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Fulltext Immune-mediated neurological syndrome in SARS-CoV-2 infection: a review of literature on autoimmune encephalitis in COVID-19

Payus AO, Jeffree MS, Ohn MH, Tan HJ, Ibrahim A, Chia YK, et al.

Neurol Sci, 2021 Dec 01.
PMID: 34853897 DOI: 10.1007/s10072-021-05785-z

INTRODUCTION: The novel Coronavirus Disease 2019 (COVID-19) is an infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has been spreading rapidly amongst humans and causing a global pandemic. The notorious infection has shown to cause a wide spectrum of neurological syndrome, including autoimmune encephalitis.
OBJECTIVE: Here, we systematically review the literature on autoimmune encephalitis that developed in the background of SARS-CoV-2 infections and also the possible pathophysiological mechanisms of auto-immune mediated damage to the nervous system.
METHODOLOGY: An exhaustive search was made in Medline/PubMed, Embase, Scopus and other medical databases, and 28 relevant published articles were selected according to the strict inclusion criteria.
RESULTS: Autoimmune encephalitis can occur via three possible proposed pathophysiological mechanism and can manifest during or after the acute infection period. It is more common in adult but can also occur in the paediatric patients. There were various spectra of autoantibody panels reported including antineuronal antibody, anti-gangliosides antibody and onconeural antibody. Majority of the patients responded well to the immunomodulating therapy and achieved good recovery.
CONCLUSION: In conclusion, SARSCoV-2 infection can induce various spectrum of autoimmune encephalitis. It is a major concern since there is very limited long-term study on the topic. Hence, this review aims to elucidate on the potential long-term complication of SARS-CoV-2 infection and hopefully to improve the management and prognosis of COVID-19.
Fulltext Study of sexual dimorphism of Malaysian crania: an important step in identification of the skeletal remains

Ibrahim A, Alias A, Nor FM, Swarhib M, Abu Bakar SN, Das S

Anat Cell Biol, 2017 Jun;50(2):86-92.
PMID: 28713610 DOI: 10.5115/acb.2017.50.2.86

Sex determination is one of the main steps in the identification of human skeletal remains. It constitutes an initial step in personal identification from the skeletal remains. The aim of the present study was to provide the population-specific sex discriminating osteometric standards to aid human identification. The present study was conducted on 87 (174 sides) slices of crania using postmortem computed tomography in 45 males and 42 females, aged between 18 and 75 years. About 22 parameters of crania were measured using Osirix software 3-D Volume Rendering. Results showed that all parameters were significantly higher in males than in females except for orbital height of the left eye by independent t test (P<0.01). By discriminant analysis, the classification accuracy was 85.1%, and by regression, the classification accuracy ranged from 78.2% to 86.2%. In conclusion, cranium can be used to distinguish between males and females in the Malaysian population. The results of the present study can be used as a forensic tool for identification of unknown crania.
Fulltext Experimental data for the magnetic properties of vulcanized natural rubber nanocomposites using vibrating sample magnetometer (VSM)

Ismail R, Ibrahim A, Mohamed HMSH, Mahmood MR, Adnan A

Data Brief, 2023 Feb;46:108872.
PMID: 36691557 DOI: 10.1016/j.dib.2022.108872

Base isolation is a technique installed to absorb any movement or vibration on the structures. The incorporation of nanocomposites into elastomer as the interesting materials especially for the active stiffness and vibration control of structural systems. A base isolator is made up of alternate layers of steel and rubber. The performance of magnetic rubber device is dependent on mechanical and magnetic properties of composite rubber materials. A vibrating sample magnetometer (VSM) is an instrument to detect the magnetic properties. The article provides information on the magnetic properties corresponding to different carbon nanotubes loadings of 0%, 1%, 3% and 5% and different loading of microcarbonyl iron (MCI) i.e. 0% (B0), 10% (B10), 20% (B20) and 30% (B30) in natural rubber compound. The magnetic properties dataset described the data from compression test.
Fulltext Effects of Annona muricata extraction on inhibition of polyphenoloxidase and microbiology quality of Macrobrachium rosenbergii

