customizable nanosensors. These advancements are critical in cancer research, aiming to improve early detection and monitoring of tumors. In current times, the usage of the 3D printing technique has been more prevalent as a flexible medium for the production of accurate and adaptable nanosensors characterized by exceptional sensitivity and specificity. The study aims to enhance early cancer diagnosis and prognosis by developing advanced 3D-printed nanosensors using 3D printing technology. The research explores various 3D printing techniques, design strategies, and functionalization strategies for cancer-specific biomarkers. The integration of these nanosensors with detection modalities like fluorescence, electrochemical, and surface-enhanced Raman spectroscopy is also evaluated. The study explores the use of inkjet printing, stereolithography, and fused deposition modeling to create nanostructures with enhanced performance. It also discusses the design and functionalization methods for targeting cancer indicators. The integration of 3D-printed nanosensors with multiple detection modalities, including fluorescence, electrochemical, and surface-enhanced Raman spectroscopy, enables rapid and reliable cancer diagnosis. The results show improved sensitivity and specificity for cancer biomarkers, enabling early detection of tumor indicators and circulating cells. The study highlights the potential of 3D-printed nanosensors to transform cancer diagnosis by enabling highly sensitive and specific detection of tumor biomarkers. It signifies a pivotal step forward in cancer diagnostics, showcasing the capacity of 3D printing technology to produce advanced nanosensors that can significantly improve early cancer detection and patient outcomes.
  8. Fulltext Headspace Extraction of Chlorobenzenes from Water Using Electrospun Nanofibers Fabricated with Calix[4]arene-Doped Polyurethane-Polysulfone
    Najarzadekan H, Kamboh MA, Sereshti H, Ahmad I, Sridewi N, Shahabuddin S, et al.
    Polymers (Basel), 2022 Sep 08;14(18).
    PMID: 36145908 DOI: 10.3390/polym14183760
    Chlorobenzenes (CBs) are persistent and potentially have a carcinogenic effect on mammals. Thus, the determination of CBs is essential for human health. Hence, in this study, novel polyurethane−polysulfone/calix[4]arene (PU-PSU/calix[4]arene) nanofibers were synthesized using an electrospinning approach over in-situ coating on a stainless-steel wire. The nanosorbent was comprehensively characterized using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR) techniques. The SEM analysis depicted the nanofiber’s unique morphology and size distribution in the range of 50−200 nm. To determine the levels of 1,2,4-trichlorobenzene, 1,2,3-trichlorobenzene, and 1,2,3,4-tetrachlorobenzene in water samples, freshly prepared nanosorbent was employed using headspace-solid phase microextraction (HS-SPME) in combination with gas chromatography micro electron capture detector (GC-µECD). Other calixarenes, such as sulfonated calix[4]arene, p-tert-calixarene, and calix[6]arene were also examined, and among the fabricated sorbents, the PU−PSU/calix[4]arene showed the highest efficiency. The key variables of the procedure, including ionic strength, extraction temperature, extraction duration, and desorption conditions were examined. Under optimal conditions, the LOD (0.1−1.0 pg mL−1), the LDR (0.4−1000 pg mL−1), and the R2 > 0.990 were determined. Additionally, the repeatability from fiber to fiber and the intra-day and inter-day reproducibility were determined to be 1.4−6.0, 4.7−10.1, and 0.9−9.7%, respectively. The nanofiber adsorption capacity was found to be 670−720 pg/g for CBs at an initial concentration of 400 pg mL−1. A satisfactory recovery of 80−106% was attained when the suggested method’s application for detecting chlorobenzenes (CBs) in tap water, river water, sewage water, and industrial water was assessed.
  9. Fulltext Superhydrophobic Nanosilica Decorated Electrospun Polyethylene Terephthalate Nanofibers for Headspace Solid Phase Microextraction of 16 Organochlorine Pesticides in Environmental Water Samples
    Najarzadekan H, Sereshti H, Ahmad I, Shahabuddin S, Rashidi Nodeh H, Sridewi N
    Polymers (Basel), 2022 Sep 05;14(17).
    PMID: 36080757 DOI: 10.3390/polym14173682
    A new solid phase micro extraction (SPME) fiber coating composed of electrospun polyethylene terephthalate (PET) nanofibrous mat doped with superhydrophobic nanosilica (SiO2) was coated on a stainless-steel wire without the need of a binder. The coating was characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectrometer (FTIR) techniques and it was used in headspace-SPME of 16 organochlorine pesticides in water samples prior to gass chromatography micro electron capture detector (GC-µECD) analysis. The effects of main factors such as adsorption composition, electrospinning flow rate, salt concentration, extraction temperature, extraction time, and desorption conditions were investigated. Under the optimum conditions, the linear dynamic range (8−1000 ng L−1, R2 > 0.9907), limits of detection (3−80 ng L−1), limits of quantification (8−200 ng L−1), intra-day and inter-day precisions (at 400 and 1000 ng L−1, 1.7−13.8%), and fiber-to-fiber reproducibility (2.4−13.4%) were evaluated. The analysis of spiked tap, sewage, industrial, and mineral water samples for the determination of the analytes resulted in satisfactory relative recoveries (78−120%).
  10. Fulltext Resistance patterns, prevalence, and predictors of fluoroquinolones resistance in multidrug resistant tuberculosis patients
    Ahmad N, Javaid A, Sulaiman SA, Ming LC, Ahmad I, Khan AH
    Braz J Infect Dis, 2016;20(1):41-7.
    PMID: 26626164 DOI: 10.1016/j.bjid.2015.09.011
    BACKGROUND: Fluoroquinolones are the backbone of multidrug resistant tuberculosis treatment regimens. Despite the high burden of multidrug resistant tuberculosis in the country, little is known about drug resistance patterns, prevalence, and predictors of fluoroquinolones resistance among multidrug resistant tuberculosis patients from Pakistan.

