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HLA-A, -B, -C, -DRB1 and -DQB1 alleles and haplotypes in 271 Southeast Asia Indians from Peninsular Malaysia

Nurul-Aain AF, Tan LK, Heselynn H, Nor-Shuhaila S, Eashwary M, Wahinuddin S, et al.

Hum Immunol, 2020 Jun;81(6):263-264.
PMID: 32312605 DOI: 10.1016/j.humimm.2020.04.004

A total of 271 Southeast Asia Indians from Peninsular Malaysia were genotyped for HLA-A, -B, -C, -DRB1, and -DQB1 loci using polymerase chain reaction sequence-specific oligonucleotide probe hybridization methods. In this report, HLA-B and HLA-DQB1 was in Hardy-Weinberg proportions (HWEP) (p > 0.05). We observed significant deviation from the HWEP for HLA-A (p
Fulltext Obesity and Its Association with Undiagnosed Diabetes Mellitus, High Blood Pressure and Hypercholesterolemia in the Malaysian Adult Population: A National Cross-Sectional Study Using NHMS Data

Koo HC, Tan LK, Lim GP, Kee CC, Omar MA

Int J Environ Res Public Health, 2023 Feb 09;20(4).
PMID: 36833764 DOI: 10.3390/ijerph20043058

This study aimed to report the prevalence of obesity, classified using Asian cut-off, and its relationships with undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia. We analyzed the nationally representative data from 14,025 Malaysian adults who participated in the NHMS 2015. The relationship between obesity and undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia was determined using multivariable logistic regressions, and lifestyle risk factors and sociodemographic characteristics were adjusted. The undiagnosed high blood pressure group showed the highest proportionate of overweight/obese (80.0%, 95% CI: 78.1-81.8) and central obesity (61.8%, 95% CI: 59.3-64.2). Inverse association was observed between underweight with undiagnosed high blood pressure (aOR: 0.40, 95% CI: 0.26-0.61) and hypercholesterolemia (aOR: 0.75, 95% CI: 0.59-0.95) groups. In contrast, positive relationships were shown between overweight/obese and risk of undiagnosed diabetes mellitus (aOR: 1.65, 95% CI: 1.31-2.07), high blood pressure (aOR: 3.08, 95% CI: 2.60-3.63), and hypercholesterolemia (aOR: 1.37, 95% CI: 1.22-1.53). Likewise, central obesity was positively associated with a risk of undiagnosed diabetes mellitus (aOR: 1.40, 95% CI: 1.17-1.67), high blood pressure (aOR: 2.83, 95% CI: 2.45-3.26), and hypercholesterolemia (aOR: 1.26, 95% CI: 1.12-1.42). Our findings indicated the importance of periodical health examinations to assess the risk of non-communicable diseases among the general and abdominal obese Malaysian adults.
Fulltext Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

Yong YL, Tan LK, McLaughlin RA, Chee KH, Liew YM

J Biomed Opt, 2017 12;22(12):1-9.
PMID: 29274144 DOI: 10.1117/1.JBO.22.12.126005

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.
Assessing Complex Left Ventricular Adaptations in Aortic Stenosis Using Personalized 3D + time Cardiac MRI Modeling

Chuah SH, Md Sari NA, Tan LK, Chiam YK, Chan BT, Abdul Aziz YF, et al.

J Cardiovasc Transl Res, 2023 Oct;16(5):1110-1122.
PMID: 37022611 DOI: 10.1007/s12265-023-10375-9

Left ventricular adaptations can be a complex process under the influence of aortic stenosis (AS) and comorbidities. This study proposed and assessed the feasibility of using a motion-corrected personalized 3D + time LV modeling technique to evaluate the adaptive and maladaptive LV response to aid treatment decision-making. A total of 22 AS patients were analyzed and compared against 10 healthy subjects. The 3D + time analysis showed a highly distinct and personalized pattern of remodeling in individual AS patients which is associated with comorbidities and fibrosis. Patients with AS alone showed better wall thickening and synchrony than those comorbid with hypertension. Ischemic heart disease in AS caused impaired wall thickening and synchrony and systolic function. Apart from showing significant correlations to echocardiography and clinical MRI measurements (r: 0.70-0.95; p
A Radiomics Study: Classification of Breast Lesions by Textural Features from Mammography Images

Letchumanan N, Wong JHD, Tan LK, Ab Mumin N, Ng WL, Chan WY, et al.

