Displaying publications 1 - 20 of 68 in total

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  1. Fulltext Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels
    Al-Samman AM, Azmi MH, Rahman TA, Khan I, Hindia MN, Fattouh A
    PLoS One, 2016;11(12):e0164944.
    PMID: 27992445 DOI: 10.1371/journal.pone.0164944
    This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk-1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method.
  2. Fulltext Unraveling the Behavior of Intrinsically Disordered Protein c-Myc: A Study Utilizing Gaussian-Accelerated Molecular Dynamics
    Gunasinghe KKJ, Rahman T, Chee Wezen X
    ACS Omega, 2024 Jan 16;9(2):2250-2262.
    PMID: 38250404 DOI: 10.1021/acsomega.3c05822
    The protein c-Myc is a transcription factor that remains largely intrinsically disordered and is known to be involved in various biological processes and is overexpressed in various cancers, making it an attractive drug target. However, intrinsically disordered proteins such as c-Myc do not show funnel-like basins in their free-energy landscapes; this makes their druggability a challenge. For the first time, we propose a heterodimer model of c-Myc/Max in full length in this work. We used Gaussian-accelerated molecular dynamics (GaMD) simulations to explore the behavior of c-Myc and its various regions, including the transactivation domain (TAD) and the basic helix-loop-helix-leucine-zipper (bHLH-Zipper) motif in three different conformational states: (a) monomeric c-Myc, (b) c-Myc when bound to its partner protein, Max, and (c) when Max was removed after binding. We analyzed the GaMD trajectories using root-mean-square deviation (RMSD), radius of gyration, root-mean-square fluctuation, and free-energy landscape (FEL) calculations to elaborate the behaviors of these regions. The results showed that the monomeric c-Myc structure showed a higher RMSD fluctuation as compared with the c-Myc/Max heterodimer in the bHLH-Zipper motif. This indicated that the bHLH-Zipper motif of c-Myc is more stable when it is bound to Max. The TAD region in both monomeric and Max-bound states showed similar plasticity in terms of RMSD. We also conducted residue decomposition calculations and showed that the c-Myc and Max interaction could be driven mainly by electrostatic interactions and the residues Arg299, Ile403, and Leu420 seemed to play important roles in the interaction. Our work provides insights into the behavior of c-Myc and its regions that could support the development of drugs that target c-Myc and other intrinsically disordered proteins.
  3. The unmet need of organ transplantation in Africa
    Awuah WA, Ng JC, Bulut HI, Nazir A, Tenkorang PO, Yarlagadda R, et al.
    Int J Surg, 2023 Mar 01;109(3):519-520.
    PMID: 36927835 DOI: 10.1097/JS9.0000000000000025
  4. Fulltext The state of African surgical research capacity: highlighting the current efforts, challenges, and recommendations - Editorial
    Wireko AA, Ohenewaa Tenkorang P, Tope Adebusoye F, Mehta A, Cheng Ng J, Yaa Asieduwaa O, et al.
    Int J Surg, 2023 Feb 01;109(2):91-93.
    PMID: 36799813 DOI: 10.1097/JS9.0000000000000216
  5. The molecular landscape of neurological disorders: insights from single-cell RNA sequencing in neurology and neurosurgery
    Awuah WA, Ahluwalia A, Ghosh S, Roy S, Tan JK, Adebusoye FT, et al.
    Eur J Med Res, 2023 Nov 16;28(1):529.
    PMID: 37974227 DOI: 10.1186/s40001-023-01504-w
    Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology in neurological and neurosurgical research, revolutionising our comprehension of complex neurological disorders. In brain tumours, scRNA-seq has provided valuable insights into cancer heterogeneity, the tumour microenvironment, treatment resistance, and invasion patterns. It has also elucidated the brain tri-lineage cancer hierarchy and addressed limitations of current models. Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. In epilepsy, scRNA-seq has explored the cellular and molecular heterogeneity underlying the condition, uncovering unique glial subpopulations and dysregulation of the immune system. ScRNA-seq has characterised distinct cellular constituents and responses to spinal cord injury in spinal cord diseases, as well as provided molecular signatures of various cell types and identified interactions involved in vascular remodelling. Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. This review highlights the potential of scRNA-seq in guiding precision medicine approaches, identifying clinical biomarkers, and facilitating therapeutic discovery. However, challenges related to data analysis, standardisation, sample acquisition, scalability, and cost-effectiveness need to be addressed. Despite these challenges, scRNA-seq has the potential to transform clinical practice in neurological and neurosurgical research by providing personalised insights and improving patient outcomes.
  6. Fulltext The importance of pharmacists in modern day surgery - editorial
    Wireko AA, Ohenewaa Tenkorang P, Tope Adebusoye F, Yaa Asieduwaa O, Mehta A, Fosuah Debrah A, et al.
    Int J Surg, 2023 Feb 01;109(2):88-90.
    PMID: 36799812 DOI: 10.1097/JS9.0000000000000146
  7. Fulltext The impact of natural disasters on healthcare and surgical services in low- and middle-income countries
    Salam A, Wireko AA, Jiffry R, Ng JC, Patel H, Zahid MJ, et al.
    Ann Med Surg (Lond), 2023 Aug;85(8):3774-3777.
    PMID: 37554857 DOI: 10.1097/MS9.0000000000001041
  8. The African cancer burden: what is the potential role of modern oncology innovation in reducing the continent's rapidly rising mortality?
    Awuah WA, Ng JC, Mehta A, Nansubuga EP, Abdul-Rahman T, Kundu M, et al.
    Postgrad Med J, 2023 Aug 22;99(1175):941-945.
    PMID: 37280156 DOI: 10.1093/postmj/qgad043
    With increasing prevalence and an expected rise in disease burden, cancer is a cause of concern for African healthcare. The cancer burden in Africa is expected to rise to 2.1 million new cases per year and 1.4 million deaths annually by the year 2040. Even though efforts are being made to improve the standard of oncology service delivery in Africa, the current state of cancer care is not yet on par with the rise in the cancer burden. Cutting-edge technologies and innovations are being developed across the globe to augment the battle against cancer; however, many of them are beyond the reach of African countries. Modern oncology innovations targeted to ward Africa would be promising to address the high cancer mortality rates. The innovations should be cost-effective and widely accessible to tackle the rapidly rising mortality rate on the African continent. Though it may seem promising, a multidisciplinary approach is required to overcome the challenges associated with the development and implementation of modern oncology innovations in Africa.
  9. Fulltext Structure-Based Discovery of Lipoteichoic Acid Synthase Inhibitors
    Chee Wezen X, Chandran A, Eapen RS, Waters E, Bricio-Moreno L, Tosi T, et al.
    J Chem Inf Model, 2022 May 23;62(10):2586-2599.
    PMID: 35533315 DOI: 10.1021/acs.jcim.2c00300