    OBJECTIVE: To evaluate drug resistance patterns, prevalence, and predictors of fluoroquinolones resistance in multidrug resistant tuberculosis patients.

    METHODS: This was a cross-sectional study conducted at a programmatic management unit of drug resistant tuberculosis, Lady Reading Hospital Peshawar, Pakistan. Two hundred and forty-three newly diagnosed multidrug resistant tuberculosis patients consecutively enrolled for treatment at study site from January 1, 2012 to July 28, 2013 were included in the study. A standardized data collection form was used to collect patients' socio-demographic, microbiological, and clinical data. SPSS 16 was used for data analysis.

    RESULTS: High degree of drug resistance (median 5 drugs, range 2-8) was observed. High proportion of patients was resistant to all five first-line anti-tuberculosis drugs (62.6%), and more than half were resistant to second line drugs (55.1%). The majority of the patients were ofloxacin resistant (52.7%). Upon multivariate analysis previous tuberculosis treatment at private (OR=1.953, p=0.034) and public private mix (OR=2.824, p=0.046) sectors were predictors of ofloxacin resistance.

    CONCLUSION: The high degree of drug resistance observed, particularly to fluoroquinolones, is alarming. We recommend the adoption of more restrictive policies to control non-prescription sale of fluoroquinolones, its rational use by physicians, and training doctors in both private and public-private mix sectors to prevent further increase in fluoroquinolones resistant Mycobacterium tuberculosis strains.

  11. Fulltext Metabolic associated fatty liver disease (MAFLD): assessing the knowledge and practice of primary care doctors in Seremban District, Negeri Sembilan
    Vijan K, Ali A, Mohamed Idrus NA, Lourdesamy P, Margammuthu S, Perumal S, et al.
    Malays Fam Physician, 2024;19:51.
    PMID: 39220239 DOI: 10.51866/oa.629
    INTRODUCTION: Metabolic-associated fatty liver disease (MAFLD) is the liver manifestation of metabolic syndrome, which is commonly seen in primary care settings. This study aimed to determine the knowledge and practice of primary care physicians regarding MAFLD in Seremban District, Negeri Sembilan.

    METHODS: This cross-sectional study was conducted among medical officers in 14 health clinics in Seremban District, using a validated, self-administered online questionnaire.

    RESULTS: A total of 240 medical officers from 14 health clinics in Seremban District, participated in this study. Most participants (85.4%) passed the knowledge test. Their practice was acceptable, but only a minority were familiar with non-invasive testing of liver fibrosis (e.g. APRI or FIB-4), medication and specific diet for the treatment of MAFLD.

    CONCLUSION: Most primary care physicians in Seremban District are knowledgeable in identifying risk factors and managing patients with MAFLD. However, there are still areas to improve in terms of management, particularly regarding the use of silymarin, vitamin E and pioglitazone.

