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Fulltext An efficient algorithm for energy harvesting in IIoT based on machine learning and swarm intelligence

Xing P, Zhang H, Derbali M, Sefat SM, Alharbi AH, Khafaga DS, et al.

Heliyon, 2023 Jul;9(7):e17622.
PMID: 37424589 DOI: 10.1016/j.heliyon.2023.e17622

The Internet of Things (IoT) is a network of smart gadgets that are connected through the Internet, including computers, cameras, smart sensors, and mobile phones. Recent developments in the industrial IoT (IIoT) have enabled a wide range of applications, from small businesses to smart cities, which have become indispensable to many facets of human existence. In a system with a few devices, the short lifespan of conventional batteries, which raises maintenance costs, necessitates more replacements and has a negative environmental impact, does not present a problem. However, in networks with millions or even billions of devices, it poses a serious problem. The rapid expansion of the IoT paradigm is threatened by these battery restrictions, thus academics and businesses are now interested in prolonging the lifespan of IoT devices while retaining optimal performance. Resource management is an important aspect of IIoT because it's scarce and limited. Therefore, this paper proposed an efficient algorithm based on federated learning. Firstly, the optimization problem is decomposed into various sub-problems. Then, the particle swarm optimization algorithm is deployed to solve the energy budget. Finally, a communication resource is optimized by an iterative matching algorithm. Simulation results show that the proposed algorithm has better performance as compared with existing algorithms.
Fulltext Isolation of Acanthamoeba sp. from conjunctival sac of healthy individuals using swab

Anisah N, Amal H, Kamel AG, Yusof S, Noraina AR, Norhayati M

Trop Biomed, 2005 Jun;22(1):11-4.
PMID: 16880749 MyJurnal

Is Acanthamoeba sp. normally found in the eyes? A study was carried out to establish the possibility of Acanthamoeba sp. as a part of the normal conjunctival flora. Conjunctiva swabbing were carried out in 286 healthy Orang Asli school children using sterile cotton swab. The swab was then inoculated onto non-nutrient agar (NN-A). Heat killed Escherichia coli that was used as food source for the growth of the amoebae was pipetted onto and away from the smear. The plates were incubated at 30 degrees C and examined daily using an inverted microscope for 14 days. Morphology of the trophozoites and cysts of the amoebae were used as the taxonomic criteria for identification. Positive-controls and negative-controls were done to check for the consistency of the technique used and monitoring of contamination respectively. None of the conjunctiva swab cultured was positive for Acanthamoeba sp. This finding may indicate that Acanthamoeba sp. is not part of normal conjunctival flora or conjunctiva swab is an insensitive technique to isolate the organism. However, a more extensive research is needed to investigate these possibilities.
Fulltext Optimizing HCV Disease Prediction in Egypt: The hyOPTGB Framework

Elshewey AM, Shams MY, Tawfeek SM, Alharbi AH, Ibrahim A, Abdelhamid AA, et al.

Diagnostics (Basel), 2023 Nov 13;13(22).
PMID: 37998575 DOI: 10.3390/diagnostics13223439

The paper focuses on the hepatitis C virus (HCV) infection in Egypt, which has one of the highest rates of HCV in the world. The high prevalence is linked to several factors, including the use of injection drugs, poor sterilization practices in medical facilities, and low public awareness. This paper introduces a hyOPTGB model, which employs an optimized gradient boosting (GB) classifier to predict HCV disease in Egypt. The model's accuracy is enhanced by optimizing hyperparameters with the OPTUNA framework. Min-Max normalization is used as a preprocessing step for scaling the dataset values and using the forward selection (FS) wrapped method to identify essential features. The dataset used in the study contains 1385 instances and 29 features and is available at the UCI machine learning repository. The authors compare the performance of five machine learning models, including decision tree (DT), support vector machine (SVM), dummy classifier (DC), ridge classifier (RC), and bagging classifier (BC), with the hyOPTGB model. The system's efficacy is assessed using various metrics, including accuracy, recall, precision, and F1-score. The hyOPTGB model outperformed the other machine learning models, achieving a 95.3% accuracy rate. The authors also compared the hyOPTGB model against other models proposed by authors who used the same dataset.
Fulltext Corrigendum to "A narrative review of approved and emerging anti-obesity medications" [Saudi Pharm. J. 31(10) (2023) 101757]

Beshir SA, Elnour AA, Soorya A, Mohamed AP, Goh SSL, Hussain N, et al.

Saudi Pharm J, 2024 May;32(5):102047.
PMID: 38596318 DOI: 10.1016/j.jsps.2024.102047

[This corrects the article DOI: 10.1016/j.jsps.2023.101757.].
Fulltext A narrative review of approved and emerging anti-obesity medications

Abdi Beshir S, Ahmed Elnour A, Soorya A, Parveen Mohamed A, Sir Loon Goh S, Hussain N, et al.

