MyMedR

Displaying all 8 publications

Abstract:

Sort:

Clay-starch combination for micropollutants removal from wastewater treatment plant effluent

Mohd Amin MF, Heijman SG, Rietveld LC

Water Sci Technol, 2016;73(7):1719-27.
PMID: 27054745 DOI: 10.2166/wst.2016.001

In this study, a new, more effective and cost-effective treatment alternative is investigated for the removal of pharmaceuticals from wastewater treatment plant effluent (WWTP-eff). The potential of combining clay with biodegradable polymeric flocculants is further highlighted. Flocculation is viewed as the best method to get the optimum outcome from clay. In addition, flocculation with cationic starch increases the biodegradability and cost of the treatment. Clay is naturally abundantly available and relatively inexpensive compared to conventional adsorbents. Experimental studies were carried out with existing naturally occurring pharmaceutical concentrations found and measured in WWTP-eff with atrazine spiking for comparison between the demineralised water and WWTP-eff matrix. Around 70% of the total measured pharmaceutical compounds were removable by the clay-starch combination. The effect of clay with and without starch addition was also highlighted.
Fulltext A Cost-Effective Alternative for Lateral Femoral Wall Perforation in Anterior Cruciate Ligament (ACL) Reconstruction: A Case Report

Tan SY, Leong WH, Ong LH, Mohd-Amin MZ

Malays Orthop J, 2020 Jul;14(2):138-140.
PMID: 32983390 DOI: 10.5704/MOJ.2007.023

Lateral femoral wall perforation is a rare intra-operative complication in anterior cruciate ligament (ACL) reconstruction surgery. However, it can be challenging to manage if it occurs. We share our experience on lateral femoral wall perforation managed by a large fragment washer. A 25-year-old man with right ACL injury presented with knee instability despite physiotherapy. Anterior drawer test (ADT) and Lachman test were grade 3, glide on pivot shift was positive. During ACL reconstruction, the lateral femoral wall was perforated. Due to unavailability of the rescue endobutton and budget constraint, we passed the endobutton through a washer and allowed it to sit on the washer over the lateral femoral wall. ADT and Lachman test on post-operative 6, 12 and 24 weeks were grade 1, with a negative pivot shift test. Lysholm knee score improved from 69 pre-operatively to 98 post-operatively. Conventionally, lateral femoral wall perforation can be managed by rescue endobutton, or screw and washer post technique. As this complication is rare, the rescue endobutton may not be available at all times, and the cost of the implant is also another important factor to consider. A washer can be used as an alternative technique to manage lateral femoral wall perforation in ACL reconstruction as it is not only cost-effective but also provides stable fixation with good functional outcome.
Fulltext Recent updates on liposomal formulations for detection, prevention and treatment of coronavirus disease (COVID-19)

Dini Fatini Mohammad Faizal N, Cairul Iqbal Mohd Amin M

Int J Pharm, 2023 Jan 05;630:122421.
PMID: 36410670 DOI: 10.1016/j.ijpharm.2022.122421

The unprecedented outbreak of severe acute respiratory syndrome-2 (SARS-CoV-2) worldwide has rendered it one of the most notorious pandemics ever documented in human history. As of November 2022, nearly 626 million cases of infection and over 6.6 million deaths have been reported globally. The scientific community has made significant progress in therapeutics and prevention for the management of coronavirus disease (COVID-19), including the development of vaccines and antiviral agents such as monoclonal antibodies and antiviral drugs. Although many advancements and a plethora of positive results have been obtained and global restrictions are being uplifted, obstacles in efficiently delivering these therapies, such as their rapid clearance, suboptimal biodistribution, and toxicity to organs, have yet to be addressed. To address these drawbacks, researchers have attempted applying nanotechnology-based formulations. Here, we summarized the recent data about COVID-19, its emergence, pathophysiology and life cycle, diagnosis, and currently-available medications. Subsequently, we discussed the progress in lipid nanocarriers, such as liposomes in infection detection and control. This review provides critical insights into the design of the latest liposomal-based formulations for tackling the barriers to detecting, preventing, and treating SARS-CoV-2.
Topological characterization of a bacterial cellulose-acrylic acid polymeric matrix

Halib N, Mohd Amin MC, Ahmad I, Abrami M, Fiorentino S, Farra R, et al.

