Islamic University in Uganda

BACKGROUND: COVID-19 is still a major global threat for which vaccination remains the ultimate solution. Uganda reported 40,751 cases and 335 deaths as of 9 April 2021 and started its vaccination program among priority groups like health workers, teachers, those with chronic diseases among others in early March 2021. Unanimous uptake of the COVID-19 vaccine is required to subsequently avert its spread; therefore, we assessed COVID-19 vaccine acceptability, hesitancy, and associated factors among medical students in Uganda. METHODS: This study employed an online descriptive cross-sectional survey among medical students across 10 medical schools in Uganda. A structured questionnaire via Google Form was conveniently sent to eligible participants via WhatsApp. Each medical school had a coordinator who consistently shared the data tool in the WhatsApp groups. Chi-square or Fisher's exact test, and logistic regression were used to assess the association between vaccine acceptability with demographics, COVID-19 risk perception, and vaccine hesitancy. RESULTS: We surveyed 600 medical students, 377 (62.8%) were male. COVID-19 vaccine acceptability was 37.3% and vaccine hesitancy 30.7%. Factors associated with vaccine acceptability were being male (adjusted odds ratio (aOR) = 1.9, 95% CI 1.3-2.9, p=0.001) and being single (aOR= 2.1, 95% CI 1.1-3.9, p=0.022). Very high (aOR= 3.5, 95% CI 1.7-6.9, p<0.001) or moderate (aOR =2.2, 95% CI 1.2-4.1, p=0.008) perceived risk of getting COVID-19 in the future, receiving any vaccine in the past 5 years (aOR= 1.6, 95% CI 1.1-2.5, p=0.017), and COVID-19 vaccine hesitancy (aOR 0.6, 95% CI 0.4-0.9, p=0.036). CONCLUSIONS: This study revealed low levels of acceptance towards the COVID-19 vaccine among medical students, low self-perceived risks of COVID-19, and many had relied on social media that provided them with negative information. This poses an evident risk on the battle towards COVID-19 in the future especially when these future health professions are expected to be influencing decisions of the general public towards the same.

BACKGROUND: The global consumption of herbal medicine is increasing steadily, posing an extinction risk to medicinal plants. Uganda is among the top ten countries with a high threat of herbal medicine extinction, and Traditional Medicinal Knowledge (TMK) erosion. This might be attributed to the inadequate documentation, plus many more unclear hindrances. In this study, plant species used to treat human diseases in Butaleja district in Eastern Uganda and their associated TMK were documented. The conservation methods for medicinal plants were also evaluated. The rationale was to support the preservation of ethnopharmacological knowledge. METHODS: Data were collected from 80 herbalists using semi-structured questionnaires, from July 2020 to March 2021. Additionally, guided field walks and observations were conducted. Quantitative indices such as, use categories and informant consensus factor (ICF) were evaluated to elucidate the importance of the medicinal plants. Data were analyzed using STATA version-15.0 software. RESULTS: In total, 133 species, belonging to 34 families and 125 genera were identified. Fabaceae (65%), and Solanaceae (29%) were the dominant families. Leaves (80%), and roots (15%), were the commonest parts used in medicinal preparations; mostly administered orally as decoctions (34.6%) and infusions (16%). The commonest illnesses treated were cough (7.74%), gastric ulcers (7.42%), and malaria (4.52%). The informant consensus factor was high for all disease categories (≥ 0.8), indicating homogeneity of knowledge about remedies used. Only 73% of the respondents made efforts to conserve medicinal plants. The commonest conservation strategy was preservation of forests with spiritually valued species (100%), while compliance with government regulations was the rarest (4.5%). Overall, efforts to stop the extinction of medicinal plants and TMK were inadequate. CONCLUSION AND RECOMMENDATIONS: There was enormous dependency on a rich diversity of medicinal plant species and TMK for healthcare and income generation. The potential for medicinal plant biodiversity loss was evident due to habitat destruction. Inclusion of traditional cultural norms in conservation strategies, and laboratory-based efficacy tests for the species identified are necessary, to promote the conservative and utilization of validated herbal medicines and TMK in rural settings.