  12. Labour induction with randomized comparison of oral and intravaginal misoprostol in post date multigravida women
    Ayaz A, Saeed S, Farooq MU, Ahmad I, Ali Bahoo ML, Saeed M
    Malays J Med Sci, 2009 Jan;16(1):34-8.
    PMID: 22589646
    The efficacy and safety of oral versus vaginal misoprostol for elective induction of labor in post date multigravida with an unfavourable cervix was compared over a period of one year in the Bahawal Victoria Hospital, Bahawalpur, Pakistan. Eightyeight multigravida post date women were divided into two groups and given 50 mg misoprostol orally and 50 mg intravaginally, respectively. The induction to onset of significant uterine contractions and delivery intervals were lower in the first group (7.8 h vs. 8.9 h) when compared to (10.4 h vs. 12 h). The first group had a higher rate of Caesarean section (7% vs. 4%; p>0.05), uterine hyperstimulation (9% vs. 5%; p>0.05), uterine tachysystole (23% vs. 14%; p>0.05) and neonatal admissions to intensive care unit (12% vs. 4%; p>0.05) when compared to second group. Fifty mg oral misoprostol has the potential to induce labor as safely and effectively as the intravaginal route.
  13. Emerging Drug Use Trends in Kelantan, Malaysia
    Desrosiers A, Chooi WT, Zaharim NM, Ahmad I, Mohd Yasin MA, Syed Jaapar SZ, et al.
    J Psychoactive Drugs, 2016 05 25;48(3):218-26.
    PMID: 27224011 DOI: 10.1080/02791072.2016.1185553
    The primarily rural and agrarian Kelantan province of Malaysia has high rates of drug use and is characterized by unique sociocultural factors. Combining qualitative and ethnographic methods, we investigated drug use and treatment needs of people who use drugs (PWUD) in rural areas of Kelantan. In February 2014, field visits, participant observation, and focus group discussions (FGDs) with 27 active PWUD were conducted in rural areas surrounding the capital city of Kelantan. The findings indicate a high prevalence of opiate and amphetamine type stimulants (ATS) use in these areas. FGD participants reported initiating drug use at early ages due to peer influences, to relieve boredom, to cope with problems, and a high saturation of villages with other PWUD was reported as a major contributor to their own continued drug use. They reported a trend of drug use initiation at younger ages and increased drug use among females. Participants were interested in treatment; however, their limited knowledge about treatment options and perceived limited availability of services were barriers to treatment seeking. Easy access to drugs, primarily from Thailand and facilitated by the use of mobile phones, resulted in an expanding prevalence of drug use that underscores the need to bolster education and prevention efforts and accessibility of treatment services in Kelantan.
  14. Comparative secondary metabolites profiling and biological activities of aerial, stem and root parts of Salvadora oleoides decne (Salvadoraceae)
    Saleem H, Ahmad I, Zengin G, Mahomoodally FM, Rehman Khan KU, Ahsan HM, et al.
    Nat Prod Res, 2020 Dec;34(23):3373-3377.
    PMID: 30678488 DOI: 10.1080/14786419.2018.1564299
    In this study, different parts (aerial, stem and root) of Salvadora oleoides Decne were investigated in order to explore their phytochemical composition and biological potential. The bioactive contents were evaluated by conventional spectrophotometric methods. Additionally, the secondary metabolite compounds were identified by UHPLC-MS analysis. Biological potential was evaluated by determining antioxidant (DPPH, FRAP, and Phosphomolybdenum) and enzyme inhibitory (butrylcholinesterase and lipoxygenase) effects. Higher total bioactive contents were found in methanolic extracts which tend to correlate with higher radical scavenging and reducing potential of these extracts. LC/MS spectrum revealed the presence of 16 different secondary metabolites belonging to terpene, glucoside and sesquiterpenoid dervivatives. Glucocleomin and emotin A were the main compounds present in all three parts. The strongest butrylcholinesterase and lipoxygenase inhibitory activity was observed for root and stem DCM extracts. Demonstrated biological potential of S. oleoides plant can trace a new road map for developing newly designed bioactive pharmaceuticals.
  15. Fulltext Treatment Outcomes of Extensively Drug-Resistant Tuberculosis in Pakistan: A Countrywide Retrospective Record Review
    Abubakar M, Ahmad N, Ghafoor A, Latif A, Ahmad I, Atif M, et al.
    Front Pharmacol, 2021;12:640555.
    PMID: 33867989 DOI: 10.3389/fphar.2021.640555
