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Contemporary evidence of workplace violence against the primary healthcare workforce worldwide: a systematic review

Yusoff HM, Ahmad H, Ismail H, Reffin N, Chan D, Kusnin F, et al.

Hum Resour Health, 2023 Oct 13;21(1):82.
PMID: 37833727 DOI: 10.1186/s12960-023-00868-8

Violence against healthcare workers recently became a growing public health concern and has been intensively investigated, particularly in the tertiary setting. Nevertheless, little is known of workplace violence against healthcare workers in the primary setting. Given the nature of primary healthcare, which delivers essential healthcare services to the community, many primary healthcare workers are vulnerable to violent events. Since the Alma-Ata Declaration of 1978, the number of epidemiological studies on workplace violence against primary healthcare workers has increased globally. Nevertheless, a comprehensive review summarising the significant results from previous studies has not been published. Thus, this systematic review was conducted to collect and analyse recent evidence from previous workplace violence studies in primary healthcare settings. Eligible articles published in 2013-2023 were searched from the Web of Science, Scopus, and PubMed literature databases. Of 23 included studies, 16 were quantitative, four were qualitative, and three were mixed method. The extracted information was analysed and grouped into four main themes: prevalence and typology, predisposing factors, implications, and coping mechanisms or preventive measures. The prevalence of violence ranged from 45.6% to 90%. The most commonly reported form of violence was verbal abuse (46.9-90.3%), while the least commonly reported was sexual assault (2-17%). Most primary healthcare workers were at higher risk of patient- and family-perpetrated violence (Type II). Three sub-themes of predisposing factors were identified: individual factors (victims' and perpetrators' characteristics), community or geographical factors, and workplace factors. There were considerable negative consequences of violence on both the victims and organisations. Under-reporting remained the key issue, which was mainly due to the negative perception of the effectiveness of existing workplace policies for managing violence. Workplace violence is a complex issue that indicates a need for more serious consideration of a resolution on par with that in other healthcare settings. Several research gaps and limitations require additional rigorous analytical and interventional research. Information pertaining to violent events must be comprehensively collected to delineate the complete scope of the issue and formulate prevention strategies based on potentially modifiable risk factors to minimise the negative implications caused by workplace violence.
The Efficacy of Apple Cider Vinegar at Different pH Values as an Antimicrobial Agent: An In Vitro Study

Chandraseharan P, Sockalingam SNM, Shafiei Z, Zakaria ASI, Mahyuddin A, Rahman MA

J Contemp Dent Pract, 2023 Oct 01;24(10):779-786.
PMID: 38152911 DOI: 10.5005/jp-journals-10024-3581

AIMS AND BACKGROUND: This study evaluates the antimicrobial activities of commercially available 5% apple cider vinegar (ACV) against Enterococcus faecalis, Streptococcus mutans, and Lactobacillus casei. Materials and methods: Minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) were conducted using the broth microdilution method. Sodium hypochlorite (NaOCl) of 5.25% was used as a positive control, and comparisons were also made with acetic acid (AA) as the main ingredient in ACV. The three test bacteria treated with the most effective ACV dilution were visualized under a transmission electron microscope (TEM) for structural changes.
RESULTS: Minimal inhibitory concentration was determined at 0.625% of the concentration of ACV against S. mutans and E. faecalis and 1.25% of the concentration of ACV against L. casei with two-fold serial dilutions. A concentration of 5 × 10-1% with 10-fold serial dilutions was found to be the MIC value for all three bacteria. No significant differences were found when compared with the positive control (NaOCl) (p = 0.182, p = 0.171, and p = 0.234), respectively, for two-fold serial dilutions and (p = 1.000, p = 0.658, and p = 0.110), respectively for 10-fold serial dilutions. MBC was observed to be 5% ACV for both E. faecalis and S. mutans. However, positive microbial growth was observed on the agar plate when cultured with L. casei. An independent sample t-test showed no significant differences (p > 0.05) in the antimicrobial activities between 5% ACV and 5% pure AA. TEM revealed cell wall and cytoplasmic membrane disruptions on all three bacteria at MIC value.
CONCLUSION: Apple cider vinegar has antimicrobial activities against Enterococcus faecalis, Streptococcus mutans, and Lactobacillus casei at their respective MIC values.
CLINICAL SIGNIFICANCE: Apple cider vinegar can be an alternative antimicrobial dental pulp disinfectant to sodium hypochlorite. Apple cider vinegar can be used safely, especially in children's dental pulp therapy and deep caries management, when adequate tooth isolation is not readily achievable. Thus, adverse reactions commonly associated with other frequently used chemical disinfectants can be avoided.
Fulltext Sustainable approach for catalytic green epoxidation of oleic acid with applied ion exchange resin