Abstract Objective Green synthesized iron(III) oxide (Fe 3 O 4 ) nanoparticles are gaining appeal in targeted drug delivery systems because of their low cost, fast processing and nontoxicity. However, there is no known research work undertaken in the production of green synthesized nano-particles from the Ugandan grown Moringa Oleifera (MO). This study aims at exploring and developing an optimized protocol aimed at producing such nanoparticles from the Ugandan grown Moringa. Results While reducing ferric chloride solution with Moringa oleifera leaves, Iron oxide nanoparticles (Fe 3 O 4 -NPs) were synthesized through an economical and completely green biosynthetic method. The structural properties of these Fe 3 O 4 -NPs were investigated by Ultra Violet–visible (UV–Vis) spectrophotometry, X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX) and scanning electron microscopy (SEM). These nanoparticles exhibited UV–visible absorption peaks at 225 nm (nm) for the sixth dilution and 228 nm for the fifth dilution which indicated that the nanoparticles were photosensitive and the SEM study confirmed the spherical nature of these nanoparticles. The total synthesis time was approximately 5 h after drying the moringa leaves, and the average particle size was approximately 16 nm. Such synthesized nanoparticles can potentially be useful for drug delivery, especially in Low and Middle Income Countries (LMICs).

BACKGROUND: The coronavirus disease (COVID-19) pandemic is a global public health concern affecting over 5 million people and posing a great burden on health care systems worldwide. OBJECTIVE: The aim of this study is to determine the knowledge, attitude, and practices of medical students in Uganda on the COVID-19 pandemic. METHODS: We conducted an online, descriptive cross-sectional study in mid-April 2020, using WhatsApp Messenger. Medical students in 9 of the 10 medical schools in Uganda were approached through convenience sampling. Bloom's cut-off of 80% was used to determine good knowledge (≥12 out of 15), positive attitude (≥20 out of 25), and good practice (≥12 out of 15). RESULTS: The data of 741 first- to fifth-year medical students, consisting of 468 (63%) males with a mean age of 24 (SD 4) years, were analyzed. The majority (n=626, 84%) were pursuing Bachelor of Medicine and Bachelor of Surgery degrees. Overall, 671 (91%) had good knowledge, 550 (74%) had a positive attitude, and 426 (57%) had good practices. Knowledge was associated with the 4th year of study (adjusted odds ratio [aOR] 4.1, 95% CI 1.6-10.3; P<.001). Attitude was associated with the female sex (aOR 0.7, 95% CI 0.5-1; P=.04) and TV or radio shows (aOR 1.1, 95% CI 0.6-2.1; P=.01). Practices were associated with the ≥24 years age category (aOR 1.5, 95% CI 1.1-2.1; P=.02) and online courses (aOR 1.8, 95% CI 1.1-3.2; P=.03). In total, 592 (80%) medical students were willing to participate in frontline care if called upon. CONCLUSIONS: Medical students in Uganda have sufficient knowledge of COVID-19 and will be a large reservoir for health care response when the need arises.

The identification of plant species is fundamental for the effective study and management of biodiversity. In a manual identification process, different characteristics of plants are measured as identification keys which are examined sequentially and adaptively to identify plant species. However, the manual process is laborious and time-consuming. Recently, technological development has called for more efficient methods to meet species' identification requirements, such as developing digital-image-processing and pattern-recognition techniques. Despite several existing studies, there are still challenges in automating the identification of plant species accurately. This study proposed designing and developing an automated real-time plant species identification system of medicinal plants found across the Borneo region. The system is composed of a computer vision system that is used for training and testing a deep learning model, a knowledge base that acts as a dynamic database for storing plant images, together with auxiliary data, and a front-end mobile application as a user interface to the identification and feedback system. For the plant species identification task, an EfficientNet-B1-based deep learning model was adapted and trained/tested on a combined public and private plant species dataset. The proposed model achieved 87% and 84% Top-1 accuracies on a test set for the private and public datasets, respectively, which is more than a 10% accuracy improvement compared to the baseline model. During real-time system testing on the actual samples, using our mobile application, the accuracy slightly dropped to 78.5% (Top-1) and 82.6% (Top-5), which may be related to training data and testing conditions variability. A unique feature of the study is the provision of crowdsourcing feedback and geo-mapping of the species in the Borneo region, with the help of the mobile application. Nevertheless, the proposed system showed a promising direction toward real-time plant species identification system.

