MyMedR

Displaying publications 1 - 20 of 58 in total

Abstract:

Sort:

Fulltext "I feel it is not enough…" Health providers' perspectives on services for victims of intimate partner violence in Malaysia

Colombini M, Mayhew S, Ali SH, Shuib R, Watts C

BMC Health Serv Res, 2013;13:65.
PMID: 23419141 DOI: 10.1186/1472-6963-13-65

This study explores the views and attitudes of health providers in Malaysia towards intimate partner violence (IPV) and abused women and considers whether and how their views affect the provision or quality of services. The impact of provider attitudes on the provision of services for women experiencing violence is particularly important to understand since there is a need to ensure that these women are not re-victimised by the health sector, but are treated sensitively.
Fulltext A Statistical Study on the Development of Metronidazole-Chitosan-Alginate Nanocomposite Formulation Using the Full Factorial Design

Sabbagh HAK, Hussein-Al-Ali SH, Hussein MZ, Abudayeh Z, Ayoub R, Abudoleh SM

Polymers (Basel), 2020 Apr 01;12(4).
PMID: 32244671 DOI: 10.3390/polym12040772

The goal of this study was to develop and statistically optimize the metronidazole (MET), chitosan (CS) and alginate (Alg) nanoparticles (NP) nanocomposites (MET-CS-AlgNPs) using a (21 × 31 × 21) × 3 = 36 full factorial design (FFD) to investigate the effect of chitosan and alginate polymer concentrations and calcium chloride (CaCl2) concentration ondrug loading efficiency(LE), particle size and zeta potential. The concentration of CS, Alg and CaCl2 were taken as independent variables, while drug loading, particle size and zeta potential were taken as dependent variables. The study showed that the loading efficiency and particle size depend on the CS, Alg and CaCl2 concentrations, whereas zeta potential depends only on the Alg and CaCl2 concentrations. The MET-CS-AlgNPs nanocomposites were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM) and in vitro drug release studies. XRD datashowed that the crystalline properties of MET changed to an amorphous-like pattern when the nanocomposites were formed.The XRD pattern of MET-CS-AlgNPs showed reflections at 2θ = 14.2° and 22.1°, indicating that the formation of the nanocompositesprepared at the optimum conditions havea mean diameter of (165±20) nm, with a MET loading of (46.0 ± 2.1)% and a zeta potential of (-9.2 ± 0.5) mV.The FTIR data of MET-CS-AlgNPs showed some bands of MET, such as 3283, 1585 and 1413 cm-1, confirming the presence of the drug in the MET-CS-AlgNPs nanocomposites. The TGA for the optimized sample of MET-CS-AlgNPs showed a 70.2% weight loss compared to 55.3% for CS-AlgNPs, and the difference is due to the incorporation of MET in the CS-AlgNPs for the formation of MET-CS-AlgNPs nanocomposites. The release of MET from the nanocomposite showed sustained-release properties, indicating the presence of an interaction between MET and the polymer. The nanocomposite shows a smooth surface and spherical shape. The release profile of MET from its MET-CS-AlgNPs nanocomposites was found to be governed by the second kinetic model (R2 between 0.956-0.990) with more than 90% release during the first 50 h, which suggests that the release of the MET drug can be extended or prolonged via the nanocomposite formulation.
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.
A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations

Haque F, Ibne Reaz MB, Chowdhury MEH, Md Ali SH, Ashrif A Bakar A, Rahman T, et al.

Comput Biol Med, 2021 12;139:104954.
PMID: 34715551 DOI: 10.1016/j.compbiomed.2021.104954

BACKGROUND: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system.
METHOD: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features.
RESULTS: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively.
CONCLUSIONS: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients.
Fulltext A novel sample based quadrature phase shift keying demodulator

Mohamed Moubark A, Ali SH

ScientificWorldJournal, 2014;2014:107831.
PMID: 25197687 DOI: 10.1155/2014/107831