J Digit Imaging, 2023 Aug;36(4):1533-1540.
PMID: 37253893 DOI: 10.1007/s10278-022-00753-1

This study investigates the feasibility of using texture radiomics features extracted from mammography images to distinguish between benign and malignant breast lesions and to classify benign lesions into different categories and determine the best machine learning (ML) model to perform the tasks. Six hundred and twenty-two breast lesions from 200 retrospective patient data were segmented and analysed. Three hundred fifty radiomics features were extracted using the Standardized Environment for Radiomics Analysis (SERA) library, one of the radiomics implementations endorsed by the Image Biomarker Standardisation Initiative (IBSI). The radiomics features and selected patient characteristics were used to train selected machine learning models to classify the breast lesions. A fivefold cross-validation was used to evaluate the performance of the ML models and the top 10 most important features were identified. The random forest (RF) ensemble gave the highest accuracy (89.3%) and positive predictive value (66%) and likelihood ratio of 13.5 in categorising benign and malignant lesions. For the classification of benign lesions, the RF model again gave the highest likelihood ratio of 3.4 compared to the other models. Morphological and textural radiomics features were identified as the top 10 most important features from the random forest models. Patient age was also identified as one of the significant features in the RF model. We concluded that machine learning models trained against texture-based radiomics features and patient features give reasonable performance in differentiating benign versus malignant breast lesions. Our study also demonstrated that the radiomics-based machine learning models were able to emulate the visual assessment of mammography lesions, typically used by radiologists, leading to a better understanding of how the machine learning model arrive at their decision.
Microstructural Integrity of Peripheral Nerves in Charcot-Marie-Tooth Disease: An MRI Evaluation Study

Cheah PL, Krisnan T, Wong JHD, Rozalli FI, Fadzli F, Rahmat K, et al.

J Magn Reson Imaging, 2021 02;53(2):437-444.
PMID: 32918328 DOI: 10.1002/jmri.27354

BACKGROUND: Charcot-Marie-Tooth (CMT) disease is diagnosed through clinical findings and genetic testing. While there are neurophysiological tools and clinical functional scales in CMT, objective disease biomarkers that can facilitate in monitoring disease progression are limited.
PURPOSE: To investigate the utility of diffusion tensor imaging (DTI) in determining the microstructural integrity of sciatic and peroneal nerves and its correlation with the MRI grading of muscle atrophy severity and clinical function in CMT as determined by the CMT neuropathy score (CMTNS).
STUDY TYPE: Prospective case-control.
SUBJECTS: Nine CMT patients and nine age-matched controls.
FIELD STRENGTH/SEQUENCE: 3 T T1 -weighted in-/out-of phase spoiled gradient recalled echo (SPGR) and DTI sequences.
ASSESSMENT: Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) values for sciatic and peroneal nerves were obtained from DTI. Muscle atrophy was graded according to the Goutallier classification using in-/out-of phase SPGRs. DTI parameters and muscle atrophy grades were compared between CMT and controls, and the relationship between DTI parameters, muscle atrophy grades, and CMTNS were assessed.
STATISTICAL TESTS: The Wilcoxon Signed Ranks test was used to compare DTI parameters between CMT and controls. The relationship between DTI parameters, muscle atrophy grades, and CMTNS were analyzed using the Spearman correlation. Receiver operating characteristic (ROC) analyses of DTI parameters that can differentiate CMT from healthy controls were done.
RESULTS: There was a significant reduction in FA and increase in RD of both nerves (P
Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression

Tan LK, McLaughlin RA, Lim E, Abdul Aziz YF, Liew YM

J Magn Reson Imaging, 2018 07;48(1):140-152.
PMID: 29316024 DOI: 10.1002/jmri.25932