    Lipoteichoic acid synthase (LtaS) is a key enzyme for the cell wall biosynthesis of Gram-positive bacteria. Gram-positive bacteria that lack lipoteichoic acid (LTA) exhibit impaired cell division and growth defects. Thus, LtaS appears to be an attractive antimicrobial target. The pharmacology around LtaS remains largely unexplored with only two small-molecule LtaS inhibitors reported, namely "compound 1771" and the Congo red dye. Structure-based drug discovery efforts against LtaS remain unattempted due to the lack of an inhibitor-bound structure of LtaS. To address this, we combined the use of a molecular docking technique with molecular dynamics (MD) simulations to model a plausible binding mode of compound 1771 to the extracellular catalytic domain of LtaS (eLtaS). The model was validated using alanine mutagenesis studies combined with isothermal titration calorimetry. Additionally, lead optimization driven by our computational model resulted in an improved version of compound 1771, namely, compound 4 which showed greater affinity for binding to eLtaS than compound 1771 in biophysical assays. Compound 4 reduced LTA production in S. aureus dose-dependently, induced aberrant morphology as seen for LTA-deficient bacteria, and significantly reduced bacteria titers in the lung of mice infected with S. aureus. Analysis of our MD simulation trajectories revealed the possible formation of a transient cryptic pocket in eLtaS. Virtual screening (VS) against the cryptic pocket led to the identification of a new class of inhibitors that could potentiate β-lactams against methicillin-resistant S. aureus. Our overall workflow and data should encourage further drug design campaign against LtaS. Finally, our work reinforces the importance of considering protein conformational flexibility to a successful VS endeavor.
  10. Fulltext Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks
    Al-Samman AM, Rahman TA, Azmi MH, Hindia MN, Khan I, Hanafi E
    PLoS One, 2016 Sep 21;11(9):e0163034.
    PMID: 27654703 DOI: 10.1371/journal.pone.0163034
    This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios.
  11. Repurposing FDA-approved drugs as HIV-1 integrase inhibitors: an in silico investigation
    Ha CHX, Lee NK, Rahman T, Hwang SS, Yam WK, Chee XW
    J Biomol Struct Dyn, 2023 Apr;41(6):2146-2159.
    PMID: 35067186 DOI: 10.1080/07391102.2022.2028677
    The Human Immunodeficiency Virus (HIV) infection is a global pandemic that has claimed 33 million lives to-date. One of the most efficacious treatments for naïve or pretreated HIV patients is the HIV integrase strand transfer inhibitors (INSTIs). However, given that HIV treatment is life-long, the emergence of HIV strains resistant to INSTIs is an imminent challenge. In this work, we showed two best regression QSAR models that were constructed using a boosted Random Forest algorithm (r2 = 0.998, q210CV = 0.721, q2external_test = 0.754) and a boosted K* algorithm (r2 = 0.987, q210CV = 0.721, q2external_test = 0.758) to predict the pIC50 values of INSTIs. Subsequently, the regression QSAR models were deployed against the Drugbank database for drug repositioning. The top-ranked compounds were further evaluated for their target engagement activity using molecular docking studies and accelerated Molecular Dynamics simulation. Lastly, their potential as INSTIs were also evaluated from our literature search. Our study offers the first example of a large-scale regression QSAR modelling effort for discovering highly active INSTIs to combat HIV infection.Communicated by Ramaswamy H. Sarma.
  12. Fulltext Recent Outcomes and Challenges of Artificial Intelligence, Machine Learning, and Deep Learning in Neurosurgery
    Awuah WA, Adebusoye FT, Wellington J, David L, Salam A, Weng Yee AL, et al.
    World Neurosurg X, 2024 Jul;23:100301.
    PMID: 38577317 DOI: 10.1016/j.wnsx.2024.100301