Devices are increasingly getting connected to the internet with the advances in technologies called the Internet of Things (IoT). The IoTs are the physical device in which are embedded with software, sensors, among other technologies. Linking and switching data resources with other devices, IoT has been recognized to be a trending research arena due to the world’s technological advancement. Every stage of technology avails several capacities, for instance, the IoT avails any device, anyone, any service, any technological path or any network, any place, and any context to be connected. The effective IoT applications permit public and private business organizations to regulate their assets, optimize the performance of the business, and develop new business models. In this study, we scrutinize the IoT progress as an approach to the technological upgrade through analyzing traits, architectures, applications, enabling technologies, and future challenges. To enable an aging society, and optimize different kinds of mobility and transportation, and helps to enhance the effectiveness of energy, along with the definition and characteristics of the IoT devices, the study examined the architecture of the IoT that includes the perception layer, transmission layer, application layer, and network management. It discusses the enabling technologies of the IoT that include application domain, middleware domain, network domain, and object domain. The study further evaluated the role of the IoT and its application in the everyday lives of the people by making smart cities, smart agriculture and waste management, retail and logistics, and smart environment. Besides the benefits, the IoT has demonstrated future technological challenges and is equally explained within the study.

BACKGROUND: The epidemiology of hepatitis B virus (HBV) in the general population in east Africa is not well documented. In this meta-analysis, we examined 37 full published research articles to synthesise up-to-date data on the prevalence and predictors of the HBV burden for the effective prevention and management of the virus in our region. METHODS: statistics for heterogeneity were calculated using MedCalc software version 19.1.3. Begg's tests was used to test for publication bias. Sources of heterogeneity were analysed through sensitivity analysis, meta-regression, and sub-group analysis at 95% CI. P < 0.05 was considered significant for all analyses. RESULTS: The prevalence of HBV was generally high (6.025%), with publications from Kenya (8.54%), Uganda (8.454%) and those from between 2011 and 2015 (8.759%) reporting the highest prevalence (P < 0.05). Blood transfusion, scarification, promiscuity, HIV seropositivity, and being male were independent predictors significantly associated with HBV infection (P < 0.05), with the male sex being the most strongly associated predictor of HBV infection. Meta-regressions for the pooled HBV prevalence and sample size, as well as the year of publication, lacked statistical significance (P > 0.05). Omitting the study with the largest sample size slightly increased pooled HBV prevalence to 6.149%, suggesting that the studies are robust. Begg's test showed no evidence of publication bias for overall meta-analysis (p > 0.05). CONCLUSION: The burden of HBV is still high, with the male sex, blood transfusion, body scarification, and HIV seropositivity being potential predictors of infection. Thus, it is important to scale up control and prevention measures targeting persons at high risk.

In 1992 the Islamic Medical Association of Uganda designed an AIDS prevention project and conducted a baseline survey prior to community level activities. Results of that baseline were previously reported in this journal. During 2 years of prevention activities in local Muslim communities, 23 trainers educated over 3,000 religious leaders and their assistants, who in turn educated their communities on AIDS during home visits and at religious gatherings. After 2 years, there was a significant increase in correct knowledge of HIV transmission, methods of preventing HIV infection and the risk associated with ablution of the dead and unsterile circumcision (p < 0.001). There was a significant reduction in self-reported sexual partners among the young respondents less than 45 years. In addition there was a significant increase in self-reported condom use among males in urban areas (p < 0.001). Collaboration between health professionals and religious leaders can be achieved and can contribute to the success of AIDS prevention efforts.