BACKGROUND: Left ventricle (LV) structure and functions are the primary assessment performed in most clinical cardiac MRI protocols. Fully automated LV segmentation might improve the efficiency and reproducibility of clinical assessment.
PURPOSE: To develop and validate a fully automated neural network regression-based algorithm for segmentation of the LV in cardiac MRI, with full coverage from apex to base across all cardiac phases, utilizing both short axis (SA) and long axis (LA) scans.
STUDY TYPE: Cross-sectional survey; diagnostic accuracy.
SUBJECTS: In all, 200 subjects with coronary artery diseases and regional wall motion abnormalities from the public 2011 Left Ventricle Segmentation Challenge (LVSC) database; 1140 subjects with a mix of normal and abnormal cardiac functions from the public Kaggle Second Annual Data Science Bowl database.
FIELD STRENGTH/SEQUENCE: 1.5T, steady-state free precession.
ASSESSMENT: Reference standard data generated by experienced cardiac radiologists. Quantitative measurement and comparison via Jaccard and Dice index, modified Hausdorff distance (MHD), and blood volume.
STATISTICAL TESTS: Paired t-tests compared to previous work.
RESULTS: Tested against the LVSC database, we obtained 0.77 ± 0.11 (Jaccard index) and 1.33 ± 0.71 mm (MHD), both metrics demonstrating statistically significant improvement (P < 0.001) compared to previous work. Tested against the Kaggle database, the signed difference in evaluated blood volume was +7.2 ± 13.0 mL and -19.8 ± 18.8 mL for the end-systolic (ES) and end-diastolic (ED) phases, respectively, with a statistically significant improvement (P < 0.001) for the ED phase.
DATA CONCLUSION: A fully automated LV segmentation algorithm was developed and validated against a diverse set of cardiac cine MRI data sourced from multiple imaging centers and scanner types. The strong performance overall is suggestive of practical clinical utility.
LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
Remodeling in Aortic Stenosis With Reduced and Preserved Ejection Fraction: Insight on Motion Abnormality Via 3D + Time Personalized LV Modeling in Cardiac MRI

Chuah SH, Tan LK, Md Sari NA, Chan BT, Hasikin K, Lim E, et al.

J Magn Reson Imaging, 2023 Jul 15.
PMID: 37452574 DOI: 10.1002/jmri.28915

BACKGROUND: Increased afterload in aortic stenosis (AS) induces left ventricle (LV) remodeling to preserve a normal ejection fraction. This compensatory response can become maladaptive and manifest with motion abnormality. It is a clinical challenge to identify contractile and relaxation dysfunction during early subclinical stage to prevent irreversible deterioration.
PURPOSE: To evaluate the changes of regional wall dynamics in 3D + time domain as remodeling progresses in AS.
STUDY TYPE: Retrospective.
POPULATION: A total of 31 AS patients with reduced and preserved ejection fraction (14 AS_rEF: 7 male, 66.5 [7.8] years old; 17 AS_pEF: 12 male, 67.0 [6.0] years old) and 15 healthy (6 male, 61.0 [7.0] years old).
FIELD STRENGTH/SEQUENCE: 1.5 T Magnetic resonance imaging/steady state free precession and late-gadolinium enhancement sequences.
ASSESSMENT: Individual LV models were reconstructed in 3D + time domain and motion metrics including wall thickening (TI), dyssynchrony index (DI), contraction rate (CR), and relaxation rate (RR) were automatically extracted and associated with the presence of scarring and remodeling.
STATISTICAL TESTS: Shapiro-Wilk: data normality; Kruskal-Wallis: significant difference (P
Fulltext Alternating Hemiplegia of Childhood in a Person of Malay Ethnicity with Diffusion Tensor Imaging Abnormalities

Tan AH, Ong TL, Ramli N, Tan LK, Lim JL, Azhan MA, et al.

J Mov Disord, 2019 May;12(2):132-134.
PMID: 31158946 DOI: 10.14802/jmd.18063
Preliminary study of longitudinal changes in the pituitary and brain of children on growth hormone therapy

Low LS, Wong JHD, Tan LK, Chan WY, Jalaludin MY, Anuar Zaini A, et al.