This paper presents a new practical QPSK receiver that uses digitized samples of incoming QPSK analog signal to determine the phase of the QPSK symbol. The proposed technique is more robust to phase noise and consumes up to 89.6% less power for signal detection in demodulation operation. On the contrary, the conventional QPSK demodulation process where it uses coherent detection technique requires the exact incoming signal frequency; thus, any variation in the frequency of the local oscillator or incoming signal will cause phase noise. A software simulation of the proposed design was successfully carried out using MATLAB Simulink software platform. In the conventional system, at least 10 dB signal to noise ratio (SNR) is required to achieve the bit error rate (BER) of 10(-6), whereas, in the proposed technique, the same BER value can be achieved with only 5 dB SNR. Since some of the power consuming elements such as voltage control oscillator (VCO), mixer, and low pass filter (LPF) are no longer needed, the proposed QPSK demodulator will consume almost 68.8% to 99.6% less operational power compared to conventional QPSK demodulator.
Fulltext An integrated health sector response to violence against women in Malaysia: lessons for supporting scale up

Colombini M, Mayhew SH, Ali SH, Shuib R, Watts C

BMC Public Health, 2012;12:548.
PMID: 22828240 DOI: 10.1186/1471-2458-12-548

Malaysia has been at the forefront of the development and scale up of One-Stop Crisis Centres (OSCC) - an integrated health sector model that provides comprehensive care to women and children experiencing physical, emotional and sexual abuse. This study explored the strengths and challenges faced during the scaling up of the OSCC model to two States in Malaysia in order to identify lessons for supporting successful scale-up.
Fulltext Antimicrobial and controlled release studies of a novel nystatin conjugated iron oxide nanocomposite

Hussein-Al-Ali SH, El Zowalaty ME, Kura AU, Geilich B, Fakurazi S, Webster TJ, et al.

Biomed Res Int, 2014;2014:651831.
PMID: 24900976 DOI: 10.1155/2014/651831

Nystatin is a tetraene diene polyene antibiotic showing a broad spectrum of antifungal activity. In the present study, we prepared a nystatin nanocomposite (Nyst-CS-MNP) by loading nystatin (Nyst) on chitosan (CS) coated magnetic nanoparticles (MNPs). The magnetic nanocomposites were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), thermogravimetry analysis (TGA), vibrating sample magnetometer (VSM), and scanning electron microscopy (SEM). The XRD results showed that the MNPs and nanocomposite are pure magnetite. The FTIR analysis confirmed the binding of CS on the surface of the MNPs and also the loading of Nyst in the nanocomposite. The Nyst drug loading was estimated using UV-Vis instrumentation and showing a 14.9% loading in the nanocomposite. The TEM size image of the MNPs, CS-MNP, and Nyst-CS-MNP was 13, 11, and 8 nm, respectively. The release profile of the Nyst drug from the nanocomposite followed a pseudo-second-order kinetic model. The antimicrobial activity of the as-synthesized Nyst and Nyst-CS-MNP nanocomposite was evaluated using an agar diffusion method and showed enhanced antifungal activity against Candida albicans. In this manner, this study introduces a novel nanocomposite that can decrease fungus activity on-demand for numerous medical applications.
Fulltext Antituberculosis nanodelivery system with controlled-release properties based on para-amino salicylate-zinc aluminum-layered double-hydroxide nanocomposites

Saifullah B, Hussein MZ, Hussein-Al-Ali SH, Arulselvan P, Fakurazi S

Drug Des Devel Ther, 2013;7:1365-75.
PMID: 24255593 DOI: 10.2147/DDDT.S50665

We report the intercalation and characterization of para-amino salicylic acid (PASA) into zinc/aluminum-layered double hydroxides (ZLDHs) by two methods, direct and indirect, to form nanocomposites: PASA nanocomposite prepared by a direct method (PASA-D) and PASA nanocomposite prepared by an indirect method (PASA-I). Powder X-ray diffraction, Fourier-transform infrared spectroscopy, and thermogravimetric analysis revealed that the PASA drugs were accommodated within the ZLDH interlayers. The anions of the drug were accommodated as an alternate monolayer (along the long-axis orientation) between ZLDH interlayers. Drug loading was estimated to be 22.8% and 16.6% for PASA-D and PASA-I, respectively. The in vitro release properties of the drug were investigated in physiological simulated phosphate-buffered saline solution of pH 7.4 and 4.8. The release followed the pseudo-second-order model for both nanocomposites. Cell viability (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide [MTT] assays) was assessed against normal human lung fibroblast MRC-5 and 3T3 mouse fibroblast cells at 24, 48, and 72 hours. The results showed that the nanocomposite formulations did not possess any cytotoxicity, at least up to 72 hours.
Arginine-chitosan- and arginine-polyethylene glycol-conjugated superparamagnetic nanoparticles: Preparation, cytotoxicity and controlled-release