Ibrahim A, Ibrahim MSC, Bakar K, Bakar J, Ikhwanuddin M, Karim NU

J Food Sci Technol, 2022 Mar;59(3):859-868.
PMID: 35153318 DOI: 10.1007/s13197-021-05081-w

Giant freshwater prawn (Macrobrachium rosenbergii) is one of the important aquaculture species and quickly expanding in many countries. High demand and mass commercialization on M. rosenbergii regulating 18% of the international seafood business. Seafood products contend with various level across the supply chains and time to reach the consumers depending upon the marketing and delivery channels after harvesting. Therefore, these may cause biodeterioration such as melanosis (dark pigmentation) and microbial changes that limit the shelf life. This studies reveal the antioxidant properties from Annona muricata leaves extract and their effectiveness in inhibiting the polyphenoloxidase (PPO) activity and delaying the bacterial accumulation during 20 days of chilled storage. Five metabolites including coumarins, flavonoid, glycoside, terpenoids and steroid compound were found in A. muricata leaves extract. Total phenolic content and total flavonoid content of A. muricata were recorded at 191.24 ± 0.03 mgGAEg-1 and 1777.48 ± 1.08 mgQEg-1, respectively. Sixteen percent (16%) of A. muricata leaf extract effectively inhibit 82.41% PPO. Furthermore, 15% of A. muricata leaves extracts showed a significant reduced (p
Fulltext Changes in cardiovascular-health blood biomarkers in response to exercise intervention among older adults with cognitive frailty: A scoping review

Ibrahim A, Mat Ludin AF, Singh DKA, Rajab NF, Shahar S

Front Physiol, 2023;14:1077078.
PMID: 36875037 DOI: 10.3389/fphys.2023.1077078

Introduction: Cardiovascular health contributes significantly to the incidence of cognitive impairment. Prior to conducting exercise-related intervention, it is crucial to explore cardiovascular health blood parameters that have been commonly used as guidance for the purpose of monitoring. Information on the effectiveness of exercise on cardiovascular-related biomarkers is lacking, especially among older adults with cognitive frailty. Therefore, we aimed to review existing evidence on cardiovascular-related blood parameters and their changes following exercise intervention among older adults with cognitive frailty. Methods: A systematic search was conducted on PubMed, Cochrane, and Scopus databases. Related studies involving only human and full text in either English or Malay language were selected. Types of impairment were limited to cognitive impairment, frailty, and cognitive frailty. Studies were restricted to randomized controlled trial and clinical trial design studies. For charting purposes, all variables were extracted and tabulated. Trends in types of parameters studied were explored. Results: A total of 607 articles were screened, and the final 16 were included in this review. Four cardiovascular-related blood parameter categories were extracted: inflammatory, glucose homeostasis, lipid profile, and hemostatic biomarkers. The common parameters monitored were IGF-1 and HbA1c, glucose, and insulin sensitivity in some studies. Out of the nine studies on inflammatory biomarkers, exercise interventions showed a reduction in pro-inflammatory markers, namely, IL-6, TNF-α, IL-15, leptin, and C-reactive protein and an increase in anti-inflammatory markers, namely, IFN-γ and IL-10. Similarly, in all eight studies, glucose homeostasis-related biomarkers had improved with exercise intervention. The lipid profile was tested in five studies, with four studies showing improvements with exercise intervention via a decrease in total cholesterol, triglycerides, and low-density lipoprotein and an increase in high-density lipoprotein. A decrease in pro-inflammatory biomarkers and an increase in anti-inflammatory biomarkers were demonstrated with multicomponent exercise, including aerobic exercise in six studies and aerobic exercise on its own in the remaining two studies. Meanwhile, four out of six studies that yielded improvements in glucose homeostasis biomarkers involved only aerobic exercise and the remaining two studies involved multicomponent with aerobic exercise. Conclusion: The most consistent blood parameters studied were glucose homeostasis and inflammatory biomarkers. These parameters have been shown to improve with multicomponent exercise programs, particularly with the inclusion of aerobic exercise.
Water quality modelling using principal component analysis and artificial neural network

Ibrahim A, Ismail A, Juahir H, Iliyasu AB, Wailare BT, Mukhtar M, et al.