    Background: The current study is conducted with the aim to the fill the gap of information regarding treatment outcomes and variables associated with unsuccessful outcome among XDR-TB patients from Pakistan. Methods: A total of 404 culture confirmed XDR-TB patients who received treatment between 1st May 2010 and June 30, 2017 at 27 treatment centers all over Pakistan were retrospectively followed until their treatment outcomes were reported. A p-value <0.05 reflected a statistical significant association. Results: The patients had a mean age 32.9 ± 14.1 years. The overall treatment success rate was 40.6% (95% confidence interval [CI]:35.80-45.60%). A total of 155 (38.4%) patients were declared cured, 9 (2.2%) completed treatment, 149 (36.9%) died, 60 (14.9%) failed treatment and 31 (7.7%) were lost to follow up (LTFU). The results of the multivariate binary logistic regression analysis revealed that the patients' age of >60 years (OR = 4.69, 95%CI:1.57-15.57) and receiving high dose isoniazid (OR = 2.36, 95%CI:1.14-4.85) had statistically significant positive association with death, whereas baseline body weight >40 kg (OR = 0.43, 95%CI:0.25-0.73) and sputum culture conversion in the initial two months of treatment (OR = 0.33, 95%CI:0.19-0.58) had statistically significant negative association with death. Moreover, male gender had statistically significant positive association (OR = 1.92, 95%CI:1.04-3.54) with LTFU. Conclusion: The treatment success rate (40.6%) of XDR-TB patients in Pakistan was poor. Providing special attention and enhanced clinical management to patients with identified risk factors for death and LTFU in the current cohort may improve the treatment outcomes.
  16. New insights into the phytochemical composition, enzyme inhibition and antioxidant properties of desert cotton (Aerva javanica (Bum.f) Shult. -Amaranthaceae)
    Saleem H, Zengin G, Khan KU, Ahmad I, Waqas M, Mahomoodally FM, et al.
    Nat Prod Res, 2021 Feb;35(4):664-668.
    PMID: 30919661 DOI: 10.1080/14786419.2019.1587427
    This study sets out to probe into total bioactive contents, UHPLC-MS secondary metabolites profiling, antioxidant (DPPH, ABTS, FRAP, CUPRAC, phosphomolybdenum and metal chelating) and enzyme inhibitory (acetylcholinesterase- AChE, butyrylcholinesterase- BChE, α-amylase, α glucosidase, and tyrosinase) activities of methanol extract of Aerva javanica, also known as desert cotton or Kapok bush. Aerva javanica contains considerable phenolic (44.79 ± 3.12 mg GAE/g) and flavonoid (28.86 ± 0.12 mg QE/g) contents which tends to correlate with its significant antioxidant potential for ABTS, FRAP and CUPRAC assays with values of 101.41 ± 1.18, 124.10 ± 1.71 and 190.22 ± 5.70 mg TE/g, respectively. The UHPLC-MS analysis identified the presence of 45 phytochemicals belonging to six major groups: phenolic, flavonoids, lignin, terpenes, glycoside and alkaloid. Moreover, the plant extract also showed potent inhibitory action against AChE (3.73 ± 0.22 mg GALAE/g), BChE (3.31 ± 0.19 mg GALAE/g) and tyrosinase (126.05 ± 1.77 mg KAE/g). The observed results suggest A. javanica could be further explored as a natural source of bioactive compounds.
  17. Dye degradation, antibacterial and in-silico analysis of Mg/cellulose-doped ZnO nanoparticles
    Ikram M, Mahmood A, Haider A, Naz S, Ul-Hamid A, Nabgan W, et al.
    Int J Biol Macromol, 2021 Aug 31;185:153-164.
    PMID: 34157328 DOI: 10.1016/j.ijbiomac.2021.06.101
    Various concentrations of Mg into fixed amount of cellulose nanocrystals (CNC)-doped ZnO were synthesized using facile chemical precipitation. The aim of present study is to remove dye degradation of methylene blue (MB) and bactericidal behavior with synthesized product. Phase constitution, functional group analysis, optical behavior, elemental composition, morphology and microstructure were examined using XRD, FTIR, UV-Vis spectrophotometer, EDS and HR-TEM. Highly efficient photocatalytic performance was observed in basic medium (98%) relative to neutral (65%), and acidic (83%) was observed upon Mg and CNC co-doping. Significant bactericidal activity of doped ZnO nanoparticles depicted inhibition zones for G -ve and +ve bacteria ranging (2.20 - 4.25 mm) and (5.80-7.25 mm) for E. coli and (1.05 - 2.75 mm) and (2.80 - 4.75 mm) for S. aureus at low and high doses, respectively. Overall, doped nanostructures showed significant (P 
  18. Emotional Regulation as a Remedy for Teacher Burnout in Special Schools: Evaluating School Climate, Teacher's Work-Life Balance and Children Behavior
    Mulyani S, Salameh AA, Komariah A, Timoshin A, Hashim NAAN, Fauziah RSP, et al.
    Front Psychol, 2021;12:655850.
    PMID: 34326792 DOI: 10.3389/fpsyg.2021.655850