Hussein-Al-Ali SH, Arulselvan P, Fakurazi S, Hussein MZ, Dorniani D

J Biomater Appl, 2014 Jan 19;29(2):186-198.
PMID: 24445774

Iron oxide magnetic nanoparticles (MNPs) can be used in targeted drug delivery systems for localized cancer treatment. MNPs coated with biocompatible polymers are useful for delivering anticancer drugs. Iron oxide MNPs were synthesized via co-precipitation method then coated with either chitosan (CS) or polyethylene glycol (PEG) to form CS-MNPs and PEG-MNPs, respectively. Arginine (Arg) was loaded onto both coated nanoparticles to form Arg-CS-MNP and Arg-PEG-MNP nanocomposites. The X-ray diffraction results for the MNPs and the Arg-CS-MNP and Arg-PEG-MNPs nanocomposites indicated that the iron oxide contained pure magnetite. The amount of CS and PEG bound to the MNPs were estimated via thermogravimetric analysis and confirmed via Fourier transform infrared spectroscopy analysis. Arg loading was estimated using UV-vis measurements, which yielded values of 5.5% and 11% for the Arg-CS-MNP and Arg-PEG-MNP nanocomposites, respectively. The release profile of Arg from the nanocomposites followed a pseudo-second-order kinetic model. The cytotoxic effects of the MNPs, Arg-CS-MNPs, and Arg-PEG-MNPs were evaluated in human cervical carcinoma cells (HeLa), mouse embryonic fibroblast cells (3T3) and breast adenocarcinoma cells (MCF-7). The results indicate that the MNPs, Arg-CS-MNPs, and Arg-PEG-MNPs do not exhibit cytotoxicity toward 3T3 and HeLa cells. However, treatment of the MCF-7 cells with the Arg-CS-MNP and Arg-PEG-MNP nanocomposites reduced the cancer cell viability with IC50 values of 48.6 and 42.6 µg/mL, respectively, whereas the MNPs and free Arg did not affect the viability of the MCF-7 cells.
Fulltext Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System

Alhasa KM, Mohd Nadzir MS, Olalekan P, Latif MT, Yusup Y, Iqbal Faruque MR, et al.

Sensors (Basel), 2018 Dec 11;18(12).
PMID: 30544953 DOI: 10.3390/s18124380

Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor.
Fulltext Chlorambucil-Iron Oxide Nanoparticles as a Drug Delivery System for Leukemia Cancer Cells

Hussein-Al-Ali SH, Hussein MZ, Bullo S, Arulselvan P

Int J Nanomedicine, 2021;16:6205-6216.
PMID: 34526768 DOI: 10.2147/IJN.S312752

Introduction: Traditional cancer therapies may have incomplete eradication of cancer or destroy the normal cells. Nanotechnology solves the demerit by a guide in surgical resection of tumors, targeted chemotherapies, selective to cancerous cells, etc. This new technology can reduce the risk to the patient and automatically increased the probability of survival. Toward this goal, novel iron oxide nanoparticles (IONPs) coupled with leukemia anti-cancer drug were prepared and assessed.
Methods: The IONPs were prepared by the co-precipitation method using Fe+3/Fe+2ratio of 2:1. These IONPs were used as a carrier for chlorambucil (Chloramb), where the IONPs serve as the cores and chitosan (CS) as a polymeric shell to form Chloramb-CS-IONPs. The products were characterized using transmission electron microscopy (TEM), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) analysis, Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometry (VSM) analyses, and thermal gravimetric analysis (TGA).
Results: The as-prepared IONPs were found to be magnetite (Fe3O4) and were coated by the CS polymer/Chloramb drug for the formation of the Chloramb-CS-IONPs. The average size for CS-IONPs and Chloramb-CS-IONPs nanocomposite was found to be 15 nm, with a drug loading of 19% for the letter. The release of the drug from the nanocomposite was found to be of a controlled-release manner with around 89.9% of the drug was released within about 5000 min and governed by the pseudo-second order. The in vitro cytotoxicity studies of CS-IONPs and Chloramb-CS-IONPs nanocomposite were tested on the normal fibroblast cell lines (3T3) and leukemia cancer cell lines (WEHI). Chloramb in Chloramb-CS-IONPs nanocomposite was found to be more efficient compared to its free form.
Conclusion: This work shows that Chloramb-CS-IONPs nanocomposite is a promising candidate for magnetically targeted drug delivery for leukemia anti-cancer agents.
Fulltext Cognitive assessments for the early diagnosis of dementia after stroke

Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S

Neuropsychiatr Dis Treat, 2014;10:1743-51.
PMID: 25246795 DOI: 10.2147/NDT.S68443

The early detection of poststroke dementia (PSD) is important for medical practitioners to customize patient treatment programs based on cognitive consequences and disease severity progression. The aim is to diagnose and detect brain degenerative disorders as early as possible to help stroke survivors obtain early treatment benefits before significant mental impairment occurs. Neuropsychological assessments are widely used to assess cognitive decline following a stroke diagnosis. This study reviews the function of the available neuropsychological assessments in the early detection of PSD, particularly vascular dementia (VaD). The review starts from cognitive impairment and dementia prevalence, followed by PSD types and the cognitive spectrum. Finally, the most usable neuropsychological assessments to detect VaD were identified. This study was performed through a PubMed and ScienceDirect database search spanning the last 10 years with the following keywords: "post-stroke"; "dementia"; "neuro-psychological"; and "assessments". This study focuses on assessing VaD patients on the basis of their stroke risk factors and cognitive function within the first 3 months after stroke onset. The search strategy yielded 535 articles. After application of inclusion and exclusion criteria, only five articles were considered. A manual search was performed and yielded 14 articles. Twelve articles were included in the study design and seven articles were associated with early dementia detection. This review may provide a means to identify the role of neuropsychological assessments as early PSD detection tests.
Fulltext Cognitive impairment and memory dysfunction after a stroke diagnosis: a post-stroke memory assessment

Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S, Mohamad K

Neuropsychiatr Dis Treat, 2014;10:1677-91.
PMID: 25228808 DOI: 10.2147/NDT.S67184

Cognitive impairment and memory dysfunction following stroke diagnosis are common symptoms that significantly affect the survivors' quality of life. Stroke patients have a high potential to develop dementia within the first year of stroke onset. Currently, efforts are being exerted to assess stroke effects on the brain, particularly in the early stages. Numerous neuropsychological assessments are being used to evaluate and differentiate cognitive impairment and dementia following stroke. This article focuses on the role of available neuropsychological assessments in detection of dementia and memory loss after stroke. This review starts with stroke types and risk factors associated with dementia development, followed by a brief description of stroke diagnosis criteria and the effects of stroke on the brain that lead to cognitive impairment and end with memory loss. This review aims to combine available neuropsychological assessments to develop a post-stroke memory assessment (PSMA) scheme based on the most recognized and available studies. The proposed PSMA is expected to assess different types of memory functionalities that are related to different parts of the brain according to stroke location. An optimal therapeutic program that would help stroke patients enjoy additional years with higher quality of life is presented.
Fulltext Comparative study of Mg/Al- and Zn/Al-layered double hydroxide-perindopril erbumine nanocomposites for inhibition of angiotensin-converting enzyme