Mar Pollut Bull, 2023 Feb;187:114493.
PMID: 36566515 DOI: 10.1016/j.marpolbul.2022.114493

The study investigates the latent pollution sources and most significant parameters that cause spatial variation and develops the best input for water quality modelling using principal component analysis (PCA) and artificial neural network (ANN). The dataset, 22 water quality parameters were obtained from Department of Environment Malaysia (DOE). The PCA generated six significant principal component scores (PCs) which explained 65.40 % of the total variance. Parameters for water quality variation are mainlyrelated to mineral components, anthropogenic activities, and natural processes. However, in ANN three input combination models (ANN A, B, and C) were developed to identify the best model that can predict water quality index (WQI) with very high precision. ANN A model appears to have the best prediction capacity with a coefficient of determination (R2) = 0.9999 and root mean square error (RMSE) = 0.0537. These results proved that the PCA and ANN methods can be applied as tools for decision-making and problem-solving for better managing of river quality.
Data mining of the essential causes of different types of fatal construction accidents

Rafindadi AD, Shafiq N, Othman I, Ibrahim A, Aliyu MM, Mikić M, et al.

Heliyon, 2023 Feb;9(2):e13389.
PMID: 36761825 DOI: 10.1016/j.heliyon.2023.e13389

Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible.
Fulltext Incorporating theoretical and PRACTICAL approaches to assess the amount of sunlight CAPTURED by a tilted surface in a tropical climate

Hakemzadeh MH, Ibrahim A, Sopian K, Abd Hamid AS, Jarimi H

Heliyon, 2023 Mar;9(3):e14661.
PMID: 37020933 DOI: 10.1016/j.heliyon.2023.e14661

Global solar radiation can theoretically be approximated in terms of tilt and azimuth of the surface regarding the impossibility of simultaneous measurement of solar radiation at various surface tilt and azimuth angles. Moreover, the random and anisotropic nature of diffuse radiation in a tropical climate makes it extremely difficult to estimate global solar radiation accurately as a function of surface tilt and azimuth angles. This study aims to develop a novel experimental and theoretical approach in the form of a computational network in order to determine a precise combined model integrated with global horizontal solar radiation to evaluate global tilted solar radiation in a tropical climate. Obtained results revealed that precisely estimation of the global tilted solar radiation was possible, by combining geometric factors for the tilted beam solar radiation, a combination of Gueymard and Louche models for the tilted diffuse solar radiation, and isotropic ground reflectance model for the ground reflected radiation, along with global horizontal solar radiation. It was observed that the accuracy of the model developed was higher for the partly sunny sky compared to the cloudy and rainy sky, estimates were more accurate on south-facing surfaces, and the model's accuracy declined with the increasing tilt angle of the surface. The statistical analysis exhibited excellent agreement between the measured data and simulation results, considering the value of normalized mean absolute error (nMAE %), normalized root mean squared error (nRMSE %), and mean absolute percentage error (MAPE %), which were in the ranges 0.22-0.94, 0.27-1.11, and 0.23-1.02, respectively for estimating global tilted solar radiation in various regions of Peninsular Malaysia, and they were respectively found in the range of 10.2-27.5%, 16.1-38.9%, and 6.0-17.8%, for evaluating the monthly optimum tilt angle towards the south, that leads to a loss of solar energy from 1.3 to 5.4 kWh/m2/year in Peninsular Malaysia. This search revealed that the experimental and theoretical approach employed in this study can be extended to more climatic regions.
Isolations of influenza A viruses from passerine birds in Malaysia

Ibrahim HM, Awang IP, Alexander DJ, Manvell RJ, Aini I, Ibrahim AL

Vet Rec, 1990 Nov 24;127(21):528.
PMID: 2281590
Development of assessment methods for photovoltaic module enhancing techniques using the lifespan parameter

M Sultan S, Tso CP, Sopian K, K Ajeel R, Sobayel K, Ibrahim A, et al.