    This research aimed to identify whether improvement in working conditions, children's classroom behavior and work-life balance can lower teacher burnout ratio in Pakistan's special schools by using techniques such as emotions regulation. The researcher employed a quantitative research methodology to fulfill the research's purpose. The data for this research was collected using a questionnaire-based instrument. The confirmatory factor analysis and structural equation modeling techniques were used to test the construct validity and underlying structural relationships. The findings demonstrated that the impacts of all three variables are significant in reducing job burnout in teachers. Emotional regulation helps decrease the impact of working conditions and the children's behavior. Nevertheless, it does not aid work-life balance as it requires other techniques of emotional regulation. The research is significant as it highlights the importance of overall working conditions' improvement for teachers working with special needs children. The improvements are essential because the teachers must take extra effort and emotions into their job compared to a typical teacher. The researcher has highlighted the key finding, implications and limitations of this research besides suggesting directions for future research to facilitate peer researchers.
  19. A comprehensive phytochemical, biological, toxicological and molecular docking evaluation of Suaeda fruticosa (L.) Forssk.: An edible halophyte medicinal plant
    Saleem H, Khurshid U, Sarfraz M, Tousif MI, Alamri A, Anwar S, et al.
    Food Chem Toxicol, 2021 Aug;154:112348.
    PMID: 34144099 DOI: 10.1016/j.fct.2021.112348
    Suaeda fruticosa is an edible medicinal halophyte known for its traditional uses. In this study, methanol and dichloromethane extracts of S. fruticosa were explored for phytochemical, biological and toxicological parameters. Total phenolic and flavonoid constituents were determined by using standard aluminum chloride and Folin-Ciocalteu methods, and UHPLC-MS analysis of methanol extract was performed for tentative identification of secondary metabolites. Different standard methods like DPPH, ABTS, FRAP, CUPRAC, total antioxidant capacity (TAC), and metal chelation assays were utilized to find out the antioxidant potential of extracts. Enzyme inhibition studies of extracts against acetylcholinesterase, butyrylcholinesterase, tyrosinase, α-amylase and, α-glucosidase enzymes were also studied. Likewise, the cytotoxicity was also assessed against MCF-7, MDA-MB-231, and DU-145 cell lines. The higher phenolic and flavonoids contents were observed in methanol extracts which can be correlated to its higher radical scavenging potential. Similarly, 11 different secondary metabolites were tentatively identified by UHPLC profiling. Both the extract showed significant inhibition against all the enzymes except for α-glucosidase. Moreover, docking studies were also performed against the tested enzymes. In the case of cytotoxicity, both the samples were found moderately toxic against the tested cell lines. This plant can be explored further for its potential therapeutic and edible uses.
  20. Fulltext Development of Waste Polystyrene-Based Copper Oxide/Reduced Graphene Oxide Composites and Their Mechanical, Electrical and Thermal Properties
    Ahmad W, Ahmad Q, Yaseen M, Ahmad I, Hussain F, Mohamed Jan B, et al.
    Nanomaterials (Basel), 2021 Sep 13;11(9).
    PMID: 34578688 DOI: 10.3390/nano11092372
    The current study reports the effect of different wt. ratios of copper oxide nanoparticle (CuO-NPs) and reduced graphene oxide (rGO) as fillers on mechanical, electrical, and thermal properties of waste polystyrene (WPS) matrix. Firstly, thin sheets of WPS-rGO-CuO composites were prepared through solution casting method with different ratios, i.e., 2, 8, 10, 15 and 20 wt.% of CuO-NPs and rGO in WPS matrix. The synthesized composite sheets were characterized by Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray (EDX), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM) and thermal gravimetric analysis (TGA). The electrical conductance and mechanical strength of the prepared composites were determined by using LCR meter and universal testing machine (UTM). These properties were dependent on the concentrations of CuO-NPs and rGO. Results display that the addition of both fillers, i.e., rGO and CuO-NPs, collectively led to remarkable increase in the mechanical properties of the composite. The incorporation of rGO-CuO: 15% WPS sample, i.e., WPS-rGO-CuO: 15%, has shown high mechanical strength with tensile strength of 25.282 MPa and Young modulus of 1951.0 MPa, respectively. Similarly, the electrical conductance of the same composite is also enhanced from 6.7 × 10-14 to 4 × 10-7 S/m in contrast to WPS at 2.0 × 106 Hz. The fabricated composites exhibited high thermal stability through TGA analysis in terms of 3.52% and 6.055% wt. loss at 250 °C as compared to WPS.
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