J Neuroradiol, 2023 Mar;50(2):271-277.
PMID: 34800564 DOI: 10.1016/j.neurad.2021.11.004

BACKGROUND: In subjects with isolated growth hormone deficiency (IGHD), recombinant human growth hormone (rhGH) is an approved method to achieve potential mid-parental height. However, data reporting rhGH treatment response in terms of brain structure volumes were scarce. We report the volumetric changes of the pituitary gland, basal ganglia, corpus callosum, thalamus, hippocampus and amygdala in these subjects post rhGH treatment.
MATERIALS AND METHODS: This was a longitudinal study of eight IGHD subjects (2 males, 6 females) with a mean age of 11.1 ± 0.8 years and age-matched control groups. The pituitary gland, basal ganglia and limbic structures volumes were obtained using 3T MRI voxel-based morphology. The left-hand bone age was assessed using the Tanner-Whitehouse method. Follow-up imaging was performed after an average of 1.8 ± 0.4 years on rhGH.
RESULTS: Subjects with IGHD had a smaller mean volume of the pituitary gland, right thalamus, hippocampus, and amygdala than the controls. After rhGH therapy, these volumes normalized to the age-matched controls. Corpus callosum of IGHD subjects had a larger mean volume than the controls and did not show much volume changes in response to rhGH therapy. There were changes towards normalization of bone age deficit of IGHD in response to rhGH therapy.
CONCLUSION: The pituitary gland, hippocampus, and amygdala volumes in IGHD subjects were smaller than age-matched controls and showed the most response to rhGH therapy. Semi-automated volumetric assessment of pituitary gland, hippocampus, and amygdala using MRI may provide an objective assessment of response to rhGH therapy.
Microstructural Change and Cognitive Alteration in Maxillofacial Trauma and Mild Traumatic Brain Injury: A Diffusion Tensor Imaging Study

Veeramuthu V, Hariri F, Narayanan V, Tan LK, Ramli N, Ganesan D

J Oral Maxillofac Surg, 2016 Jun;74(6):1197.e1-1197.e10.
PMID: 26917201 DOI: 10.1016/j.joms.2016.01.042

The aim of the present study was to establish the incidence of maxillofacial (MF) injury accompanying mild traumatic brain injury (mTBI) and the associated neurocognitive deficits and white matter changes.
Genetic diversity, virulotyping and antimicrobial resistance susceptibility of Yersinia enterocolitica isolated from pigs and porcine products in Malaysia

Thong KL, Tan LK, Ooi PT

J Sci Food Agric, 2018 Jan;98(1):87-95.
PMID: 28542807 DOI: 10.1002/jsfa.8442

BACKGROUND: The objectives of the present study were to determine the antimicrobial resistance, virulotypes and genetic diversity of Yersinia enterocolitica isolated from uncooked porcine food and live pigs in Malaysia.
RESULTS: Thirty-two non-repeat Y. enterocolitica strains of three bioserotypes (3 variant/O:3, n = 27; 1B/O:8, n = 3; 1A/O:5, n = 2) were analysed. Approximately 90% of strains were multidrug-resistant with a multiple antibiotic resistance index < 0.2 and the majority of the strains were resistant to nalidixic acid, clindamycin, ampicillin, ticarcillin, tetracycline and amoxicillin. Yersinia enterocolitica could be distinguished distinctly into three clusters by pulsed-field gel electrophoresis, with each belonging to a particular bioserotype. Strains of 3 variant/O:3 were more heterogeneous than others. Eleven of the 15 virulence genes tested (hreP, virF, rfbC, myfA, sat, inv, ail, ymoA, ystA, tccC, yadA) and pYV virulence plasmid were present in all the bioserotpe 3 variant/03 strains.
CONCLUSION: The occurrence of virulent strains of Y. enterocolitica in pigs and porcine products reiterated that pigs are important reservoirs for Y. enterocolitica. The increasing trend of multidrug resistant strains is a public health concern. This is the first report on the occurrence of potential pathogenic and resistant strains of Y. enterocolitica in pigs in Malaysia. © 2017 Society of Chemical Industry.
Fulltext Human leucocyte antigens profiling in Malay female patients with systemic lupus erythematosus: are we the same or different?

Selvaraja M, Too CL, Tan LK, Koay BT, Abdullah M, Shah AM, et al.