Heliyon, 2023 Nov;9(11):e21294.
PMID: 37885726 DOI: 10.1016/j.heliyon.2023.e21294

The photovoltaic module (PV) enhancer is a technology used for improving the PV performance. Recently, much research has been conducted to propose new concepts of PV enhancer such as coolers and reflectors. The PV enhancer performance is assessed by the common existing methods available in the literature, which solely depends on total exergy or energy, volume, area, weight and the manufacturing cost. These assessment methods are useful but cannot assess the PV enhancer's performance when considering the lifespan parameter. Hence, this study is intended to solve the current problem by linking the lifespan parameter into the existing methods by proposing three enhanced assessment methods: yield times lifespan per cost per area, yield times lifespan per cost per volume and yield times lifespan per cost per weight. The PV enhancer with the highest values of these factors will have the optimum performance. The influential parameters and limitations of the enhanced assessment methods are investigated. It is shown that the proposed methods can assess and classify the performance of the PV enhancer with different models when the lifespan is considered in the analysis. These assessment approaches can be applied by manufacturers and designers of PV enhancers.
Fulltext Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud

Mohd Romlay MR, Mohd Ibrahim A, Toha SF, De Wilde P, Venkat I

PLoS One, 2021;16(8):e0256665.
PMID: 34432855 DOI: 10.1371/journal.pone.0256665

Low-end LiDAR sensor provides an alternative for depth measurement and object recognition for lightweight devices. However due to low computing capacity, complicated algorithms are incompatible to be performed on the device, with sparse information further limits the feature available for extraction. Therefore, a classification method which could receive sparse input, while providing ample leverage for the classification process to accurately differentiate objects within limited computing capability is required. To achieve reliable feature extraction from a sparse LiDAR point cloud, this paper proposes a novel Clustered Extraction and Centroid Based Clustered Extraction Method (CE-CBCE) method for feature extraction followed by a convolutional neural network (CNN) object classifier. The integration of the CE-CBCE and CNN methods enable us to utilize lightweight actuated LiDAR input and provides low computing means of classification while maintaining accurate detection. Based on genuine LiDAR data, the final result shows reliable accuracy of 97% through the method proposed.
Preliminary assessment of the NACA0021 trailing edge wedge for wind turbine application

Abdalkarem AAM, Ansaf R, Muzammil WK, Ibrahim A, Harun Z, Fazlizan A

Heliyon, 2023 Nov;9(11):e21193.
PMID: 37942161 DOI: 10.1016/j.heliyon.2023.e21193

The airfoil blade is the primary component of a wind turbine, and its aerodynamic properties play a crucial role in determining the energy conversion efficiency of these blades. Many researchers have proposed different airfoil modifications intending to enhance the aerodynamic characteristics and limit the unsteady interaction with the atmospheric boundary layer. This study evaluates the benefits of mounting wedge tails (WTs) on the trailing edge of an airfoil. The aerodynamic characteristics of a 2-D, steady-state NACA 0021 airfoil featuring the wedge tails (WT) and fish wedge tails (FWT) were studied computationally by employing the shear stress transport (SST) k-ω turbulence model. Different WT and FWT configurations were studied at various wedge length (L) to wedge height (H) ratios, L/H, at the airfoil's trailing edge. The effects of different L/H ratios, including L/H > 1, L/H = 1, and L/H
Fulltext Solar irradiation prediction using empirical and artificial intelligence methods: A comparative review

Nawab F, Abd Hamid AS, Ibrahim A, Sopian K, Fazlizan A, Fauzan MF

Heliyon, 2023 Jun;9(6):e17038.
PMID: 37484325 DOI: 10.1016/j.heliyon.2023.e17038

Solar irradiation data is essential for the feasibility of solar energy projects. Notably, the intermittent nature of solar irradiation influences solar energy use in all forms, whether energy or agriculture. Accurate solar irradiation prediction is the only solution to effectively use solar energy in different forms. The estimation of solar irradiation is the most critical factor for site selection and sizing of solar energy projects and for selecting a suitable crop selection for the area. But the physical measurement of solar irradiation, due to the cost and technology involved, is not possible for all locations across the globe. Numerous techniques have been implemented to predict solar irradiation for this purpose. The two types of approaches that are most frequently employed are empirical techniques and artificial intelligence (AI). Both approaches have demonstrated good accuracy in various places of the world. To find out the best method, a thorough review of research articles discussing solar irradiation prediction has been done to compare different methods for solar irradiation prediction. In this paper, articles predicting solar irradiation using AI and empirical published from 2017 to 2022 have been reviewed, and both methods have been compared. The review showed that AI methods are more accurate than empirical methods. In empirical models, modified sunshine-based models (MSSM) have the highest accuracy, followed by sunshine-based (SSM) and non-sunshine-based models (NSM). The NSM has a little lower accuracy than MSSM and SSM, but the NSM can give good results in sunshine data unavailability. Also, the literature review confirmed that simple empirical models could predict accurately, and increasing the empirical model's polynomial order cannot improve results. Artificial neural networks (ANN) and Hybrid models have the highest accuracy among AI methods, followed by support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS). The increase in efficiency by hybrid models is minimal, but the complexity of models requires very sophisticated programming knowledge. ANN's most important input factors are maximum and minimum temperatures, temperature differential, relative humidity, clearness index and precipitation.
Fulltext A Malaysian ex-smoker with cough, breathlessness and nonresolving bronchospasm