Rahman MA, Mubarak NM, Azmi IS, Jalil MJ

Sci Rep, 2023 Sep 19;13(1):15470.
PMID: 37726425 DOI: 10.1038/s41598-023-42879-4

Epoxides were primarily derived from petroleum-based sources. However, there has been limited research on optimizing the process parameters for epoxidized palm oil-derived oleic acid, resulting in its underutilization. Therefore, this study aimed to optimize the catalytic epoxidation of palm oleic acid concerning the oxirane content by applying ion exchange resin as a catalyst. Epoxidized oleic acid was produced using in-situ-formed performic acid by combining formic acid as the oxygen carrier with hydrogen peroxide as the oxygen donor. The findings revealed that the optimal reaction conditions for producing epoxidized oleic acid with the highest oxirane content were an Amberlite IR-120 catalyst loading of 0.9 g, a molar ratio of formic acid to oleic acid of 1:1., and a molar ratio of hydrogen peroxide to oleic acid of 1:1.1. By employing these optimal conditions, the maximum relative conversion of palm oleic acid to oxirane was achieved at 85%. The reaction rate constants (k) based on the optimized epoxidized oleic acid are determined as follows: k11 = 20 mol L-1 min-1, k12 = 2 mol L-1 min-1, and k2 = 20 mol L-1 min-1. The findings validated the kinetic model by showing good agreement between the simulation and experimental data.
Fulltext Machine learning-based technique for resonance and directivity prediction of UMTS LTE band quasi Yagi antenna

Haque MA, Saha D, Al-Bawri SS, Paul LC, Rahman MA, Alshanketi F, et al.

Heliyon, 2023 Sep;9(9):e19548.
PMID: 37809766 DOI: 10.1016/j.heliyon.2023.e19548

In this study, we have presented our findings on the deployment of a machine learning (ML) technique to enhance the performance of LTE applications employing quasi-Yagi-Uda antennas at 2100 MHz UMTS band. A number of techniques, including simulation, measurement, and a model of an RLC-equivalent circuit, are discussed in this article as ways to assess an antenna's suitability for the intended applications. The CST simulation gives the suggested antenna a reflection coefficient of -38.40 dB at 2.1 GHz and a bandwidth of 357 MHz (1.95 GHz-2.31 GHz) at a -10 dB level. With a dimension of 0.535λ0×0.714λ0, it is not only compact but also features a maximum gain of 6.9 dB, a maximum directivity of 7.67, VSWR of 1.001 at center frequency and a maximum efficiency of 89.9%. The antenna is made of a low-cost substrate, FR4. The RLC circuit, sometimes referred to as the lumped element model, exhibits characteristics that are sufficiently similar to those of the proposed Yagi antenna. We use yet another supervised regression machine learning (ML) technique to create an exact forecast of the antenna's frequency and directivity. The performance of machine learning (ML) models can be evaluated using a variety of metrics, including the variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and mean squared logarithmic error (MSLE). Out of the seven ML models, the linear regression (LR) model has the lowest error and maximum accuracy when predicting directivity, whereas the ridge regression (RR) model performs the best when predicting frequency. The proposed antenna is a strong candidate for the intended UMTS LTE applications, as shown by the modeling results from CST and ADS, as well as the measured and forecasted outcomes from machine learning techniques.
Fulltext Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna

Haque MA, Rahman MA, Al-Bawri SS, Yusoff Z, Sharker AH, Abdulkawi WM, et al.