Lupus Sci Med, 2022 Feb;9(1).
PMID: 35105721 DOI: 10.1136/lupus-2021-000554

OBJECTIVE: SLE is a heterogeneous autoimmune disease, in terms of clinical presentation, incidence and severity across diverse ethnic populations. We investigated the human leucocyte antigens (HLA) profile (ie, HLA-A, HLA-B and HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1) in Malaysian Malay female patients with SLE and determined the generalisability of the published HLA risk factors across different ethnic populations globally including Malaysia.
METHODS: One hundred Malay female patients with SLE were recruited between January 2016 and October 2017 from a nephrology clinic. All patients were genotyped for HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1 alleles using PCR sequence-specific oligonucleotides method on Luminex platform. A total of 951 HLA genotyped population-based Malay control subjects was used for association testing by means of OR with 95% CIs.
RESULTS: Our findings convincingly validated common associations between HLA-A*11 (OR=1.65, p=3.36×10-3, corrected P (Pc)=4.03×10-2) and DQB1*05:01 (OR=1.56, p=2.02×10-2, Pc=non-significant) and SLE susceptibility in the Malay population. In contrast, DQB1*03:01 (OR=0.51, p=4.06×10-4, Pc=6.50×10-3) were associated with decreased risk of SLE in Malay population. Additionally, we also detected novel associations of susceptibility HLA genes (ie, HLA-B*38:02, DPA1*02:02, DPB1*14:01) and protective HLA genes (ie, DPA1*01:03). When comparing the current data with data from previously published studies from Caucasian, African and Asian populations, DRB1*15 alleles, DQB1*03:01 and DQA1*01:02 were corroborated as universal susceptibility and protective genes.
CONCLUSIONS: This study reveals multiple HLA alleles associated with susceptibility and protection against risk of developing SLE in Malay female population with renal disorders. In addition, the published data from different ethnic populations together with our study further support the notion that the genetic effects from association with DRB1*15:01/02, DQB1*03:01 and DQA1*01:02 alleles are generalised to multiple ethnic populations of Caucasian, African and Asian descents.
Segmentation of left ventricle in late gadolinium enhanced MRI through 2D-4D registration for infarct localization in 3D patient-specific left ventricular model

Leong CO, Lim E, Tan LK, Abdul Aziz YF, Sridhar GS, Socrates D, et al.

Magn Reson Med, 2019 02;81(2):1385-1398.
PMID: 30230606 DOI: 10.1002/mrm.27486

PURPOSE: To evaluate a 2D-4D registration-cum-segmentation framework for the delineation of left ventricle (LV) in late gadolinium enhanced (LGE) MRI and for the localization of infarcts in patient-specific 3D LV models.
METHODS: A 3-step framework was proposed, consisting of: (1) 3D LV model reconstruction from motion-corrected 4D cine-MRI; (2) Registration of 2D LGE-MRI with 4D cine-MRI; (3) LV contour extraction from the intersection of LGE slices with the LV model. The framework was evaluated against cardiac MRI data from 27 patients scanned within 6 months after acute myocardial infarction. We compared the use of local Pearson's correlation (LPC) and normalized mutual information (NMI) as similarity measures for the registration. The use of 2 and 6 long-axis (LA) cine-MRI scans was also compared. The accuracy of the framework was evaluated using manual segmentation, and the interobserver variability of the scar volume derived from the segmented LV was determined using Bland-Altman analysis.
RESULTS: LPC outperformed NMI as a similarity measure for the proposed framework using 6 LA scans, with Hausdorrf distance (HD) of 1.19 ± 0.53 mm versus 1.51 ± 2.01 mm (endocardial) and 1.21 ± 0.48 mm versus 1.46 ± 1.78 mm (epicardial), respectively. Segmentation using 2 LA scans was comparable to 6 LA scans with a HD of 1.23 ± 0.70 mm (endocardial) and 1.25 ± 0.74 mm (epicardial). The framework yielded a lower interobserver variability in scar volumes compared with manual segmentation.
CONCLUSION: The framework showed high accuracy and robustness in delineating LV in LGE-MRI and allowed for bidirectional mapping of information between LGE- and cine-MRI scans, crucial in personalized model studies for treatment planning.
Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images