Lim JA, Caruppaiya N, Zainol Abidin N, Khor BT, Palanivelu T, Hukam Gopal Chand SD, et al.

Breathe (Sheff), 2019 Dec;15(4):324-329.
PMID: 31803267 DOI: 10.1183/20734735.0224-2019

Repeated noisy breathing may be a tricky feature of lung infection. Recognising classical features in radiographs and CT scans may help in the diagnosis of severe lung infection and the start of life-saving treatment. http://bit.ly/2lQwe5y.
Fulltext Secondary school teachers psychological status and competencies in e-teaching during Covid-19

Wong KY, Sulaiman T, Ibrahim A, Kunchi Mohd AG, Hassan Hussin O, Wan Jaafar WM

Heliyon, 2021 Nov;7(11):e08238.
PMID: 34722941 DOI: 10.1016/j.heliyon.2021.e08238

PRESENTS PROBLEM/FOCUS OF STUDY: The Covid-19 outbreak has had a staggering impact on the global economy, public health and safety, trade and education. In Malaysia, the government implemented the Movement Control Order (MCO) as a preventive measure against Covid-19. In education, the learning process has been transferred to online teaching. However, pandemic pedagogy is making learning into completely online either synchronous or asynchronous. Therefore, the current research aims to determine the secondary school teachers' psychological status, competencies in e-teaching and teachers work motivation as well as determine the relationship between secondary school teachers' psychological status and competencies in e-teaching during the Covid-19 outbreak.
DESIGN/METHODOLOGY/APPROACH: Current research is a descriptive-correlational quantitative survey to determine teachers' psychological status, e-teaching competencies and working motivation during Movement Control Order (MCO) to contain the Covid-19 pandemic. The study sample consists of 595 secondary school teachers selected via convenient sampling. Quantitative data are collected from an online survey through the questionnaires with demographic, psychological status (stress, anxiety and depression), e-teaching competencies (teaching, monitoring and evaluation) and teaching motivation developed by the researchers were distributed during the MCO period. SPSS 25 is applied, Statistical measures such as Cronbach's alpha, means, percentage and standard deviation were employed to analyze the data to obtain the value of the school teachers' psychological status, e-teaching competencies and teaching motivation. Consequently, a Pearson correlation table was created to show the analysis of the school teachers' psychological status and competencies in e-teaching.
FINDINGS: This finding indicated that the teachers' psychological factors in stress, anxiety and depressed are moderate, the teachers' competencies in e-teaching is moderate as well as teachers' working motivations is also the moderate level. However, the highest mean value was found among the variables, this is revealed that despite the challenges during the Covid-19 outbreak, teachers showed positive and strong motivation in conducting e-teaching. Additionally, the result showed a negative relationship between psychological status and e-teaching competencies (-0.286, p < 0.01), as well as reported a negative relationship between dimension of psychological status and competencies in e-teaching.
LIMITATION & RECOMMENDATIONS: This study has its limitations. This study is included only Selangor teachers and given that the information obtained from the study was gather from secondary schools, the generalizability might be limited. future research may consider expanding the scope from secondary schools to primary schools' teachers and then to university lecturers. Perhaps the scope is expanding, so more information could be obtaining and help researchers understand the teachers' competencies in e-teaching, psychological status and work motivation.
Validation study of AR Gynae endotrainer - a new mobile laparoscopic simulator

Omar AA, Zon EM, Ismail MP, Mahdi M, Ibrahim A, Engku-Husna EI, et al.