Examined was the effect of post mortem refrigerated storage on microbial spoilage, lipid-protein oxidation and physicochemical traits of goat meat. Seven Boer bucks were slaughtered, eviscerated and aged for 24 h. The Longissimus lumborum (LL) and Semitendinosus (ST) muscles were excised and subjected to 13 days post mortem refrigerated storage. The pH, lipid and protein oxidation, tenderness, color and drip loss were determined in LL while microbiological analysis was performed on ST. Bacterial counts generally increased with increasing aging time and the limit for fresh meat was reached at day 14 post mortem. Significant differences were observed in malondialdehyde (MDA) content at day 7 of storage. The thiol concentration significantly reduced as aging time increased. The band intensities of myosin heavy chain (MHC) and troponin-T significantly decreased as storage progressed, while actin remained relatively stable. After 14 days of aging, tenderness showed significant improvement while muscle pH and drip loss reduced with increase in storage time. Samples aged for 14 days had higher lightness (P < 0.05) and lower (P < 0.05) yellowness and redness. Post mortem refrigerated storage influenced oxidative and microbial stability and physico-chemical properties of goat meat.

Human immunodeficiency virus (HIV) infection is a public health challenge that can degenerate into acquired immunodeficiency syndrome (AIDS) if not properly managed. HIV infection shortens life expectancy to about 5 to 10 years compared to noninfected individuals. People living with HIV/AIDS (PLWHA) are prone to several health challenges as a result of a deranged immune system culminating in high morbidity and mortality. Depression is a common feature of PLWHA. Depression heightens the emergence of opportunistic infections in HIV-infected individuals, accelerates the progression to AIDS, and increased suicidal tendencies, morbidity, and mortality. Food insecurity with its resultant undernutrition contributes to HIV/AIDS-related deaths. Undernourished PLWHA are more prone to opportunistic infections due to poor immunity. Interestingly, proper diet intake can boost immunity, slow the progression of AIDS and opportunistic infections, enhance body weight, and retard depression tendencies. Undernutrition can also be ameliorated by incorporating nutritional counseling and oral nutrient supplementation in routine HIV/AIDS checkups. Therefore, to increase HIV/AIDS management outcomes, the integration of nutrition counseling, dietary supplements, and mental health services should be embraced. Thus, HIV/AIDS care centers should amplify these services. In this article, we isolated relevant studies from various databases, illuminated the interwoven relationship between HIV/AIDS, depression, and undernutrition, and also reemphasized the need for adequate nutritional intervention in the battle against HIV/AIDS. Thus, this study provides a reawakening call to focus on incorporating nutritional guides and mental health care in HIV/AIDS management protocols.

BACKGROUND: The World Health Organization has recently declared a new coronavirus disease (COVID-19) a pandemic and a global health emergency. The pressure to produce drugs and vaccines against the ongoing pandemic has resulted in the use of some drugs such as azithromycin, chloroquine (sulfate and phosphate), hydroxychloroquine, dexamethasone, favipiravir, remdesivir, ribavirin, ivermectin, and lopinavir/ritonavir. However, reports from some of the clinical trials with these drugs have proved detrimental on some COVID-19 infected patients with side effects more of which cardiomyopathy, cardiotoxicity, nephrotoxicity, macular retinopathy, and hepatotoxicity have been recently reported. Realizing the need for potent and harmless therapeutic compounds to combat COVID-19, we attempted in this study to find promising therapeutic compounds against the imminent threat of this virus. In this current study, 16 derivatives of gallic acid were docked against five selected non-structural proteins of SARS-COV-2 known to be a good target for finding small molecule inhibitors against the virus, namely, nsp3, nsp5, nsp12, nsp13, and nsp14. All the protein crystal structures and 3D structures of the small molecules (16 gallic acid derivatives and 3 control drugs) were retrieved from the Protein database (PDB) and PubChem server respectively. The compounds with lower binding energy than the control drugs were selected and subjected to pharmacokinetics screening using AdmetSAR server. RESULTS: 4-O-(6-galloylglucoside) gave binding energy values of - 8.4, - 6.8, - 8.9, - 9.1, and - 7.5 kcal/mol against Mpro, nsp3, nsp12, nsp13, and nsp15 respectively. Based on the ADMET profile, 4-O-(6-galloylglucoside) was found to be metabolized by the liver and has a very high plasma protein binding. CONCLUSION: The result of this study revealed that 4-O-(6-galloylglucoside) could be a promising inhibitor against these SAR-Cov-2 proteins. However, there is still a need for further molecular dynamic simulation, in vivo and in vitro studies to support these findings.