Hussein Al Ali SH, Al-Qubaisi M, Hussein MZ, Ismail M, Zainal Z, Hakim MN

Int J Nanomedicine, 2012;7:4251-62.
PMID: 22904631 DOI: 10.2147/IJN.S32267

The intercalation of a drug active, perindopril, into Mg/Al-layered double hydroxide for the formation of a new nanocomposite, PMAE, was accomplished using a simple ion exchange technique. A relatively high loading percentage of perindopril of about 36.5% (w/w) indicates that intercalation of the active took place in the Mg/Al inorganic interlayer. Intercalation was further supported by Fourier transform infrared spectroscopy, and thermal analysis shows markedly enhanced thermal stability of the active. The release of perindopril from the nanocomposite occurred in a controlled manner governed by pseudo-second order kinetics. MTT assay showed no cytotoxicity effects from either Mg/Al-layered double hydroxide or its nanocomposite, PMAE. Mg/Al-layered double hydroxide showed angiotensin-converting enzyme inhibitory activity, with 5.6% inhibition after 90 minutes of incubation. On incubation of angiotensin-converting enzyme with 0.5 μg/mL of the PMAE nanocomposite, inhibition of the enzyme increased from 56.6% to 70.6% at 30 and 90 minutes, respectively. These results are comparable with data reported in the literature for Zn/Al-perindopril.
Fulltext Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs

Al-Qazzaz NK, Sabir MK, Bin Mohd Ali SH, Ahmad SA, Grammer K

J Healthc Eng, 2021;2021:8537000.
PMID: 34603651 DOI: 10.1155/2021/8537000

Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent (Hur) and amplitude-aware permutation entropy (AAPE) features were extracted from the EEG dataset. k-nearest neighbors (kNN) and support vector machine (SVM) classification techniques were considered for automatic gender recognition from emotional-based EEGs. The main novelty of this paper is twofold: first, to investigate Hur as a complexity feature and AAPE as an irregularity parameter for the emotional-based EEGs using two-way analysis of variance (ANOVA) and then integrating these features to propose a new CompEn hybrid feature fusion method towards developing the novel WT_CompEn gender recognition framework as a core for an automated gender recognition model to be sensitive for identifying gender roles in the brain-emotion relationship for females and males. The results illustrated the effectiveness of Hur and AAPE features as remarkable indices for investigating gender-based anger, sadness, happiness, and neutral emotional state. Moreover, the proposed WT_CompEn framework achieved significant enhancement in SVM classification accuracy of 100%, indicating that the novel WT_CompEn may offer a useful way for reliable enhancement of gender recognition of different emotional states. Therefore, the novel WT_CompEn framework is a crucial goal for improving the process of automatic gender recognition from emotional-based EEG signals allowing for more comprehensive insights to understand various gender differences and human behavior effects of an intervention on the brain.
Fulltext Controlled release and angiotensin-converting enzyme inhibition properties of an antihypertensive drug based on a perindopril erbumine-layered double hydroxide nanocomposite

Hussein Al Ali SH, Al-Qubaisi M, Hussein MZ, Ismail M, Zainal Z, Hakim MN

Int J Nanomedicine, 2012;7:2129-41.
PMID: 22619549 DOI: 10.2147/IJN.S30461

The intercalation of perindopril erbumine into Zn/Al-NO(3)-layered double hydroxide resulted in the formation of a host-guest type of material. By virtue of the ion-exchange properties of layered double hydroxide, perindopril erbumine was released in a sustained manner. Therefore, this intercalated material can be used as a controlled-release formulation.
Fulltext Controlled-release approaches towards the chemotherapy of tuberculosis

Saifullah B, Hussein MZ, Hussein Al Ali SH

Int J Nanomedicine, 2012;7:5451-63.
PMID: 23091386 DOI: 10.2147/IJN.S34996

Tuberculosis (TB), caused by the bacteria Mycobacterium tuberculosis, is notorious for its lethality to humans. Despite technological advances, the tubercle bacillus continues to threaten humans. According to the World Health Organization's 2011 global report on TB, 8.8 million cases of TB were reported in 2010, with a loss of 1.7 million human lives. As drug-susceptible TB requires long-term treatment of between 6 and 9 months, patient noncompliance remains the most important reason for treatment failure. For multidrug-resistant TB, patients must take second-line anti-TB drugs for 18-24 months and many adverse effects are associated with these drugs. Drug-delivery systems (DDSs) seem to be the most promising option for advancement in the treatment of TB. DDSs reduce the adverse effects of drugs and their dosing frequency as well as shorten the treatment period, and hence improve patient compliance. Further advantages of these systems are that they target the disease area, release the drugs in a sustained manner, and are biocompatible. In addition, targeted delivery systems may be useful in dealing with extensively drug-resistant TB because many side effects are associated with the drugs used to cure the disease. In this paper, we discuss the DDSs developed for the targeted and slow delivery of anti-TB drugs and their possible advantages and disadvantages.
Fulltext Development of a controlled-release anti-parkinsonian nanodelivery system using levodopa as the active agent