Med J Malaysia, 2023 Nov;78(6):711-716.
PMID: 38031211

INTRODUCTION: In gynaecology, laparoscopy is the choice of treatment for a lot of procedures as it is considered safe and effective. However, laparoscopic surgery requires skills that are different from those required for open surgery. In order to acquire the skills, a surgeon needs specific training. The aim of this study was to validate the AR Gynae endotrainer, a new mobile laparoscopic simulator, as a comparable box trainer for gynaecology laparoscopic training, comparing it with the well-established Karl Storz SZABO-BERCISACKIER laparoscopic trainer.
MATERIALS AND METHODS: A randomised prospective crossover study was designed to compare the AR Gynae endotrainer versus Karl Storz SZABO-BERCI-SACKIER laparoscopic trainer as a tool for training gynaecology laparoscopic skills. Participants were assigned to perform two specially designed tasks used for laparoscopic training using both endotrainers. All subjects evaluated both simulators concerning their performance by the use of a questionnaire comparing: design, ports placement, visibility, ergonomics, triangulation of movement, fulcrum effect, depth perception, ambidexterity, resources for training, and resources for teaching. The overall score was defined as the median value obtained. The ability and time taken for participants to complete the tasks using both endotrainers were also compared. A total of 26 participants were enrolled in this study, including 13 Masters's students from the Department of Obstetrics & Gynaecology and 13 Masters's students from the Department of Surgery, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia.
RESULTS: A better performance was observed with AR Gynae as compared to Karl Storz endotrainer in five out of ten items evaluated in the questionnaire. Additionally, the overall score of AR Gynae endotrainer (median of 3.98) was comparable to that of Karl Storz endotrainer (median of 3.91) with p=0.519. For the items design and resources for teaching, the evaluation for AR Gynae endotrainer was significantly higher with p-values of 0.003 and 0.032, respectively. All participants were able to complete both tasks using both endotrainers. The time taken to complete both tasks was comparable on both endotrainers. Also, the AR Gynae endotrainer was cheaper.
CONCLUSIONS: The AR Gynae endotrainer was found to be a convenient and cost-effective laparoscopic simulator for gynaecology laparoscopic training and was comparable to the established Karl Storz SZABO-BERCI-SACKIER laparoscopic trainer.
Fulltext Association between maximal oxygen consumption and physical performance tests among older adults with cognitive frailty

Ibrahim A, Mat Ludin AF, Shahar S, Hamzah NH, Chin AV, Singh DKA

Exp Gerontol, 2023 Dec;184:112326.
PMID: 37967590 DOI: 10.1016/j.exger.2023.112326

INTRODUCTION: Cardiorespiratory fitness has an inverse relationship with cognitive impairment and frailty in older adults. Direct assessment of maximal oxygen consumption (VO2 max) is the gold standard to assess cardiorespiratory fitness. However, it is costly and requires a laboratory setting. Therefore, VO2 max estimation among older adults with cognitive frailty (CF) will allow the assessment of aerobic capacity, which is commonly overlooked due to the complexity of the test.
AIM: This study aims to determine the use of one of three physical performance tests (2-minute step, 2-minute walk, and 1-minute sit to stand) to effectively estimate cardiorespiratory fitness among older adults with CF.
METHODS: In this cross-sectional study, community-dwelling individuals aged 60 years old and above in Klang Valley were screened for CF. The participants performed three physical performance tests (2-minute walk, 2-minute step, and 1-minute sit to stand) followed by treadmill-based maximal exercise testing on another day.
RESULTS: A total of 32 older adults with cognitive frailty (mean age; SD: 67.1;4.7 years) participated in this study. Nearly half of them had hypertension (43.5 %), hypercholesterolemia (43.5 %), and multimorbidity (47.8 %). Among the endurance tests performed, only the 2-minute walk test independently predicted VO2 max by sex-specific with men (R2 = 0.58, p = 0.03) and women (R2 = 0.34, p = 0.01). The 2-minute walk test had good agreement with VO2 max (ICC = 0.77, 95 % CI: -3.1-2.4).
CONCLUSION: The 2-minute walk test is a valid tool for estimating cardiorespiratory fitness among older adults with CF. However, it should be further tested across a larger population.
Fulltext Comparison between hCG and GnRH Agonist for Ovulation Trigger in GnRH Antagonist In-Vitro Fertilization Cycles in a Tertiary Hospital in Malaysia: An observational study

Aziz NA, Ibrahim A, Ramli R, Yaacob N, Rahman SNA, Ismail EHE, et al.