The application of Big Data Analytics is identified through the Cyber Research Alliance for cybersecurity as the foremost preference for future studies and advancement in the field of cybersecurity. In this study, we develop a repeatable procedure for detecting cyber-attacks in an accurate, scalable, and timely manner. An in-depth learning algorithm is utilized for training a neural network for detecting suspicious user activities. The proposed system architecture was implemented with the help of Splunk Enterprise Edition 6.42. A data set of average feature counts has been executed through a Splunk search command in 1-min intervals. All the data sets consisted of a minute trait total derived from a sparkling file. The attack patterns that were not anonymized or were indicative of the vulnerability of cyber-attack were denoted with yellow. The rule-based method dispensed a low quantity of irregular illustrations in contrast with the Partitioning Around Medoids method. The results in this study demonstrated that using a proportional collection of instances trained with the deep learning algorithm, a classified data set can accurately detect suspicious behavior. This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.

Moringa oleifera Lam., Moringaceae, and Telfairia occidentalis Hook. f., Curcubitaceae, leaves are two tropical vegetables of medicinal properties. In this study, the inhibitory activities and the radical scavenging potentials of these vegetables on relevant enzymes of type 2-diabetes (α-amylase and α-glucosidase) were evaluated in vitro. HPLC-DAD was used to characterize the phenolic constituents and Fe2+-induced lipid peroxidation in rat's pancreas was investigated. Various radical scavenging properties coupled with metal chelating abilities were also determined. However, phenolic extracts from the vegetables inhibited α-amylase, α-glucosidase and chelated the tested metals (Cu2+ and Fe2+) in a concentration-dependent manner. More so, the inhibitory properties of phenolic rich extracts from these vegetables could be linked to their radical scavenging abilities. Therefore, this study may offer a promising prospect for M. oleifera and T. occidentalis leaves as a potential functional food sources in the management of type 2-diabetes mellitus.

Forest Change Detection (FCD) is a critical component of natural resource monitoring and conservation strategies, enabling informed decision-making. Various methods utilizing the power of artificial intelligence (AI) have been developed for detecting and categorizing changes in forest cover using remote sensing (RS) data. One prominent AI-powered approach is the U-Net, a deep learning (DL) architecture famous for its segmentation proficiency. However, the standard U-Net architecture fails to effectively capture intricate spatial dependencies and long-range contextual information present in remote sensing imagery. To address this research gap, we introduce an attention-residual-based novel DL model which leverages the U-Net architecture and Sentinel-2 satellite images to map alterations in forest vegetation cover in the tropical region. Our novel model enhances the U-Net architecture by seamlessly integrating the strengths of the U-Net, harnessing attention mechanisms strategically to amplify crucial features, and leveraging cutting-edge residual connections to facilitate the smooth flow of information and gradient propagation. These meticulous design choices enabled the precise feature extraction, resulting in improved computational performance of the proposed method compared to the Standard U-Net, Deeplabv3+, Deep Res-U-Net, and Attention U-Net. The classification results demonstrate the enhanced efficiency of our model, achieving a Mean Intersection over Union (MIoU) of 0.9330 on our test dataset. This performance surpasses the Attention U-Net (0.9146), Standard U-Net (0.9029), Deeplabv3+ (0.9247), and Deep Res-U-Net (0.9282). The comparative analysis of ground truth reproductions unveiled the superior detection capabilities of our model in accurately identifying forest and non-forest polygons, surpassing both the standard U-Net, and the U-Net augmented with attention mechanism, along with other state-of-the-art techniques, thereby highlighting its enhanced efficacy. The model’s broad applicability can support forest managers and ecologists in rapidly evaluating the long-term ramifications of infrastructure initiatives, such as roads, on tropical forests, including those in Brunei.

