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Fulltext Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images

Rahman T, Khandakar A, Qiblawey Y, Tahir A, Kiranyaz S, Abul Kashem SB, et al.

Comput Biol Med, 2021 May;132:104319.
PMID: 33799220 DOI: 10.1016/j.compbiomed.2021.104319

Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest X-ray (CXR) imaging has several advantages over other imaging and detection techniques. Numerous works have been reported on COVID-19 detection from a smaller set of original X-ray images. However, the effect of image enhancement and lung segmentation of a large dataset in COVID-19 detection was not reported in the literature. We have compiled a large X-ray dataset (COVQU) consisting of 18,479 CXR images with 8851 normal, 6012 non-COVID lung infections, and 3616 COVID-19 CXR images and their corresponding ground truth lung masks. To the best of our knowledge, this is the largest public COVID positive database and the lung masks. Five different image enhancement techniques: histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE), image complement, gamma correction, and balance contrast enhancement technique (BCET) were used to investigate the effect of image enhancement techniques on COVID-19 detection. A novel U-Net model was proposed and compared with the standard U-Net model for lung segmentation. Six different pre-trained Convolutional Neural Networks (CNNs) (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, and ChexNet) and a shallow CNN model were investigated on the plain and segmented lung CXR images. The novel U-Net model showed an accuracy, Intersection over Union (IoU), and Dice coefficient of 98.63%, 94.3%, and 96.94%, respectively for lung segmentation. The gamma correction-based enhancement technique outperforms other techniques in detecting COVID-19 from the plain and the segmented lung CXR images. Classification performance from plain CXR images is slightly better than the segmented lung CXR images; however, the reliability of network performance is significantly improved for the segmented lung images, which was observed using the visualization technique. The accuracy, precision, sensitivity, F1-score, and specificity were 95.11%, 94.55%, 94.56%, 94.53%, and 95.59% respectively for the segmented lung images. The proposed approach with very reliable and comparable performance will boost the fast and robust COVID-19 detection using chest X-ray images.
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.
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.
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.
Diabetes-associated macrovasculopathy: pathophysiology and pathogenesis

Rahman S, Rahman T, Ismail AA, Rashid AR

Diabetes Obes Metab, 2007 Nov;9(6):767-80.
PMID: 17924861 DOI: 10.1111/j.1463-1326.2006.00655.x

The complications associated with diabetic vasculopathy are commonly grouped into two categories: microvascular and macrovascular complications. In diabetes, macrovascular disease is the commonest cause of mortality and morbidity and is responsible for high incidence of vascular diseases such as stroke, myocardial infarction and peripheral vascular diseases. Macrovascular diseases are traditionally thought of as due to underlying obstructive atherosclerotic diseases affecting major arteries. Pathological changes of major blood vessels leading to functional and structural abnormalities in diabetic vessels include endothelial dysfunction, reduced vascular compliance and atherosclerosis. Besides, advanced glycation end product formation interacts with specific receptors that lead to overexpression of a range of cytokines. Haemodynamic pathways are activated in diabetes and are possibly amplified by concomitant systemic hypertension. Apart from these, hyperglycaemia, non-enzymatic glycosylation, lipid modulation, alteration of vasculature and growth factors activation contribute to development of diabetic vasculopathy. This review focuses on pathophysiology and pathogenesis of diabetes-associated macrovasculopathy.
Effects of prolonged isolation in a confined space on status of oxidative stress and prothrombogenesis: In preparation for possible future manned space expedition to Mars

Muid S, Abu Bakar NA, Abdul Rahman T, Tengku Ismail TS, Kholin SF, Suvorov AV, et al.