Eur J Pharm Sci, 2014 Oct 1;62:326-33.
PMID: 24932712 DOI: 10.1016/j.ejps.2014.06.004

This paper focuses on the micro- and nano-topological organization of a hydrogel, constituted by a mixture of bacterial cellulose and acrylic acid, and intended for biomedical applications. The presence of acrylic acid promotes the formation of two interpenetrated continuous phases: the primary "pores phase" (PP) containing only water and the secondary "polymeric network phase" (PNP) constituted by the polymeric network swollen by the water. Low field Nuclear Magnetic Resonance (LF NMR), rheology, Scanning Electron Microscopy (SEM) and release tests were used to determine the characteristics of the two phases. In particular, we found that this system is a strong hydrogel constituted by 81% (v/v) of PP phase the remaining part being occupied by the PNP phase. Pores diameters span in the range 10-100 μm, the majority of them (85%) falling in the range 30-90 μm. The high PP phase tortuosity indicates that big pores are not directly connected to each other, but their connection is realized by a series of interconnected small pores that rend the drug path tortuous. The PNP is characterized by a polymer volume fraction around 0.73 while mesh size is around 3 nm. The theoretical interpretation of the experimental data coming from the techniques panel adopted, yielded to the micro- and nano-organization of our hydrogel.
Fulltext Three Level Thoracolumbar Spondylectomy for Recurrent Giant Cell Tumour of the Spine: A Case Report

Faruk NA, Mohd-Amin MZ, Awang-Ojep DN, Teo YY, Wong CC

Malays Orthop J, 2018 Nov;12(3):50-52.
PMID: 30555648 MyJurnal DOI: 10.5704/MOJ.1811.013

Giant cell tumour (GCT) is a benign tumour but can be locally aggressive and with the potential to metastasise especially to the lungs. Successful treatments have been reported for long bone lesions; however, optimal surgical and medical treatment for spinal and sacral lesions are not well established. In treating spinal GCTs, the aim is to achieve complete tumour excision, restore spinal stability and decompress the neural tissues. The ideal surgical procedure is an en bloc spondylectomy or vertebrectomy, where all tumour cells are removed as recurrence is closely related to the extent of initial surgical excision. However, such a surgery has a high complication rate, such as dura tear and massive blood loss. We report a patient with a missed pathological fracture of T12 treated initially with a posterior subtraction osteotomy, who had recurrence three years after the index surgery and subsequently underwent a three level vertebrectomy and posterior spinal fusion.
Fulltext Addressing Internet of Things security by enhanced sine cosine metaheuristics tuned hybrid machine learning model and results interpretation based on SHAP approach

Dobrojevic M, Zivkovic M, Chhabra A, Sani NS, Bacanin N, Mohd Amin M

PeerJ Comput Sci, 2023;9:e1405.
PMID: 37409075 DOI: 10.7717/peerj-cs.1405

An ever increasing number of electronic devices integrated into the Internet of Things (IoT) generates vast amounts of data, which gets transported via network and stored for further analysis. However, besides the undisputed advantages of this technology, it also brings risks of unauthorized access and data compromise, situations where machine learning (ML) and artificial intelligence (AI) can help with detection of potential threats, intrusions and automation of the diagnostic process. The effectiveness of the applied algorithms largely depends on the previously performed optimization, i.e., predetermined values of hyperparameters and training conducted to achieve the desired result. Therefore, to address very important issue of IoT security, this article proposes an AI framework based on the simple convolutional neural network (CNN) and extreme machine learning machine (ELM) tuned by modified sine cosine algorithm (SCA). Not withstanding that many methods for addressing security issues have been developed, there is always a possibility for further improvements and proposed research tried to fill in this gap. The introduced framework was evaluated on two ToN IoT intrusion detection datasets, that consist of the network traffic data generated in Windows 7 and Windows 10 environments. The analysis of the results suggests that the proposed model achieved superior level of classification performance for the observed datasets. Additionally, besides conducting rigid statistical tests, best derived model is interpreted by SHapley Additive exPlanations (SHAP) analysis and results findings can be used by security experts to further enhance security of IoT systems.
Fulltext Clustering analysis for classifying fake real estate listings