JBRA Assist Reprod, 2024 Feb 26;28(1):21-26.
PMID: 38224580 DOI: 10.5935/1518-0557.20230066

OBJECTIVE: hCG is commonly used as an ovulation trigger in IVF. Its usage is associated with OHSS. GnRH agonist is an alternative to hCG and is associated with reduced incidence of OHSS. This study compared the cycle outcomes of GnRH agonists with hCG as an ovulation trigger in IVF cycles.
METHODS: The medical notes of 209 IVF cycles receiving GnRH agonist and hCG as ovulation trigger over 18 months were reviewed in this retrospective study. The number and quality of mature oocytes, the number and quality of embryos, pregnancy rates, and outcomes were compared using Independent T-test or One-way ANOVA for normal distribution. The Mann-Whitney test or Kruskal-Wallis test was used for not normally distributed. p<0.05 was considered statistically significant.
RESULTS: The cycle outcomes of 107 GnRH agonist-trigger and 102 hCG-trigger were compared. The MII oocytes retrieved and 2PN count was significantly higher in the GnRH agonist trigger group (p<0.001). Clinical pregnancy rate and ongoing pregnancy were higher in the GnRH agonist trigger group but were not statistically significant. The GnRH agonist trigger group was associated with low OHSS than the hCG trigger group (n=2(1.9%) and n=12(11.8%) respectively, p=0.004).
CONCLUSION: GnRH agonist trigger is an option as a final maturation trigger in high-responder women undergoing IVF or ICSI cycles.
Fulltext Closing the global cancer divide--performance of breast cancer care services in a middle income developing country

Lim GC, Aina EN, Cheah SK, Ismail F, Ho GF, Tho LM, et al.

BMC Cancer, 2014;14:212.
PMID: 24650245 DOI: 10.1186/1471-2407-14-212

BACKGROUND: Cancer is the leading cause of deaths in the world. A widening disparity in cancer burden has emerged between high income and low-middle income countries. Closing this cancer divide is an ethical imperative but there is a dearth of data on cancer services from developing countries.
METHODS: This was a multi-center, retrospective observational cohort study which enrolled women with breast cancer (BC) attending 8 participating cancer centers in Malaysia in 2011. All patients were followed up for 12 months from diagnosis to determine their access to therapies. We assess care performance using measures developed by Quality Oncology Practice Initiative, American Society of Clinical Oncology/National Comprehensive Cancer Network, American College of Surgeons' National Accreditation Program for Breast Centers as well as our local guideline.
RESULTS: Seven hundred and fifty seven patients were included in the study; they represent about 20% of incident BC in Malaysia. Performance results were mixed. Late presentation was 40%. Access to diagnostic and breast surgery services were timely; the interval from presentation to tissue diagnosis was short (median = 9 days), and all who needed surgery could receive it with only a short wait (median = 11 days). Performance of radiation, chemo and hormonal therapy services showed that about 75 to 80% of patients could access these treatments timely, and those who could not were because they sought alternative treatment or they refused treatment. Access to Trastuzumab was limited to only 19% of eligible patients.
CONCLUSIONS: These performance results are probably acceptable for a middle income country though far below the 95% or higher adherence rates routinely reported by centres in developed countries. High cost trastuzumab was inaccessible to this population without public funding support.
Chisomicines A-C, limonoids from Chisocheton ceramicus

Najmuldeen IA, Hadi AH, Awang K, Mohamad K, Ketuly KA, Mukhtar MR, et al.

J Nat Prod, 2011 May 27;74(5):1313-7.
PMID: 21428417 DOI: 10.1021/np200013g

Three new limonoids, chisomicines A-C (1-3), have been isolated from the bark of Chisocheton ceramicus. Their structures were determined by 2D NMR, CD spectroscopic methods, and X-ray analysis. Chisomicine A (1) exhibited NO production inhibitory activity in J774.1 cells stimulated by LPS dose-dependently at high cell viability.

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