Malays J Pathol, 2019 Dec;41(3):283-292.
PMID: 31901913

INTRODUCTION: Apart from inflammation and endothelial dysfunction, other key components in the development of atherogenesis include prothrombogenesis and oxidative stress. The effects of long-term confinement and isolation, exposure to radiation and different gravity forces during space travel could potentially increase the long-term risk of atherosclerosis. To the best of our knowledge, this is the first study determining the status of prothrombogenesis and oxidative stress in six cosmonauts subjected to the longest duration of confined isolation period of 520 days in preparation for prospective undetermined manned space travel to Mars.
MATERIALS AND METHODS: This collaborative research between the National Space Agency (ANGKASA), Universiti Teknologi MARA, Malaysia and Institute of Biomedical Problems (IBMP), Russia was conducted at the Russian Academy of Sciences IBMP, Moscow, Russia. Six multi-national cosmonauts were assigned to live in a ground-based confined module for 520 days. Standard exercise and diet regime were instituted throughout the isolation phase. Six age, ethnic and gender-matched healthy, free-living ground controls were recruited in parallel. Serial serum and whole blood were analysed for biomarkers of prothrombogenesis [plasminogen activator inhibitor-1 (PAI-1) and homocysteine] and oxidative stress [oxidised low-density lipoprotein (ox-LDL) and malondialdehyde (MDA)].
RESULTS: There were significantly lower concentrations of PAI-1 and homocysteine in cosmonauts during confinement compared to the controls. There were no significant differences seen in the concentrations of biomarkers of oxidative stress during confinement but there was a significant percentage change increment for serum MDA in cosmonauts.
CONCLUSION: Long-term confinement decreased the risk of prothrombogenesis and this could be attributed to the exercise and diet regime which includes omega-3 fatty acids supplementation given to the crew members during their confinement period. However, oxidative damage could not be excluded and may be attributed to the influence of psychological stress during this prolonged confinement.
Fulltext Delta- and gamma-tocotrienol isomers are potent in inhibiting inflammation and endothelial activation in stimulated human endothelial cells

Muid S, Froemming GR, Rahman T, Ali AM, Nawawi HM

Food Nutr Res, 2016;60:31526.
PMID: 27396399 DOI: 10.3402/fnr.v60.31526

BACKGROUND: Tocotrienols (TCTs) are more potent antioxidants than α-tocopherol (TOC). However, the effectiveness and mechanism of the action of TCT isomers as anti-atherosclerotic agents in stimulated human endothelial cells under inflammatory conditions are not well established.
AIMS: 1) To compare the effects of different TCT isomers on inflammation, endothelial activation, and endothelial nitric oxide synthase (eNOS). 2) To identify the two most potent TCT isomers in stimulated human endothelial cells. 3) To investigate the effects of TCT isomers on NFκB activation, and protein and gene expression levels in stimulated human endothelial cells.
METHODS: Human umbilical vein endothelial cells were incubated with various concentrations of TCT isomers or α-TOC (0.3-10 µM), together with lipopolysaccharides for 16 h. Supernatant cells were collected and measured for protein and gene expression of cytokines (interleukin-6, or IL-6; tumor necrosis factor-alpha, or TNF-α), adhesion molecules (intercellular cell adhesion molecule-1, or ICAM-1; vascular cell adhesion molecule-1, or VCAM-1; and e-selectin), eNOS, and NFκB.
RESULTS: δ-TCT is the most potent TCT isomer in the inhibition of IL-6, ICAM-1, VCAM-1, and NFκB, and it is the second potent in inhibiting e-selectin and eNOS. γ-TCT isomer is the most potent isomer in inhibiting e-selectin and eNOS, and it is the second most potent in inhibiting is IL-6, VCAM-1, and NFκB. For ICAM-1 protein expression, the most potent is δ-TCT followed by α-TCT. α- and β-TCT inhibit IL-6 at the highest concentration (10 µM) but enhance IL-6 at lower concentrations. γ-TCT markedly increases eNOS expression by 8-11-fold at higher concentrations (5-10 µM) but exhibits neutral effects at lower concentrations.
CONCLUSION: δ- and γ-TCT are the two most potent TCT isomers in terms of the inhibition of inflammation and endothelial activation whilst enhancing eNOS, possibly mediated via the NFκB pathway. Hence, there is a great potential for TCT isomers as anti-atherosclerotic agents.
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).
Fulltext Comparable Enhanced Prothrombogenesis in Simple Central Obesity and Metabolic Syndrome

Mohd Nor NS, Saimin H, Rahman T, Abdul Razak S, Mohd Nasir N, Ismail Z, et al.