    Neurosurgeons receive extensive technical training, which equips them with the knowledge and skills to specialise in various fields and manage the massive amounts of information and decision-making required throughout the various stages of neurosurgery, including preoperative, intraoperative, and postoperative care and recovery. Over the past few years, artificial intelligence (AI) has become more useful in neurosurgery. AI has the potential to improve patient outcomes by augmenting the capabilities of neurosurgeons and ultimately improving diagnostic and prognostic outcomes as well as decision-making during surgical procedures. By incorporating AI into both interventional and non-interventional therapies, neurosurgeons may provide the best care for their patients. AI, machine learning (ML), and deep learning (DL) have made significant progress in the field of neurosurgery. These cutting-edge methods have enhanced patient outcomes, reduced complications, and improved surgical planning.
  13. Fulltext QCovSML: A reliable COVID-19 detection system using CBC biomarkers by a stacking machine learning model
    Rahman T, Khandakar A, Abir FF, Faisal MAA, Hossain MS, Podder KK, et al.
    Comput Biol Med, 2022 Apr;143:105284.
    PMID: 35180500 DOI: 10.1016/j.compbiomed.2022.105284
    The reverse transcription-polymerase chain reaction (RT-PCR) test is considered the current gold standard for the detection of coronavirus disease (COVID-19), although it suffers from some shortcomings, namely comparatively longer turnaround time, higher false-negative rates around 20-25%, and higher cost equipment. Therefore, finding an efficient, robust, accurate, and widely available, and accessible alternative to RT-PCR for COVID-19 diagnosis is a matter of utmost importance. This study proposes a complete blood count (CBC) biomarkers-based COVID-19 detection system using a stacking machine learning (SML) model, which could be a fast and less expensive alternative. This study used seven different publicly available datasets, where the largest one consisting of fifteen CBC biomarkers collected from 1624 patients (52% COVID-19 positive) admitted at San Raphael Hospital, Italy from February to May 2020 was used to train and validate the proposed model. White blood cell count, monocytes (%), lymphocyte (%), and age parameters collected from the patients during hospital admission were found to be important biomarkers for COVID-19 disease prediction using five different feature selection techniques. Our stacking model produced the best performance with weighted precision, sensitivity, specificity, overall accuracy, and F1-score of 91.44%, 91.44%, 91.44%, 91.45%, and 91.45%, respectively. The stacking machine learning model improved the performance in comparison to other state-of-the-art machine learning classifiers. Finally, a nomogram-based scoring system (QCovSML) was constructed using this stacking approach to predict the COVID-19 patients. The cut-off value of the QCovSML system for classifying COVID-19 and Non-COVID patients was 4.8. Six datasets from three different countries were used to externally validate the proposed model to evaluate its generalizability and robustness. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.961 for the internal cohort and average AUC of 0.967 for all external validation cohort, respectively. The external validation shows an average weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 92.02%, 95.59%, 93.73%, 90.54%, and 93.34%, respectively.
  14. Fulltext Provision of renal-specific nutrition knowledge for changing dietary practice in Bangladeshi hemodialysis patients
    Rahman T, Ahmed S, Kabir MR, Akhtaruzzaman M, Mitali EJ, Rashid HU, et al.
    PEC Innov, 2022 Dec;1:100028.
    PMID: 37213733 DOI: 10.1016/j.pecinn.2022.100028
    OBJECTIVE: Studies show that provision of nutrition knowledge help renal patients make informed food choices. This study aimed to evaluate the impact of nutrition knowledge for changing dietary practice among Bangladeshi dialysis patients.

