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  1. Razak NN, Annuar MS
    Appl Biochem Biotechnol, 2014 Mar;172(6):2932-44.
    PMID: 24464534 DOI: 10.1007/s12010-014-0731-7
    Free laccase and fungal biomass from white-rot fungi were compared in the thermokinetics study of the laccase-catalyzed decolorization of an azo dye, i.e., Trypan Blue. The decolorization in both systems followed a first-order kinetics. The apparent first-order rate constant, k1', value increases with temperature. Apparent activation energy of decolorization was similar for both systems at ∼ 22 kJ mol(-1), while energy for laccase inactivation was 18 kJ mol(-1). Although both systems were endothermic, fungal biomass showed higher enthalpy, entropy, and Gibbs free energy changes for the decolorization compared to free laccase. On the other hand, free laccase showed reaction spontaneity over a wider range of temperature (ΔT = 40 K) as opposed to fungal biomass (ΔT = 15 K). Comparison of entropy change (ΔS) values indicated metabolism of the dye by the biomass.
  2. Kanaheswari Y, Razak NN, Chandran V, Ong LC
    Spinal Cord, 2011 Mar;49(3):376-80.
    PMID: 20838404 DOI: 10.1038/sc.2010.125
    Prospective cross-sectional multidimensional study using clinical assessment and standard measures.
  3. Al-jarrah AM, Abdul Rahman A, Shahrim I, Razak NN, Ababneh B, Tousi ET
    Phys Med, 2016 Jan;32(1):36-41.
    PMID: 26494156 DOI: 10.1016/j.ejmp.2015.09.003
    Genipin gel dosimeters are hydrogels infused with a radiation-sensitive material which yield dosimetric information in three dimensions (3D). The effect of inorganic salts and glucose on the visible absorption dose-response, melting points and mass density of genipin gel dosimeters has been experimentally evaluated using 6-MV LINAC photons. As a result, the addition of glucose with optimum concentration of 10% (w/w) was found to improve the thermal stability of the genipin gel and increase its melting point (Tm) by 6 °C accompanied by a slight decrease of dose-response. Furthermore, glucose helps to adjust the gel mass density to obtain the desired tissue-equivalent properties. A drop of Tm was observed when salts were used as additives. As the salt concentration increased, gel Tm decreased. The mass density and melting point of the genipin gel could be adjusted using different amounts of glucose that improved the genipin gel suitability for 3D dose measurements without introducing additional toxicity to the final gel.
  4. Muhd Shukeri WFW, Mat-Nor MB, Jamaludin UK, Suhaimi F, Abd Razak NN, Ralib AM
    Indian J Crit Care Med, 2018 Jun;22(6):402-407.
    PMID: 29962739 DOI: 10.4103/ijccm.IJCCM_92_18
    Background and Aims: Currently, there is a lack of real-time metric with high sensitivity and specificity to diagnose sepsis. Insulin sensitivity (SI) may be determined in real-time using mathematical glucose-insulin models; however, its effectiveness as a diagnostic test of sepsis is unknown. Our aims were to determine the levels and diagnostic value of model-based SI for identification of sepsis in critically ill patients.

    Materials and Methods: In this retrospective, cohort study, we analyzed SI levels in septic (n = 18) and nonseptic (n = 20) patients at 1 (baseline), 4, 8, 12, 16, 20, and 24 h of their Intensive Care Unit admission. Patients with diabetes mellitus Type I or Type II were excluded from the study. The SI levels were derived by fitting the blood glucose levels, insulin infusion and glucose input rates into the Intensive Control of Insulin-Nutrition-Glucose model.

    Results: The median SI levels were significantly lower in the sepsis than in the nonsepsis at all follow-up time points. The areas under the receiver operating characteristic curve of the model-based SI at baseline for discriminating sepsis from nonsepsis was 0.814 (95% confidence interval, 0.675-0.953). The optimal cutoff point of the SI test was 1.573 × 10-4 L/mu/min. At this cutoff point, the sensitivity was 77.8%, specificity was 75%, positive predictive value was 73.7%, and negative predictive value was 78.9%.

    Conclusions: Model-based SI ruled in and ruled out sepsis with fairly high sensitivity and specificity in our critically ill nondiabetic patients. These findings can be used as a foundation for further, prospective investigation in this area.

  5. Jamaludin UK, M Suhaimi F, Abdul Razak NN, Md Ralib A, Mat Nor MB, Pretty CG, et al.
    Comput Methods Programs Biomed, 2018 Aug;162:149-155.
    PMID: 29903481 DOI: 10.1016/j.cmpb.2018.03.001
    BACKGROUND AND OBJECTIVE: Blood glucose variability is common in healthcare and it is not related or influenced by diabetes mellitus. To minimise the risk of high blood glucose in critically ill patients, Stochastic Targeted Blood Glucose Control Protocol is used in intensive care unit at hospitals worldwide. Thus, this study focuses on the performance of stochastic modelling protocol in comparison to the current blood glucose management protocols in the Malaysian intensive care unit. Also, this study is to assess the effectiveness of Stochastic Targeted Blood Glucose Control Protocol when it is applied to a cohort of diabetic patients.

    METHODS: Retrospective data from 210 patients were obtained from a general hospital in Malaysia from May 2014 until June 2015, where 123 patients were having comorbid diabetes mellitus. The comparison of blood glucose control protocol performance between both protocol simulations was conducted through blood glucose fitted with physiological modelling on top of virtual trial simulations, mean calculation of simulation error and several graphical comparisons using stochastic modelling.