Hepatitis B virus (HBV) has ten genotypes (A-J) and over 40 sub-genotypes based on the divergence of ≥ 8% and 4 to < 8% in the complete genome respectively. These genotypes and sub-genotypes influence the disease prognosis, response to therapy and route of viral transmission. Besides, infection with mixed genotypes and recombinant genotypes has also been reported. This study aimed at mapping the de novo genotypes and correlate them with the immigration trends in order to inform future research on the underlying reasons for the relative distribution of HBV genotypes from a large sample size pooled from many primary studies. Data was extracted from 59 full research articles obtained from Scopus, PubMed, EMBASE, Willy library, African Journal Online (AJOL) and Google Scholar. Studies that investigated the genotypes, sub-genotypes, mixed genotypes and recombinant were included. The Z-test and regression were used for the analysis. The study protocol is registered with PROSPERO under the registration number CRD42022300220. Overall, genotype E had the highest pooled prevalence significantly higher than all the other genotypes (P < 0.001). By region, genotype A posted the highest pooled prevalence in eastern and southern Africa, E in west Africa and D in north Africa (P < 0.0001). Regarding the emerging genotypes B and C on the African continent, genotype B was significantly higher in south Africa than C (P < 0.001). In contrast, genotype C was significantly higher in east Africa than west Africa (P < 0.0001). The A1 and D/E were the most diverse sub-genotypes and genotype mixtures respectively. Finally, we observed a general progressive decrease in the prevalence of predominant genotypes but a progressive increase in the less dominant by region. Historical and recent continental and intercontinental migrations can provide a plausible explanation for the HBV genotype distribution pattern on the African continent.

Acanthamoeba spp. can cause amoebic keratitis (AK). Chlorhexidine is effective for AK treatment as monotherapy, but with a relative failure on drug bioavailability in the deep corneal stroma. The combination of chlorhexidine and propamidine isethionate is recommended in the current AK treatment. However, the effectiveness of treatment depends on the parasite and virulence strains. This study aims to determine the potential of Garcinia mangostana pericarp extract and α-mangostin against Acanthamoeba triangularis, as well as the combination with chlorhexidine in the treatment of Acanthamoeba infection. The minimal inhibitory concentrations (MICs) of the extract and α-mangostin were assessed in trophozoites with 0.25 and 0.5 mg/mL, for cysts with 4 and 1 mg/mL, respectively. The MIC of the extract and α-mangostin inhibited the growth of A. triangularis trophozoites and cysts for up to 72 h. The extract and α-mangostin combined with chlorhexidine demonstrated good synergism, resulting in a reduction of 1/4-1/16 of the MIC. The SEM results showed that Acanthamoeba cells treated with a single drug and its combination caused damage to the cell membrane and irregular cell shapes. A good combination displayed by the extract or α-mangostin and chlorhexidine, described for the first time. Therefore, this approach is promising as an alternative method for the management of Acanthamoeba infection in the future.

This study based on cross-sectional survey approach examined E-learning interactivity which was hypothesised to be a multidimensional construct, its association with learner satisfaction continuing learning intentions. The Transactional Distance theory by Moore (1989) and the three-way model for computer-initiated interaction by Evans & Sabry (2003) formed the study’s theoretical framework. The quantitative data were collected using a 28-item questionnaire from 232 learners who had enrolled in various CISCO E-learning courses. Principle Components analysis revealed a three-factor structure of E-learning interactivity comprised of learner-content, learner-interface, and learner-E-learning system feedback interactivity. Additionally, Confirmatory Factor analysis confirmed the reliability and validity of the three-factor measurement model; while the SEM fit indices revealed that the structural model has achieved goodness-of-fit. Lastly, the results have confirmed that with the exception of learner-content, the other interactivity sub dimensions demonstrated a significant relationship with learner satisfaction, and in turn, learner satisfaction had a positive influence on continuance learning intention. The results have supported and extended previous works on E-learning interactivity. This study is important for making evidence-based decisions by E-learning instructional designers, interface designers, subject matter experts and instructors while designing, implementing and evaluating E-learning interventions for Open and distance learning.