Sci Rep, 2023 Aug 03;13(1):12590.
PMID: 37537201 DOI: 10.1038/s41598-023-39730-1

In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi-Uda antennas operating in the n78 band for 5G applications. This research study investigates several techniques, such as simulation, measurement, and an RLC equivalent circuit model, to evaluate the performance of an antenna. In this investigation, the CST modelling tools are used to develop a high-gain, low-return-loss Yagi-Uda antenna for the 5G communication system. When considering the antenna's operating frequency, its dimensions are [Formula: see text]. The antenna has an operating frequency of 3.5 GHz, a return loss of [Formula: see text] dB, a bandwidth of 520 MHz, a maximum gain of 6.57 dB, and an efficiency of almost 97%. The impedance analysis tools in CST Studio's simulation and circuit design tools in Agilent ADS software are used to derive the antenna's equivalent circuit (RLC). We use supervised regression ML method to create an accurate prediction of the frequency and gain of the antenna. Machine learning models can be evaluated using a variety of measures, including variance score, R square, mean square error, mean absolute error, root mean square error, and mean squared logarithmic error. Among the nine ML models, the prediction result of Linear Regression is superior to other ML models for resonant frequency prediction, and Gaussian Process Regression shows an extraordinary performance for gain prediction. R-square and var score represents the accuracy of the prediction, which is close to 99% for both frequency and gain prediction. Considering these factors, the antenna can be deemed an excellent choice for the n78 band of a 5G communication system.
Fulltext Dual Regime Mode-Locked and Q-Switched Erbium-Doped Fiber Laser by Employing Graphene Filament-Chitin Film-Based Passive Saturable Absorber

Zuikafly SNF, Ahmad H, Ismail MF, Abdul Rahman MA, Yahya WJ, Abu Husain N, et al.

Micromachines (Basel), 2023 May 14;14(5).
PMID: 37241671 DOI: 10.3390/mi14051048

We investigate the dynamics of high energy dual regime unidirectional Erbium-doped fiber laser in ring cavity, which is passively Q-switched and mode-locked through the use of an environmentally friendly graphene filament-chitin film-based saturable absorber. The graphene-chitin passive saturable absorber allows the option for different operating regimes of the laser by simple adjustment of the input pump power, yielding, simultaneously, highly stable and high energy Q-switched pulses at 82.08 nJ and 1.08 ps mode-locked pulses. The finding can have applications in a multitude of fields due to its versatility and the regime of operation that is on demand.
Nanomedicine-driven therapeutic interventions of autophagy and stem cells in the management of Alzheimer's disease

Alhodieb FS, Rahman MA, Barkat MA, Alanezi AA, Barkat HA, Hadi HA, et al.

Nanomedicine (Lond), 2023 Mar 20.
PMID: 36938800 DOI: 10.2217/nnm-2022-0108

Drug-loaded, brain-targeted nanocarriers could be a promising tool in overcoming the challenges associated with Alzheimer's disease therapy. These nanocargoes are enormously flexible to functionalize and facilitate the delivery of drugs to brain cells by bridging the blood-brain barrier and into brain cells. To date, modifications have included nanoparticles (NPs) coating with tunable surfactants/phospholipids, covalently attaching polyethylene glycol chains (PEGylation), and tethering different targeting ligands to cell-penetrating peptides in a manner that facilitates their entry across the BBB and downregulates various pathological hallmarks as well as intra- and extracellular signaling pathways. This review provides a brief update on drug-loaded, multifunctional nanocarriers and the therapeutic intervention of autophagy and stem cells in the management of Alzheimer's disease.
Fulltext Does the US regional greenhouse gas initiative affect green innovation?

Rahman MA, Ahmad R, Ismail I

Environ Sci Pollut Res Int, 2023 Feb;30(6):15689-15707.
PMID: 36173521 DOI: 10.1007/s11356-022-23189-0

This study measures the impact of the implementation of the Regional Greenhouse Gas Initiative (RGGI) on firms' green innovation initiatives. We used 20 years of panel data from the Fortune 500 list of the US largest companies. Based on DID, a benchmark regression, the RGGI has a significant adverse effect on the green innovation of Fortune 500 companies, and we verified these findings with multiple robustness tests. As we investigate how energy-intensive industries were affected by RGGI, we found that it slowed down green innovation, but it was not statistically significant. This study provides a novel perspective on how the RGGI influences green innovation in firms and how different types of sectors respond to the policy. The findings indicate that the "weak" Porter Hypothesis has not been confirmed in the present carbon trading market (particularly the RGGI) for Fortune 500 firms in the USA. In terms of policy, we believe that a well-covered and differentiated legislation that fosters green innovation while being realistic about the policy's goal and the firm's environmental attitude, like emissions reduction through green innovation, is essential.
Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework

Muzahid AJM, Kamarulzaman SF, Rahman MA, Murad SA, Kamal MAS, Alenezi AH

Sci Rep, 2023 Jan 12;13(1):603.
PMID: 36635336 DOI: 10.1038/s41598-022-27026-9

Prospective customers are becoming more concerned about safety and comfort as the automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation of recent AVs collision data indicates that modern automated driving systems are prone to rear-end collisions, usually leading to multiple-vehicle collisions. Moreover, most investigations into severe traffic conditions are confined to single-vehicle collisions. This work reviewed diverse techniques of existing literature to provide planning procedures for multiple vehicle cooperation and collision avoidance (MVCCA) strategies in AVs while also considering their performance and social impact viewpoints. Firstly, we investigate and tabulate the existing MVCCA techniques associated with single-vehicle collision avoidance perspectives. Then, current achievements are extensively evaluated, challenges and flows are identified, and remedies are intelligently formed to exploit a taxonomy. This paper also aims to give readers an AI-enabled conceptual framework and a decision-making model with a concrete structure of the training network settings to bridge the gaps between current investigations. These findings are intended to shed insight into the benefits of the greater efficiency of AVs set-up for academics and policymakers. Lastly, the open research issues discussed in this survey will pave the way for the actual implementation of driverless automated traffic systems.
Visible-light-driven photocatalytic dual-layer hollow fibre membrane ameliorates the changes of bisphenol A exposure in gastrointestinal tract

Kamaludin R, Othman MHD, Kadir SHSA, Khan J, Ismail AF, Rahman MA, et al.

Environ Sci Pollut Res Int, 2023 Jan;30(1):259-273.
PMID: 35902521 DOI: 10.1007/s11356-022-22121-w

Various treatments of choice are available to overcome contamination of bisphenol A (BPA) in the environment including membrane technologies; however, the treatment still releases contaminants that threaten the human being. Therefore, the present study is conducted to investigate the degradation of BPA by recently developed visible-light-driven photocatalytic nitrogen-doping titanium dioxide (N-doped TiO2) dual-layer hollow fibre (DLHF) membrane and its efficiency in reducing the level of BPA in contaminated water. Fabricated with suitable polymer/photocatalyst (15/7.5 wt.%) via co-extrusion spinning method, the DLHF was characterized morphologically, evaluated for BPA degradation by using submerged photocatalytic membrane reactor under visible light irradiations followed by the investigation of intermediates formed. BPA exposure effects were accessed by immunohistochemistry staining of gastrointestinal sample obtained from animal model. BPA has been successfully degraded up to 72.5% with 2 intermediate products, B1 and B2, being identified followed by total degradation of BPA. BPA exposure leads to the high-intensity IHC staining of Claudin family which indicated the disruption of small intestinal barrier (SIB) integrity. Low IHC staining intensity of Claudin family in treated BPA group demonstrated that reducing the level of BPA by N-doped TiO2 DLHF is capable of protecting the important component of SIB. Altogether, the fabricated photocatalytic DLHF membrane is expected to have an outstanding potential in removing BPA and its health effect for household water treatment to fulfil the public focus on the safety of their household water and their need to consume clean water.
CT Reconstruction Algorithm and Low Contrast Detectability of Phantom Study: A Systematic Review and Meta-Analysis

Adibah Yusof NA, Abdul Karim MK, Asikin NM, Paiman S, Awang Kechik MM, Abdul Rahman MA, et al.

Curr Med Imaging, 2023;19(10):1105-1113.
PMID: 35975862 DOI: 10.2174/1573405618666220816160544

BACKGROUND: For almost three decades, computed tomography (CT) has been extensively used in medical diagnosis, which led researchers to conduct linking of CT dose exposure with image quality.
METHODS: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. We utilize PubMed, ScienceDirect, Google Scholar and Scopus databases to search related published articles from the year 2011 until 2020. The notable keywords comprise "computed tomography", "CT phantom", and "low contrast detectability". Of 52 articles, 20 articles are within the inclusion criteria in this systematic review.
RESULTS: The dichotomous outcomes were chosen to represent the results in terms of risk ratio as per meta-analysis study. Notably, the noise in iterative reconstruction (IR) reduced by 24%, 33% and 36% with the use of smooth, medium and sharp filters, respectively. Furthermore, adaptive iterative dose reduction (AIDR 3D) improved image quality and the visibility of smaller less dense objects compared to filtered back-projection. Most of the researchers used 120 kVp tube voltage to scan phantom for quality assurance study.
CONCLUSION: Hence, optimizing primary factors such as tube potential reduces the dose exposure significantly, and the optimized IR technique could substantially reduce the radiation dose while maintaining the image quality.
Mechanistic insight into immunomodulatory effects of food-functioned plant secondary metabolites

Ali Reza ASM, Nasrin MS, Hossen MA, Rahman MA, Jantan I, Haque MA, et al.