Tan LK, Liew YM, Lim E, Abdul Aziz YF, Chee KH, McLaughlin RA

Med Biol Eng Comput, 2018 Jun;56(6):1053-1062.
PMID: 29147835 DOI: 10.1007/s11517-017-1750-7

In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius. Graphical abstract Fully automated localization of the left ventricular blood pool in short axis cardiac cine MR images.
Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences

Tan LK, Liew YM, Lim E, McLaughlin RA

Med Image Anal, 2017 Apr 12;39:78-86.
PMID: 28437634 DOI: 10.1016/j.media.2017.04.002

Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints. We have benchmarked our approach primarily against the publicly-available left ventricle segmentation challenge (LVSC) dataset, which consists of 100 training and 100 validation cardiac MRI cases representing a heterogeneous mix of cardiac pathologies and imaging parameters across multiple centers. Our approach attained a .77 Jaccard index, which is the highest published overall result in comparison to other automated algorithms. To test general applicability, we also evaluated against the Kaggle Second Annual Data Science Bowl, where the evaluation metric was the indirect clinical measures of LV volume rather than direct myocardial contours. Our approach attained a Continuous Ranked Probability Score (CRPS) of .0124, which would have ranked tenth in the original challenge. With this we demonstrate the effectiveness of convolutional neural network regression paired with domain-specific features in clinical segmentation.
Prevalence and characterization of multidrug-resistant and extended-spectrum beta-lactamase-producing Escherichia coli from pediatric wards of a Malaysian hospital

Ho WS, Balan G, Puthucheary S, Kong BH, Lim KT, Tan LK, et al.

Microb Drug Resist, 2012 Aug;18(4):408-16.
PMID: 22394084 DOI: 10.1089/mdr.2011.0222

The emergence of Escherichia coli resistant to extended-spectrum cephalosporins (ESCs) is of concern as ESC is often used to treat infections by Gram-negative bacteria. One-hundred and ten E. coli strains isolated in 2009-2010 from children warded in a Malaysian tertiary hospital were analyzed for their antibiograms, carriage of extended-spectrum beta-lactamase (ESBL) and AmpC genes, possible inclusion of the beta-lactamase genes on an integron platform, and their genetic relatedness. All E. coli strains were sensitive to carbapenems. About 46% of strains were multidrug resistant (MDR; i.e., resistant to ≥3 antibiotic classes) and almost half (45%) were nonsusceptible to ESCs. Among the MDR strains, high resistance rates were observed for ampicillin (98%), tetracycline (75%), and trimethoprim/sulfamethoxazole (73%). Out of 110 strains, bla(TEM-1) (49.1%), bla(CTX-M) (11.8%), and bla(CMY-2) (6.4%) were detected. Twenty-one strains were ESBL producers. CTX-M-15 was the predominant CTX-M variant found and this is the first report of a CTX-M-27-producing E. coli strain from Malaysia. Majority (3.1%) of the strains harbored class 1 integron-encoded integrases with a predominance of aadA and dfr genes within the integron variable region. No gene cassette encoding ESBL genes was found and integrons were not significantly associated with ESBL or non-ESBL producers. Possible clonal expansion was observed for few CTX-M-15-positive strains but the O25-ST131 E. coli clone known to harbor CTX-M-15 was not detected while CMY-2-positive strains were genetically diverse.
Fulltext Does Awareness of Malaysian Healthy Plate Associate with Adequate Fruit and Vegetable Intake among Malaysian Adults with Non-Communicable Diseases?