    METHODS: Following development of a renal-specific nutrition booklet, a pilot study was conducted among 50 hemodialysis patients from a single dialysis setting. Demographic, anthropometric, clinical, biochemical, dietary data, and a 10-item MCQ on renal-specific nutrition information were collected before and 3 months after the provision of the booklet.

    RESULTS: 52% of the participants were male, 54% had twice weekly dialysis, age 53 ± 12 years, and dialysis vintage was 46 ± 25 months. Serum potassium and phosphorous, dietary potassium, phosphorous, and phosphorous to protein ratio were significantly reduced after the provision of the booklet. Additionally, patients consuming >3 meals/day increased to 66% while adherence to renal-specific cooking method and vegetable preference were significantly increased to 70% and 62%, respectively.

    CONCLUSION: Provision of knowledge via renal-specific nutrition booklet was able to improve patients' dietary practice and enhance their dietary adherence to renal specific recommendations.

    INNOVATION: The booklet was developed using locally available food items in local language and was found beneficial in low-resource settings where overall health care facilities, including nutrition support are limited.

  15. Protein Energy Wasting in a Cohort of Maintenance Hemodialysis Patients in Dhaka, Bangladesh
    Rahman T, Khor BH, Sahathevan S, Kaur D, Latifi E, Afroz M, et al.
    Nutrients, 2022 Apr 01;14(7).
    PMID: 35406082 DOI: 10.3390/nu14071469
    Malnutrition is associated with high rates of mortality among patients with end stage kidney disease (ESKD). There is a paucity of data from Bangladesh, where around 35,000−40,000 people reach ESKD annually. We assessed protein-energy wasting (PEW) amongst 133 patients at a single hemodialysis setting in Dhaka. Patients were 49% male, age 50 ± 13 years, 62% were on twice-weekly hemodialysis. Anthropometric, biochemical, and laboratory evaluations revealed: BMI 24.1 ± 5.2 kg/m2, mid-arm muscle circumference (MAMC) 21.6 ± 3.6 cm, and serum albumin 3.7 ± 0.6 g/dL. Based on published criteria, 18% patients had PEW and for these patients, BMI (19.8 ± 2.4 vs. 25.2 ± 5.2 kg/m2), MAMC (19.4 ± 2.4 vs. 22.2 ± 3.8 cm), serum albumin (3.5 ± 0.7 vs. 3.8 ± 0.5 g/dL), and total cholesterol (135 ± 34 vs. 159 ± 40 mg/dL), were significantly lower as compared to non-PEW patients, while hand grip strength was similar (19.5 ± 7.6 vs. 19.7 ± 7.3 kg). Inflammatory C-reactive protein levels tended to be higher in the PEW group (20.0 ± 34.8 vs. 10.0 ± 13.9 p = 0.065). Lipoprotein analyses revealed PEW patients had significantly lower low density lipoprotein cholesterol (71 ± 29 vs. 88 ± 31 mg/dL, p < 0.05) and plasma triglyceride (132 ± 51 vs. 189 ± 103 mg/dL, p < 0.05), while high density lipoprotein cholesterol was similar. Nutritional assessments using a single 24 h recall were possible from 115 of the patients, but only 66 of these were acceptable reporters. Amongst these, while no major differences were noted between PEW and non-PEW patients, the majority of patients did not meet dietary recommendations for energy, protein, fiber, and several micronutrients (in some cases intakes were 60−90% below recommendations). Malnutrition Inflammation Scores were significantly higher in PEW patients (7.6 ± 3.1 vs. 5.3 ± 2.7 p < 0.004). No discernible differences were apparent in measured parameters between patients on twice- vs. thrice-weekly dialysis. Data from a larger cohort are needed prior to establishing patient-management guidelines for PEW in this population.
  16. Fulltext Postoperative mortality in Africa: are there any improvements in the last decade?
    Awuah WA, Ng JC, Nazir A, Tenkorang PO, Yarlagadda R, Kalmanovich J, et al.
    Int J Surg, 2023 May 01;109(5):1080-1082.
    PMID: 36927691 DOI: 10.1097/JS9.0000000000000125
  17. Fulltext Observational study of the status of coronary risk biomarkers among Negritos with metabolic syndrome in the east coast of Malaysia
    Mokhsin A, Mokhtar SS, Mohd Ismail A, M Nor F, Shaari SA, Nawawi H, et al.
    BMJ Open, 2018 12 04;8(12):e021580.
    PMID: 30518581 DOI: 10.1136/bmjopen-2018-021580
    OBJECTIVES: To determine the prevalence of metabolic syndrome (MS), ascertain the status of coronary risk biomarkers and establish the independent predictors of these biomarkers among the Negritos.

    SETTINGS: Health screening programme conducted in three inland settlements in the east coast of Malaysia and Peninsular Malaysia.

    SUBJECTS: 150 Negritos who were still living in three inland settlements in the east coast of Malaysia and 1227 Malays in Peninsular Malaysia. These subjects were then categorised into MS and non-MS groups based on the International Diabetes Federation (IDF) consensus worldwide definition of MS and were recruited between 2010 and 2015. The subjects were randomly selected and on a voluntary basis.

    PRIMARY AND SECONDARY OUTCOME MEASURES: This study was a cross-sectional study. Serum samples were collected for analysis of inflammatory (hsCRP), endothelial activation (sICAM-1) and prothrombogenesis [lp(a)] biomarkers.