J Obes, 2018;2018:8508549.
PMID: 29785305 DOI: 10.1155/2018/8508549

Objective: There is limited data comparing prothrombogenic or fibrinolysis biomarkers (tissue plasminogen activator (tPA) and plasminogen activator inhibitor-1 (PAI-1)) simultaneously in subjects with Metabolic Syndrome (MS), simple central obesity without MS (COB) and normal controls (NC). We investigated the concentrations of fibrinolysis biomarkers in subjects with MS, COB and NC.
Methods: A cross-sectional study involving 503 drug naive subjects (163 males, aged 30-65 years old (mean age ± SD = 47.4 ± 8.3 years)) divided into MS, COB and NC groups. COB was defined as central obesity (waist circumference (WC) males ≥90 cm, females ≥80 cm) in the absence of MS according to the International Diabetes Federation 2006. Fasting blood levels of tPA and PAI-1were analyzed.
Results: MS and COB had significantly higher concentration of all biomarkers compared to NC. The MS group had significantly higher concentration of tPA and PAI-1 compared to COB. WC and HDL-c had significant correlation with all biomarkers (tPA p < 0.001, PAI-1 p < 0.001). Fasting plasma glucose and diastolic blood pressure were independent predictors after correcting for confounding factors.
Conclusion: Central obesity with or without MS both demonstrated enhanced prothrombogenesis. This suggests that simple obesity possibly increases the risk of coronary artery disease in part, via increased susceptibility to thrombogenesis.
Fulltext Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice

Mohamad N, Ismet RI, Rofiee M, Bannur Z, Hennessy T, Selvaraj M, et al.

J Clin Bioinforma, 2015;5:3.
PMID: 25806102 DOI: 10.1186/s13336-015-0018-4

The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempted to translate the metabolomics model to predict the health status of the Orang Asli community whom we have little information. The metabolite expressions of the healthy vs. diseased patients (cardiovascular) were compared. A metabotype model was developed and validated using partial least square discriminant analysis (PLSDA). Cardiovascular risks of the Orang Asli were predicted and confirmed by biochemistry profiles conducted concurrently.
Embracing robotic surgery in low- and middle-income countries: Potential benefits, challenges, and scope in the future

Mehta A, Cheng Ng J, Andrew Awuah W, Huang H, Kalmanovich J, Agrawal A, et al.

Ann Med Surg (Lond), 2022 Dec;84:104803.
PMID: 36582867 DOI: 10.1016/j.amsu.2022.104803

Robotic surgery has applications in many medical specialties, including urology, general surgery, and surgical oncology. In the context of a widespread resource and personnel shortage in Low- and Middle-Income Countries (LMICs), the use of robotics in surgery may help to reduce physician burnout, surgical site infections, and hospital stays. However, a lack of haptic feedback and potential socioeconomic factors such as high implementation costs and a lack of trained personnel may limit its accessibility and application. Specific improvements focused on improved financial and technical support to LMICs can help improve access and have the potential to transform the surgical experience for both surgeons and patients in LMICs. This review focuses on the evolution of robotic surgery, with an emphasis on challenges and recommendations to facilitate wider implementation and improved patient outcomes.
Fulltext A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals

Mahmud S, Ibtehaz N, Khandakar A, Tahir AM, Rahman T, Islam KR, et al.