    RESULTS: Stochastic Targeted Blood Glucose Control Protocol reduces hyperglycaemia by 16% in diabetic and 9% in nondiabetic cohorts. The protocol helps to control blood glucose level in the targeted range of 4.0-10.0 mmol/L for 71.8% in diabetic and 82.7% in nondiabetic cohorts, besides minimising the treatment hour up to 71 h for 123 diabetic patients and 39 h for 87 nondiabetic patients.

    CONCLUSION: It is concluded that Stochastic Targeted Blood Glucose Control Protocol is good in reducing hyperglycaemia as compared to the current blood glucose management protocol in the Malaysian intensive care unit. Hence, the current Malaysian intensive care unit protocols need to be modified to enhance their performance, especially in the integration of insulin and nutrition intervention in decreasing the hyperglycaemia incidences. Improvement in Stochastic Targeted Blood Glucose Control Protocol in terms of uen model is also a must to adapt with the diabetic cohort.

  6. Khounani Z, Abdul Razak NN, Hosseinzadeh-Bandbafha H, Madadi M, Sun F, Mohammadi P, et al.
    Environ Res, 2024 May 01;248:118286.
    PMID: 38280524 DOI: 10.1016/j.envres.2024.118286
    This study assesses the environmental impact of pine chip-based biorefinery processes, focusing on bioethanol, xylonic acid, and lignin production. A cradle-to-gate Life Cycle Assessment (LCA) is employed, comparing a novel biphasic pretreatment method (p-toluenesulfonic acid (TsOH)/pentanol, Sc-1) with conventional sulfuric acid pretreatment (H2SO4, Sc-2). The analysis spans biomass handling, pretreatment, enzymatic hydrolysis, yeast fermentation, and distillation. Sc-1 yielded an environmental impact of 1.45E+01 kPt, predominantly affecting human health (96.55%), followed by ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed 32.61%, 29.28%, and 38.11% to the total environmental burdens, respectively. Sc-2 resulted in an environmental burden of 1.64E+01 kPt, with a primary impact on human health (96.56%) and smaller roles for ecosystems (3.07%) and resources (0.38%). Bioethanol, xylonic acid, and lignin contributed differently at 22.59%, 12.5%, and 64.91%, respectively. Electricity generation was predominant in both scenarios, accounting for 99.05% of the environmental impact, primarily driven by its extensive usage in biomass handling and pretreatment processes. Sc-1 demonstrated a 13.05% lower environmental impact than Sc-2 due to decreased electricity consumption and increased bioethanol and xylonic acid outputs. This study highlights the pivotal role of pretreatment methods in wood-based biorefineries and underscores the urgency of sustainable alternatives like TsOH/pentanol. Additionally, adopting greener electricity generation, advanced technologies, and process optimization are crucial for reducing the environmental footprint of waste-based biorefineries while preserving valuable bioproduct production.
  7. Abu-Samah A, Knopp JL, Abdul Razak NN, Razak AA, Jamaludin UK, Mohamad Suhaimi F, et al.
    Med Devices (Auckl), 2019;12:215-226.
    PMID: 31239792 DOI: 10.2147/MDER.S187840
    Background: Stress-induced hyperglycemia is common in critically ill patients. A few forms of model-based glycemic control have been introduced to reduce this phenomena and among them is the automated STAR protocol which has been used in the Christchurch and Gyulá hospitals' intensive care units (ICUs) since 2010. Methods: This article presents the pilot trial assessment of STAR protocol which has been implemented in the International Islamic University Malaysia Medical Centre (IIUMMC) Hospital ICU since December 2017. One hundred and forty-two patients who received STAR treatment for more than 20 hours were used in the assessment. The initial results are presented to discuss the ability to adopt and adapt the model-based control framework in a Malaysian environment by analyzing its performance and safety. Results: Overall, 60.7% of blood glucose measurements were in the target band. Only 0.78% and 0.02% of cohort measurements were below 4.0 mmol/L and 2.2 mmol/L (the limitsfor mild and severe hypoglycemia, respectively). Treatment preference-wise, the clinical staff were favorable of longer intervention options when available. However, 1 hourly treatments were still used in 73.7% of cases. Conclusion: The protocol succeeded in achieving patient-specific glycemic control while maintaining safety and was trusted by nurses to reduce workload. Its lower performance results, however, give the indication for modification in some of the control settings to better fit the Malaysian environment.
  8. Abdul Razak A, Abu-Samah A, Abdul Razak NN, Jamaludin U, Suhaimi F, Ralib A, et al.
    Med Devices (Auckl), 2020;13:139-149.
    PMID: 32607009 DOI: 10.2147/MDER.S231856
    Purpose: This paper presents an assessment of an automated and personalized stochastic targeted (STAR) glycemic control protocol compliance in Malaysian intensive care unit (ICU) patients to ensure an optimized usage.

    Patients and Methods: STAR proposes 1-3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017-quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.

    Results: The results show the percentage of insulin compliance increased from 2017 to first quarter of 2019* and fluctuated in feed administrations. Overall compliance amounted to 98.8% and 97.7% for administered insulin and feed, respectively. There was higher average of 17 blood glucose measurements per day than in other centres that have been using STAR, but longer intervals were selected when recommended. Control safety and performance were similar for all periods showing no obvious correlation to compliance.

    Conclusion: The results indicate that STAR, an automated model-based protocol is positively accepted among the Malaysian ICU clinicians to automate glycemic control and the usage can be extended to other hospitals already. Performance could be improved with several propositions.

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