Kura AU, Hussein Al Ali SH, Hussein MZ, Fakurazi S, Arulselvan P

Int J Nanomedicine, 2013;8:1103-10.
PMID: 23524513 DOI: 10.2147/IJN.S39740

A new layered organic-inorganic nanocomposite material with an anti-parkinsonian active compound, L-3-(3,4-dihydroxyphenyl) alanine (levodopa), intercalated into the inorganic interlayers of a Zn/Al-layered double hydroxide (LDH) was synthesized using a direct coprecipitation method. The resulting nanocomposite was composed of the organic moiety, levodopa, sandwiched between Zn/Al-LDH inorganic interlayers. The basal spacing of the resulting nano-composite was 10.9 Å. The estimated loading of levodopa in the nanocomposite was approximately 16% (w/w). A Fourier transform infrared study showed that the absorption bands of the nanocomposite were characteristic of both levodopa and Zn/Al-LDH, which further confirmed intercalation, and that the intercalated organic moiety in the nanocomposite was more thermally stable than free levodopa. The resulting nanocomposite showed sustained-release properties, so can be used in a controlled-release formulation. Cytotoxicity analysis using an MTT assay also showed increased cell viability of 3T3 cells exposed to the newly synthesized nanocomposite compared with those exposed to pure levodopa after 72 hours of exposure.
Fulltext Development of antiproliferative nanohybrid compound with controlled release property using ellagic acid as the active agent

Hussein MZ, Al Ali SH, Zainal Z, Hakim MN

Int J Nanomedicine, 2011;6:1373-83.
PMID: 21796241 DOI: 10.2147/IJN.S21567

An ellagic acid (EA)-zinc layered hydroxide (ZLH) nanohybrid (EAN) was synthesized under a nonaqueous environment using EA and zinc oxide (ZnO) as the precursors. Powder X-ray diffraction showed that the basal spacing of the nanohybrid was 10.4 Å, resulting in the spatial orientation of EA molecules between the interlayers of 22.5° from z-axis with two negative charges at 8,8' position of the molecules pointed toward the ZLH interlayers. FTIR study showed that the intercalated EA spectral feature is generally similar to that of EA, but with bands slightly shifted. This indicates that some chemical bonding of EA presence between the nanohybrid interlayers was slightly changed, due to the formation of host-guest interaction. The nanohybrid is of mesopores type with 58.8% drug loading and enhanced thermal stability. The release of the drug active, EA from the nanohybrid was found to be sustained and therefore has good potential to be used as a drug controlled-release formulation. In vitro bioassay study showed that the EAN has a mild effect on the hepatocytes cells, similar to its counterpart, free EA.
Fulltext Effect of geometric parameters on the performance of p-type junctionless lateral gate transistors

Larki F, Dehzangi A, Md Ali SH, Jalar A, Islam MS, Hamidon MN, et al.

PLoS One, 2014;9(4):e95182.
PMID: 24743692 DOI: 10.1371/journal.pone.0095182

This paper examines the impact of two important geometrical parameters, namely the thickness and source/drain extensions on the performance of low doped p-type double lateral gate junctionless transistors (DGJLTs). The three dimensional Technology Computer-Aided Design simulation is implemented to calculate the characteristics of the devices with different thickness and source/drain extension and based on that, the parameters such as threshold voltage, transconductance and resistance in saturation region are analyzed. In addition, simulation results provide a physical explanation for the variation of device characteristics given by the variation of geometric parameters, mainly based on investigation of the electric field components and the carries density variation. It is shown that, the variation of the carrier density is the main factor which affects the characteristics of the device when the device's thickness is varied. However, the electric field is mainly responsible for variation of the characteristics when the source/drain extension is changed.

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links