Sensors (Basel), 2022 Jan 25;22(3).
PMID: 35161664 DOI: 10.3390/s22030919

Cardiovascular diseases are the most common causes of death around the world. To detect and treat heart-related diseases, continuous blood pressure (BP) monitoring along with many other parameters are required. Several invasive and non-invasive methods have been developed for this purpose. Most existing methods used in hospitals for continuous monitoring of BP are invasive. On the contrary, cuff-based BP monitoring methods, which can predict systolic blood pressure (SBP) and diastolic blood pressure (DBP), cannot be used for continuous monitoring. Several studies attempted to predict BP from non-invasively collectible signals such as photoplethysmograms (PPG) and electrocardiograms (ECG), which can be used for continuous monitoring. In this study, we explored the applicability of autoencoders in predicting BP from PPG and ECG signals. The investigation was carried out on 12,000 instances of 942 patients of the MIMIC-II dataset, and it was found that a very shallow, one-dimensional autoencoder can extract the relevant features to predict the SBP and DBP with state-of-the-art performance on a very large dataset. An independent test set from a portion of the MIMIC-II dataset provided a mean absolute error (MAE) of 2.333 and 0.713 for SBP and DBP, respectively. On an external dataset of 40 subjects, the model trained on the MIMIC-II dataset provided an MAE of 2.728 and 1.166 for SBP and DBP, respectively. For both the cases, the results met British Hypertension Society (BHS) Grade A and surpassed the studies from the current literature.
Erratum to: Differential positive selection of malaria resistance genes in three indigenous populations of Peninsular Malaysia

Liu X, Yunus Y, Lu D, Aghakhanian F, Saw WY, Deng L, et al.

Hum Genet, 2015 Jun;134(6):677.
PMID: 25783005 DOI: 10.1007/s00439-015-1540-y
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.
Fulltext A machine learning model for early detection of diabetic foot using thermogram images

Khandakar A, Chowdhury MEH, Ibne Reaz MB, Md Ali SH, Hasan MA, Kiranyaz S, et al.

Comput Biol Med, 2021 10;137:104838.
PMID: 34534794 DOI: 10.1016/j.compbiomed.2021.104838

Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through education and offloading. Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting.
Identifying Challenges and Potential Solutions for Sustainable Kidney Nutrition Care Delivery in Selected Asian Countries

Karupaiah T, Mat Daud ZA, Khosla P, Khor BH, Sahathevan S, Kaur D, et al.

J Ren Nutr, 2023 Nov;33(6S):S73-S79.
PMID: 37597574 DOI: 10.1053/j.jrn.2023.08.003

BACKGROUND: Recent surveys highlight gross workforce shortage of dietitians in global kidney health and significant gaps in renal nutrition care, with disparities greater in low/low-middle income countries.
OBJECTIVE: This paper narrates ground experiences gained through the Palm Tocotrienols in Chronic Hemodialysis (PaTCH) project on kidney nutrition care scenarios and some Asian low-to-middle-income countries namely Bangladesh, India, and Malaysia.
METHOD: Core PaTCH investigators from 3 universities (USA and Malaysia) were supported by their postgraduate students (n = 17) with capacity skills in kidney nutrition care methodology and processes. This core team, in turn, built capacity for partnering hospitals as countries differed in their ability to deliver dietitian-related activities for dialysis patients.
RESULTS: We performed a structural component analyses of PaTCH affiliated and nonaffiliated (Myanmar and Indonesia) countries to identify challenges to kidney nutrition care. Deficits in patient-centered care, empowerment processes and moderating factors to nutrition care optimization characterized country comparisons. Underscoring these factors were some countries lacked trained dietitians whilst for others generalist dietitians or nonclinical nutritionists were providing patient care. Resolution of some challenges in low-to-middle-income countries through coalition networking to facilitate interprofessional collaboration and task sharing is described.
CONCLUSIONS: We perceive interprofessional collaboration is the way forward to fill gaps in essential dietitian services and regional-based institutional coalitions will facilitate culture-sensitive capacity in building skills. For the long-term an advanced renal nutrition course such as the Global Renal Internet Course for Dietitians is vital to facilitate sustainable kidney nutrition care.
Fulltext Effects of water-based contrast media on experimentally induced established atherosclerotic plaques in rabbits.

Isa MR, Mohd Noor N, Nawawi H, Kaur M., Rahman T, Mohd Kornain NK, et al.