Mohd Amin M, Sani NS, Nasrudin MF, Abdullah S, Chhabra A, Abd Kadir F

PeerJ Comput Sci, 2024;10:e2019.
PMID: 38983188 DOI: 10.7717/peerj-cs.2019

With the rapid growth of online property rental and sale platforms, the prevalence of fake real estate listings has become a significant concern. These deceptive listings waste time and effort for buyers and sellers and pose potential risks. Therefore, developing effective methods to distinguish genuine from fake listings is crucial. Accurately identifying fake real estate listings is a critical challenge, and clustering analysis can significantly improve this process. While clustering has been widely used to detect fraud in various fields, its application in the real estate domain has been somewhat limited, primarily focused on auctions and property appraisals. This study aims to fill this gap by using clustering to classify properties into fake and genuine listings based on datasets curated by industry experts. This study developed a K-means model to group properties into clusters, clearly distinguishing between fake and genuine listings. To assure the quality of the training data, data pre-processing procedures were performed on the raw dataset. Several techniques were used to determine the optimal value for each parameter of the K-means model. The clusters are determined using the Silhouette coefficient, the Calinski-Harabasz index, and the Davies-Bouldin index. It was found that the value of cluster 2 is the best and the Camberra technique is the best method when compared to overlapping similarity and Jaccard for distance. The clustering results are assessed using two machine learning algorithms: Random Forest and Decision Tree. The observational results have shown that the optimized K-means significantly improves the accuracy of the Random Forest classification model, boosting it by an impressive 96%. Furthermore, this research demonstrates that clustering helps create a balanced dataset containing fake and genuine clusters. This balanced dataset holds promise for future investigations, particularly for deep learning models that require balanced data to perform optimally. This study presents a practical and effective way to identify fake real estate listings by harnessing the power of clustering analysis, ultimately contributing to a more trustworthy and secure real estate market.
Administration of tranexamic acid for victims of severe trauma within pre-hospital care ambulance services (PHCAS) in Malaysia

Shah Jahan MY, Shamila MA, Nurul Azlean N, Mohd Amin M, Anandakumar K, Ahmad Ibrahim KB, et al.

Med J Malaysia, 2019 08;74(4):300-306.
PMID: 31424037

INTRODUCTION: Trauma is a Global threat and the 5th highest cause of all-cause mortality in Malaysia caused predominantly due to road traffic accidents. Majority of trauma victims are young adults aged between 21-40 years old. In Malaysia, 24 out of 100,000 population die annually due to trauma, rating us amongst the highest in South East Asia. These alarming figures justify aggressive preventive and mitigation strategies. The aim of this paper is to promote the implementation of evidence-based interventions that will reduce the rate of preventable death because of trauma. Tranexamic acid is one of the few interventions in the early management of severe trauma with level-one evidence. Tranexamic acid has been proven to reduce all causes of mortality and mortality due to bleeding. Evidence proves that it is most effective when administered early, particularly within the 1st hour of trauma. This proposed guideline is formulated based upon quality evidence from multicentre studies, clinical practices in other countries and consideration of the local demographic factors with the intent of enabling an easy and simple pathway to administer tranexamic acid early in the care of the severely injured.
CONCLUSION: The guideline highlights select pre-hospital criteria's and the methods for drug administration. The authors recognise that some variants may be present amongst certain institutions necessitating minor adaptations, nevertheless the core principles of advocating tranexamic acid early in the course of pre-hospital trauma should be adhered to.