Tan LK, Chua EH, Mohd Ghazali S, Cheah YK, Jayaraj VJ, Kee CC

Nutrients, 2023 Dec 08;15(24).
PMID: 38140302 DOI: 10.3390/nu15245043

The healthy eating plate concept has been introduced in many countries, including Malaysia, as a visual guide for the public to eat healthily. The relationship between Malaysian Healthy Plate (MHP) and adequate fruit and vegetable (FV) intake among morbid Malaysian adults is unknown. Hence, we investigated the relationship between awareness of the MHP and FV intake among morbid Malaysian adults. National survey data on 9760 morbid Malaysian adults aged 18 years and above were analyzed. The relationship between awareness of MHP and FV intake among Malaysian adults with obesity, diabetes mellitus, hypertension, and hypercholesterolemia were determined using multivariable logistic regression controlling for sociodemographic characteristics and lifestyle risk factors. Our data demonstrated that MHP awareness is associated with adequate FV intake among the Malaysian adults with abdominal obesity (adjusted odds ratio (aOR): 1.86, 95% confidence interval (CI): 1.05-3.29), diabetes mellitus (aOR: 4.88, 95% CI: 2.13-22.18), hypertension (aOR: 4.39, 95% CI: 1.96-9.83), and hypercholesterolemia (aOR: 4.16, 95% CI: 1.48-11.72). Our findings indicated the necessity for ongoing efforts by policymakers, healthcare professionals, and nutrition educators to promote the concept of MHP and ensure that morbid Malaysian adults consume a sufficient intake of FV or adopt a healthy eating pattern to achieve and maintain optimal health.
Assessing changes in microstructural integrity of white matter tracts in children with leukaemia following exposure to chemotherapy

Ramli N, Lim CH, Rajagopal R, Tan LK, Seow P, Ariffin H

Pediatr Radiol, 2020 08;50(9):1277-1283.
PMID: 32591982 DOI: 10.1007/s00247-020-04717-x

BACKGROUND: Intrathecal and intravenous chemotherapy, specifically methotrexate, might contribute to neural microstructural damage.
OBJECTIVE: To assess, by diffusion tensor imaging, microstructural integrity of white matter in paediatric patients with acute lymphoblastic leukaemia (ALL) following intrathecal and intravenous chemotherapy.
MATERIALS AND METHODS: Eleven children diagnosed with de novo ALL underwent MRI scans of the brain with diffusion tensor imaging (DTI) prior to commencement of chemotherapy and at 12 months after diagnosis, using a 3-tesla (T) MRI scanner. We investigated the changes in DTI parameters in white matter tracts before and after chemotherapy using tract-based spatial statistics overlaid on the International Consortium of Brain Mapping DTI-81 atlas. All of the children underwent formal neurodevelopmental assessment at the two study time points.
RESULTS: Whole-brain DTI analysis showed significant changes between the two time points, affecting several white matter tracts. The tracts demonstrated longitudinal changes of decreasing mean and radial diffusivity. The neurodevelopment of the children was near compatible for age at the end of ALL treatment.
CONCLUSION: The quantification of white matter tracts changes in children undergoing chemotherapy showed improving longitudinal values in DTI metrics (stable fractional anisotropy, decreasing mean and radial diffusivity), which are incompatible with deterioration of microstructural integrity in these children.
Fulltext Whole mitochondrial genome sequencing of Malaysian patients with cardiomyopathy

Kuan SW, Chua KH, Tan EW, Tan LK, Loch A, Kee BP

PeerJ, 2022;10:e13265.
PMID: 35441061 DOI: 10.7717/peerj.13265

Cardiomyopathy (CMP) constitutes a diverse group of myocardium diseases affecting the pumping ability of the heart. Genetic predisposition is among the major factors affecting the development of CMP. Globally, there are over 100 genes in autosomal and mitochondrial DNA (mtDNA) that have been reported to be associated with the pathogenesis of CMP. However, most of the genetic studies have been conducted in Western countries, with limited data being available for the Asian population. Therefore, this study aims to investigate the mutation spectrum in the mitochondrial genome of 145 CMP patients in Malaysia. Long-range PCR was employed to amplify the entire mtDNA, and whole mitochondrial genome sequencing was conducted on the MiSeq platform. Raw data was quality checked, mapped, and aligned to the revised Cambridge Reference Sequence (rCRS). Variants were named, annotated, and filtered. The sequencing revealed 1,077 variants, including 18 novel and 17 CMP and/or mitochondrial disease-associated variants after filtering. In-silico predictions suggested that three of the novel variants (m.8573G>C, m.11916T>A and m.11918T>G) in this study are potentially pathogenic. Two confirmed pathogenic variants (m.1555A>G and m.11778G>A) were also found in the CMP patients. The findings of this study shed light on the distribution of mitochondrial mutations in Malaysian CMP patients. Further functional studies are required to elucidate the role of these variants in the development of CMP.

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