IIUM Medical Journal Malaysia, 2020;19(2):21-28.
MyJurnal

Imaging techniques involving optical coherence tomography, computed tomography (CT) and high-resolution magnetic resonance imaging (MRI) are used as tools to identify atherosclerotic plaques. However, the effects of water-based contrast media used in Post Mortem Computed Tomography Angiography (PMCTA) on the histopathology of atherosclerotic plaques have not been widely explored. The objective of this study is to determine the effects of water-based contrast media used in PMCTA on the histopathology of atherosclerotic plaques and biomarkers of atherosclerosis in experimentally induced established atherosclerotic rabbits. MATERIALS AND METHODS: Twenty male New Zealand white rabbits were divided into 2 groups. One group was given a high cholesterol diet (HCD) for 12 weeks to establish atherosclerosis and the control group normal diet (ND). Five rabbits from each group were then given intravenous water-based contrast media before being sacrificed. The entire length of aorta was dissected and submitted for histopathological examination and determination of tissue biomarkers α-SMA and MMP-9. RESULTS:Histopathological examination of the aorta including percentage of area covered by plaque and foam cell formation showed no significant difference in atheromatous plaque formation in both groups of HCD rabbits with or without intravenous contrast media injection (plaque: 55±41 vs. 63±15, p=0.731; foam cells: 124±83 vs. 171±55, p=0.325). Similarly, α-SMA and MMP-9 protein expression also showed no significant difference in both groups (α-SMA: 70±20 vs. 67±26, p=0.807; MMP-9: 60±12 vs. 57±17, p=0.785). CONCLUSION:Water-based contrast media used in PMCTA does not affect the morphology or the immunohistochemistry staining of SMA and MMP-9 in atherosclerotic plaques.
Fulltext A low-loss and compact single-layer butler matrix for a 5G base station antenna

Idrus II, Abdul Latef T, Aridas NK, Abu Talip MS, Yamada Y, Abd Rahman T, et al.

PLoS One, 2019;14(12):e0226499.
PMID: 31841536 DOI: 10.1371/journal.pone.0226499

Researchers are increasingly showing interest in the application of a Butler matrix for fifth-generation (5G) base station antennas. However, the design of the Butler matrix is challenging at millimeter wave because of the very small wavelength. The literature has reported issues of high insertion losses and incorrect output phases at the output ports of the Butler matrix, which affects the radiation characteristics. To overcome these issues, the circuit elements of the Butler matrix such as the crossover, the quadrature hybrid and the phase shifter must be designed using highly accurate dimensions. This paper presents a low-loss and compact single-layer 8 × 8 Butler matrix operating at 28 GHz. The optimum design of each circuit element is also demonstrated in detail. The designed Butler matrix was fabricated to validate the simulated results. The measured results showed return losses of less than -10 dB at 28 GHz. The proposed Butler matrix achieved a low insertion loss and a low phase error of ± 2 dB and ± 10°, respectively. In sum, this work obtained a good agreement between the simulated and measured results.
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.
Fulltext Enabling Remote Health-Caring Utilizing IoT Concept over LTE-Femtocell Networks

Hindia MN, Rahman TA, Ojukwu H, Hanafi EB, Fattouh A

PLoS One, 2016;11(5):e0155077.
PMID: 27152423 DOI: 10.1371/journal.pone.0155077

As the enterprise of the "Internet of Things" is rapidly gaining widespread acceptance, sensors are being deployed in an unrestrained manner around the world to make efficient use of this new technological evolution. A recent survey has shown that sensor deployments over the past decade have increased significantly and has predicted an upsurge in the future growth rate. In health-care services, for instance, sensors are used as a key technology to enable Internet of Things oriented health-care monitoring systems. In this paper, we have proposed a two-stage fundamental approach to facilitate the implementation of such a system. In the first stage, sensors promptly gather together the particle measurements of an android application. Then, in the second stage, the collected data are sent over a Femto-LTE network following a new scheduling technique. The proposed scheduling strategy is used to send the data according to the application's priority. The efficiency of the proposed technique is demonstrated by comparing it with that of well-known algorithms, namely, proportional fairness and exponential proportional fairness.

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