BACKGROUND: The use of nutritional supplements (NS) places athletes at great risk for inadvertent doping. Due to the paucity of data on supplement use, this study aimed to determine the proportion of Ugandan athletes using nutritional supplements and to investigate the athletes' motivation to use these supplements. METHODS: A cross-sectional study was conducted in which an interviewer-administered questionnaire was used to collect data from 359 professional athletes participating in individual (boxing, cycling, athletics) and team (basketball, rugby, football, netball, and volleyball) sports. The data were categorized, and a Chi-square test was used for statistical analysis. RESULTS: < 0.0001). The athletes' occupation had no bearing on whether they used supplements. Nutritionists/dieticians, retail stores and pharmacies were the most common sources of NS products, whereas health practitioners, online media and teammates were the most common sources of information regarding NS. Most athletes used NS to improve their physical performance and health. CONCLUSIONS: Compared to NS use by athletes elsewhere, NS use among Ugandan athletes was low. However, determinants of athlete NS use in the current study (category of sport and duration of time spent playing the sport) are similar to those reported elsewhere.

In the context of healthcare, big data refers to a complex compilation of digital medical data collected from many sources that are difficult to manage with normal technology and software due to its size and complexity. These big data are useful in various aspects of healthcare, such as disease diagnosis, early prevention of diseases, and predicting epidemics. Even though medical big data has many advantages and a lot of potential for revolutionizing healthcare, it also has a lot of drawbacks and problems, of which security and privacy are of the utmost concern, owing to the severity of the complications once the medical data is compromised. On the other hand, it is evident that existing security and privacy safeguards in healthcare organizations are insufficient to protect their massive, big data repositories and ubiquitous environment. Thus, motivated by the synthesizing of the current knowledge pertaining to the security and privacy of medical big data, including the countermeasures, in the study, firstly, we provide a comprehensive review of the security and privacy of medical big data, including countermeasures. Secondly, we propose a novel cloud-enabled hybrid access control framework for securing the medical big data in healthcare organizations, and the result of this research indicates that the proposed access control model can withstand most cyber-attacks, and it is also proven that the proposed framework can be utilized as a primary base to build secure and safe medical big data solutions. Thus, we believe this research would be useful for future researchers to comprehend the knowledge on the security and privacy of medical big data and the development of countermeasures.

Curcuma longa and Curcumin have been documented to have a wide spectrum of pharmacological effects, including anti-Acanthamoeba activity. Hence, this study sought to explore the anti-adhesion activity of C. longa extract and Curcumin against Acanthamoeba triangularis trophozoites and cysts in plastic and contact lenses. Our results showed that C. longa extract and Curcumin significantly inhibited the adhesion of A. triangularis trophozoites and cysts to the plastic surface, as investigated by the crystal violet assay (P < 0.05). Also, an 80-90% decrease in adhesion of trophozoites and cysts to the plastic surface was detected following the treatment with C. longa extract and Curcumin at 1/2 × MIC, compared to the control. In the contact lens model, approximately 1 log cells/mL of the trophozoites and cysts was reduced when the cells were treated with Curcumin, when compared to the control. Pre-treatment of the plastic surface with Curcumin at 1/2-MIC reduced 60% and 90% of the adhesion of trophozoites and cysts, respectively. The reduction in 1 Log cells/mL of the adhesion of A. triangularis trophozoites was observed when lenses were pre-treated with both the extract and Curcumin. Base on the results obtained from this study, A. triangularis trophozoites treated with C. longa extract and Curcumin have lost strong acanthopodia, thorn-like projection pseudopodia observed by scanning electron microscope. This study also revealed the therapeutic potentials of C. longa extract and Curcumin, as such, have promising anti-adhesive potential that can be used in the management/prevention of A. triangularis adhesion to contact lenses.