Crit Rev Food Sci Nutr, 2023;63(22):5546-5576.
PMID: 34955042 DOI: 10.1080/10408398.2021.2021138

Medicinally important plant-foods offer a balanced immune function, which is essential for protecting the body against antigenic invasion, mainly by microorganisms. Immunomodulators play pivotal roles in supporting immune function either suppressing or stimulating the immune system's response to invading pathogens. Among different immunomodulators, plant-based secondary metabolites have emerged as high potential not only for immune defense but also for cellular immunoresponsiveness. These natural immunomodulators can be developed into safer alternatives to the clinically used immunosuppressants and immunostimulant cytotoxic drugs which possess serious side effects. Many plants of different species have been reported to possess strong immunomodulating properties. The immunomodulatory effects of plant extracts and their bioactive metabolites have been suggested due to their diverse mechanisms of modulation of the complex immune system and their multifarious molecular targets. Phytochemicals such as alkaloids, flavonoids, terpenoids, carbohydrates and polyphenols have been reported as responsible for the immunomodulatory effects of several medicinal plants. This review illustrates the potent immunomodulatory effects of 65 plant secondary metabolites, including dietary compounds and their underlying mechanisms of action on cellular and humoral immune functions in in vitro and in vivo studies. The clinical potential of some of the compounds to be used for various immune-related disorders is highlighted.
Fulltext Stability and Reproducibility of Radiomic Features Based on Various Segmentation Techniques on Cervical Cancer DWI-MRI

Ramli Z, Karim MKA, Effendy N, Abd Rahman MA, Kechik MMA, Ibahim MJ, et al.

Diagnostics (Basel), 2022 Dec 12;12(12).
PMID: 36553132 DOI: 10.3390/diagnostics12123125

Cervical cancer is the most common cancer and ranked as 4th in morbidity and mortality among Malaysian women. Currently, Magnetic Resonance Imaging (MRI) is considered as the gold standard imaging modality for tumours with a stage higher than IB2, due to its superiority in diagnostic assessment of tumour infiltration with excellent soft-tissue contrast. In this research, the robustness of semi-automatic segmentation has been evaluated using a flood-fill algorithm for quantitative feature extraction, using 30 diffusion weighted MRI images (DWI-MRI) of cervical cancer patients. The relevant features were extracted from DWI-MRI segmented images of cervical cancer. First order statistics, shape features, and textural features were extracted and analysed. The intra-class relation coefficient (ICC) was used to compare 662 radiomic features extracted from manual and semi-automatic segmentations. Notably, the features extracted from the semi-automatic segmentation and flood filling algorithm (average ICC = 0.952 0.009, p > 0.05) were significantly higher than the manual extracted features (average ICC = 0.897 0.011, p > 0.05). Henceforth, we demonstrate that the semi-automatic segmentation is slightly expanded to manual segmentation as it produces more robust and reproducible radiomic features.
Fulltext Optimized Intelligent Classifier for Early Breast Cancer Detection Using Ultra-Wide Band Transceiver

Halim AAA, Andrew AM, Mustafa WA, Mohd Yasin MN, Jusoh M, Veeraperumal V, et al.

Diagnostics (Basel), 2022 Nov 19;12(11).
PMID: 36428930 DOI: 10.3390/diagnostics12112870

Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary to remove the cancerous cells and prolong life. For early breast cancer detection, it is crucial to propose a robust intelligent classifier with statistical feature analysis that considers parameter existence, size, and location. This paper proposes a novel Multi-Stage Feature Selection with Binary Particle Swarm Optimization (MSFS-BPSO) using Ultra-Wideband (UWB). A collection of 39,000 data samples from non-tumor and with tumor sizes ranging from 2 to 7 mm was created using realistic tissue-like dielectric materials. Subsequently, the tumor models were inserted into the heterogeneous breast phantom. The breast phantom with tumors was imaged and represented in both time and frequency domains using the UWB signal. Consequently, the dataset was fed into the MSFS-BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. Feature selection using Analysis of Variance (ANOVA) is able to distinguish between class-correlated data. Finally, the optimum feature subset was selected using a Probabilistic Neural Network (PNN) classifier with the Binary Particle Swarm Optimization (BPSO) method. The research findings found that the MSFS-BPSO method has increased classification accuracy up to 96.3% and given good dependability even when employing an enormous data sample.
Fulltext Performance Analysis of Linearly Arranged Concentric Circular Antenna Array with Low Sidelobe Level and Beamwidth Using Robust Tapering Technique

Rahaman I, Haque MA, Singh NSS, Jafor MS, Sarkar PK, Rahman MA, et al.

Micromachines (Basel), 2022 Nov 11;13(11).
PMID: 36422388 DOI: 10.3390/mi13111959

In this research, a novel antenna array named Linearly arranged Concentric Circular Antenna Array (LCCAA) is proposed, concerning lower beamwidth, lower sidelobe level, sharp ability to detect false signals, and impressive SINR performance. The performance of the proposed LCCAA beamformer is compared with geometrically identical existing beamformers using the conventional technique where the LCCAA beamformer shows the lowest beamwidth and sidelobe level (SLL) of 12.50° and -15.17 dB with equal elements accordingly. However, the performance is degraded due to look direction error, for which robust techniques, fixed diagonal loading (FDL), optimal diagonal loading (ODL), and variable diagonal loading (VDL), are applied to all the potential arrays to minimize this problem. Furthermore, the LCCAA beamformer is further simulated to reduce the sidelobe applying tapering techniques where the Hamming window shows the best performance having 17.097 dB less sidelobe level compared to the uniform window. The proposed structure is also analyzed under a robust tapered (VDL-Hamming) method which reduces around 69.92 dB and 48.39 dB more sidelobe level compared to conventional and robust techniques. Analyzing all the performances, it is clear that the proposed LCCAA beamformer is superior and provides the best performance with the proposed robust tapered (VDL-Hamming) technique.
Fulltext Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019

Global Burden of Disease 2019 Cancer Collaboration, Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, et al.

JAMA Oncol, 2022 Mar 01;8(3):420-444.
PMID: 34967848 DOI: 10.1001/jamaoncol.2021.6987

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden.
OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019.
EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).
FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles.
CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.
Oilfield-produced water treatment using conventional and membrane-based technologies for beneficial reuse: A critical review

Samuel O, Othman MHD, Kamaludin R, Sinsamphanh O, Abdullah H, Puteh MH, et al.

J Environ Manage, 2022 Feb 03;308:114556.
PMID: 35124308 DOI: 10.1016/j.jenvman.2022.114556

Oilfield produced water (OPW) is one of the most important by-products, resulting from oil and gas exploration. The water contains a complex mixture of organic and inorganic compounds such as grease, dissolved salt, heavy metals as well as dissolved and dispersed oils, which can be toxic to the environment and public health. This article critically reviews the complex properties of OPW and various technologies for its treatment. They include the physico-chemical treatment process, biological treatment process, and physical treatment process. Their technological strengths and bottlenecks as well as strategies to mitigate their bottlenecks are elaborated. A particular focus is placed on membrane technologies. Finally, further research direction, challenges, and perspectives of treatment technologies for OPW are discussed. It is conclusively evident from 262 published studies (1965-2021) that no single treatment method is highly effective for OPW treatment as a stand-alone process however, conventional membrane-based technologies are frequently used for the treatment of OPW with the ultrafiltration (UF) process being the most used for oil rejection form OPW and oily waste water. After membrane treatment, treated effluents of the OPW could be reused for irrigation, habitant and wildlife watering, microalgae production, and livestock watering. Overall, this implies that target pollutants in the OPW samples could be removed efficiently for subsequent use, despite its complex properties. In general, it is however important to note that feed quality, desired quality of effluent, cost-effectiveness, simplicity of process are key determinants in choosing the most suitable treatment process for OPW treatment.
Fulltext Clinical characteristics and outcomes of critically ill coronavirus disease 2019 patients in Malaysia during the first wave: A multi-center observational study (COVIDICU-MY)

Ab Rahman NI, Yunos NM, Atan R, Mariapun J, Ab Rahman MA, Ismail AJ, et al.