    RESULTS: MS was significantly higher among the Malays compared with Negritos (27.7%vs12.0%). Among the Malays, MS subjects had higher hsCRP (p=0.01) and sICAM-1 (p<0.05) than their non-MS counterpart. There were no significant differences in all the biomarkers between MS and the non-MS Negritos. However, when compared between ethnicity, all biomarkers were higher in Negritos compared with Malays (p<0.001). Binary logistic regression analysis affirmed that Negritos were an independent predictor for Lp(a) concentration (p<0.001).

    CONCLUSIONS: This study suggests that there may possibly be a genetic influence other than lifestyle, which could explain the lack of difference in biomarkers concentration between MS and non-MS Negritos and for Negritos predicting Lp(a).

  18. NeuroVerse: neurosurgery in the era of Metaverse and other technological breakthroughs
    Kundu M, Ng JC, Awuah WA, Huang H, Yarlagadda R, Mehta A, et al.
    Postgrad Med J, 2023 May 22;99(1170):240-243.
    PMID: 36892407 DOI: 10.1093/postmj/qgad002
    The tremendous evolution in modern technology has led to a paradigm shift in neurosurgery. The latest advancements such as augmented reality, virtual reality, and mobile applications have been incorporated into neurosurgical practice. NeuroVerse, representing the application of the metaverse in neurosurgery, brings enormous potential to neurology and neurosurgery. Implementation of NeuroVerse could potentially elevate neurosurgical and interventional procedures, enhance medical visits and patient care, and reshape neurosurgical training. However, it is also vital to consider the challenges that may be associated with its implementation, such as privacy issues, cybersecurity breaches, ethical concerns, and widening of existing healthcare inequalities. NeuroVerse adds phenomenal dimensions to the neurosurgical environment for patients, doctors, and trainees, and represents an incomparable advancement in the delivery of medicine. Therefore, more research is needed to encourage widespread use of the metaverse in healthcare, particularly focusing on the areas of morality and credibility. Although the metaverse is expected to expand rapidly during and after the COVID-19 pandemic, it remains to be seen whether it represents an emerging technology that will revolutionize our society and healthcare or simply an immature condition of the future.
  19. Fulltext Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension
    Hoh BP, Abdul Rahman T, Yusoff K
    Hereditas, 2019;156:1.
    PMID: 30636949 DOI: 10.1186/s41065-019-0080-1
    Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.
  20. Multilevel Pharmacological Effects of Antipsychotics in Potential Glioblastoma Treatment
    Awuah WA, Kalmanovich J, Mehta A, Huang H, Abdul-Rahman T, Cheng Ng J, et al.
    Curr Top Med Chem, 2023;23(5):389-402.
    PMID: 36593538 DOI: 10.2174/1568026623666230102095836
    Glioblastoma Multiforme (GBM) is a debilitating type of brain cancer with a high mortality rate. Despite current treatment options such as surgery, radiotherapy, and the use of temozolomide and bevacizumab, it is considered incurable. Various methods, such as drug repositioning, have been used to increase the number of available treatments. Drug repositioning is the use of FDA-approved drugs to treat other diseases. This is possible because the drugs used for this purpose have polypharmacological effects. This means that these medications can bind to multiple targets, resulting in multiple mechanisms of action. Antipsychotics are one type of drug used to treat GBM. Antipsychotics are a broad class of drugs that can be further subdivided into typical and atypical classes. Typical antipsychotics include chlorpromazine, trifluoperazine, and pimozide. This class of antipsychotics was developed early on and primarily works on dopamine D2 receptors, though it can also work on others. Olanzapine and Quetiapine are examples of atypical antipsychotics, a category that was created later. These medications have a high affinity for serotonin receptors such as 5- HT2, but they can also act on dopamine and H1 receptors. Antipsychotic medications, in the case of GBM, also have other effects that can affect multiple pathways due to their polypharmacological effects. These include NF-B suppression, cyclin deregulation, and -catenin phosphorylation, among others. This review will delve deeper into the polypharmacological, the multiple effects of antipsychotics in the treatment of GBM, and an outlook for the field's future progression.
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