Front Med (Lausanne), 2022;9:1086288.
PMID: 36698832 DOI: 10.3389/fmed.2022.1086288

BACKGROUND: Coronavirus disease 2019 (COVID-19) emerged with a wide range of clinical presentations; Malaysia was not spared from its impact. This study describes the clinical characteristics of COVID-19 patients admitted to intensive care unit, their clinical course, management, and hospital outcomes.
METHODS: COVIDICU-MY is a retrospective analysis of COVID-19 patients from 19 intensive care units (ICU) across Malaysia from 1 March 2020 to 31 May 2020. We collected epidemiological history, demographics, clinical comorbidities, laboratory investigations, respiratory and hemodynamic values, management, length of stay and survival status. We compared these variables between survival and non-survival groups.
RESULTS: A total of 170 critically ill patients were included, with 77% above 50 years of age [median age 60, IQR (51-66)] and 75.3% male. Hypertension, diabetes mellitus, hyperlipidemia, chronic cardiac disease, and chronic kidney disease were most common among patients. A high Simplified Acute Physiology Score (SAPS) II score [median 45, IQR (34-49)] and Sequential Organ Failure Assessment (SOFA) score [median 8, IQR (6-11)] were associated with mortality. Patients were profoundly hypoxic with a median lowest PaO2/FiO2 ratio of 150 (IQR 99-220) at admission. 91 patients (53.5%) required intubation on their first day of admission, out of which 38 died (73.1% of the hospital non-survivors). Our sample had more patients with moderate Acute Respiratory Distress Syndrome (ARDS), 58 patients (43.9%), compared to severe ARDS, 33 patients (25%); with both ARDS classification groups contributing to 25 patients (54.4%) and 11 patients (23.9%) of the non-survival group, respectively. Cumulative fluid balance over 24 h was higher in the non-survival group with significant differences on Day 3 (1,953 vs. 622 ml, p < 0.05) and Day 7 of ICU (3,485 vs. 830 ml, p < 0.05). Patients with high serum creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and low lymphocyte count throughout the stay also had a higher risk of mortality. The hospital mortality rate was 30.6% in our sample.
CONCLUSION: We report high mortality amongst critically ill patients in intensive care units in Malaysia, at 30.6%, during the March to May 2020 period. High admission SAPS II and SOFA, and severe hypoxemia and high cumulative fluid balance were associated with mortality. Higher creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and lymphopenia were observed in the non-survival group.
Fulltext A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization

Biswas K, Nazir A, Rahman MT, Khandaker MU, Idris AM, Islam J, et al.

PLoS One, 2022;17(1):e0261427.
PMID: 35085239 DOI: 10.1371/journal.pone.0261427

Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO's exploration phase is enhanced, and the SHO's hunting mechanisms are modified with PSO's velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization.
Fulltext Optimization of a High-Performance Poly(diallyl dimethylammonium chloride)-alumina-perfluorooctanoate Intercalated Ultrafiltration Membrane for Treating Emulsified Oily Wastewater via Response Surface Methodology Approach

Raji YO, Othman MHD, Nordin NAHSM, Adam MR, Said KAM, Abdulyekeen KA, et al.

Membranes (Basel), 2021 Dec 01;11(12).
PMID: 34940457 DOI: 10.3390/membranes11120956

This research aimed to investigate the ultrafiltration of water from emulsified oily wastewater through the application of surface-functionalized ceramic membrane to enhance its water permeability based on optimized parameters using a cross-flow filtration system. The interactive effects of feed concentration (10-1000 ppm), pH (4-10), and pressure (0-3 bar) on the water flux and oil rejection were investigated. Central composite design (CCD) from response surface methodology (RSM) was employed for statistical analysis, modeling, and optimization of operating conditions. The analysis of variance (ANOVA) results showed that the oil rejection and water flux models were significant with p-values of 0.0001 and 0.0075, respectively. In addition, good correlation coefficients of 0.997 and 0.863 were obtained for the oil rejection and water flux models, respectively. The optimum conditions for pressure, pH, and feed concentration were found to be 1.5 bar, pH 8.97, and 10 ppm, respectively with water flux and oil rejection maintained at 152 L/m2·h and 98.72%, respectively. Hence, the functionalized ultrafiltration ceramic membrane enables the separation efficiency of the emulsified oil in water to be achieved.

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