Saudi Pharm J, 2023 Oct;31(10):101757.
PMID: 37712012 DOI: 10.1016/j.jsps.2023.101757

BACKGROUND: Recently, many drugs have been approved for halting overweight and obesity-few types of research shifted to using Anti-obesity medications (AOM) solely for well-being and shape-keeping.
OBJECTIVE: This narrative review's objective was to explore the use of AOM in relation to their medical indications, efficacy, and cardiovascular safety.
METHODS AND MATERIALS: We have conducted a narrative review of the literature on approved/non-approved AOM used for obesity and overweight. We have shed light on the emerging trials of therapies and evolving remedies.
RESULTS: Recently, there has been an enormous change in the use of AOM with high consumption that deserves extensive surveillance for the long-term consequences and impact on social, mental, and physical health. Nearly six AOMs and combined therapy are approved by the Food and Drug Administration. The recent guidelines for obesity management have shifted the focus from weight loss to goals that the patient considers essential and toward targeting the root cause of obesity.
CONCLUSION: The use of AOM increased enormously despite its sometimes-dubious safety and ineffectiveness. The public and medical professionals should be vigilant to the real-world benefits of anti-obesity drugs and their achieved effectiveness with an improved safety profile.
Fulltext A Comprehensive Review on the Current Vaccines and Their Efficacies to Combat SARS-CoV-2 Variants

Rabaan AA, Mutair AA, Hajissa K, Alfaraj AH, Al-Jishi JM, Alhajri M, et al.

Vaccines (Basel), 2022 Oct 02;10(10).
PMID: 36298520 DOI: 10.3390/vaccines10101655

Since the first case of Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, SARS-CoV-2 infection has affected many individuals worldwide. Eventually, some highly infectious mutants-caused by frequent genetic recombination-have been reported for SARS-CoV-2 that can potentially escape from the immune responses and induce long-term immunity, linked with a high mortality rate. In addition, several reports stated that vaccines designed for the SARS-CoV-2 wild-type variant have mixed responses against the variants of concern (VOCs) and variants of interest (VOIs) in the human population. These results advocate the designing and development of a panvaccine with the potential to neutralize all the possible emerging variants of SARS-CoV-2. In this context, recent discoveries suggest the design of SARS-CoV-2 panvaccines using nanotechnology, siRNA, antibodies or CRISPR-Cas platforms. Thereof, the present comprehensive review summarizes the current vaccine design approaches against SARS-CoV-2 infection, the role of genetic mutations in the emergence of new viral variants, the efficacy of existing vaccines in limiting the infection of emerging SARS-CoV-2 variants, and efforts or challenges in designing SARS panvaccines.
Inflammatory and vascular biomarkers in post-COVID-19 syndrome: A systematic review and meta-analysis of over 20 biomarkers

Yong SJ, Halim A, Halim M, Liu S, Aljeldah M, Al Shammari BR, et al.

Rev Med Virol, 2023 Mar;33(2):e2424.
PMID: 36708022 DOI: 10.1002/rmv.2424

Severe acute respiratory syndrome coronavirus 2 may inflict a post-viral condition known as post-COVID-19 syndrome (PCS) or long-COVID. Studies measuring levels of inflammatory and vascular biomarkers in blood, serum, or plasma of COVID-19 survivors with PCS versus non-PCS controls have produced mixed findings. Our review sought to meta-analyse those studies. A systematic literature search was performed across five databases until 25 June 2022, with an updated search on 1 November 2022. Data analyses were performed with Review Manager and R Studio statistical software. Twenty-four biomarkers from 23 studies were meta-analysed. Higher levels of C-reactive protein (Standardized mean difference (SMD) = 0.20; 95% CI: 0.02-0.39), D-dimer (SMD = 0.27; 95% CI: 0.09-0.46), lactate dehydrogenase (SMD = 0.30; 95% CI: 0.05-0.54), and leukocytes (SMD = 0.34; 95% CI: 0.02-0.66) were found in COVID-19 survivors with PCS than in those without PCS. After sensitivity analyses, lymphocytes (SMD = 0.30; 95% CI: 0.12-0.48) and interleukin-6 (SMD = 0.30; 95% CI: 0.12-0.49) were also significantly higher in PCS than non-PCS cases. No significant differences were noted in the remaining biomarkers investigated (e.g., ferritin, platelets, troponin, and fibrinogen). Subgroup analyses suggested the biomarker changes were mainly driven by PCS cases diagnosed via manifestation of organ abnormalities rather than symptomatic persistence, as well as PCS cases with duration of <6 than ≥6 months. In conclusion, our review pinpointed certain inflammatory and vascular biomarkers associated with PCS, which may shed light on potential new approaches to understanding, diagnosing, and treating PCS.
Experimental drugs in randomized controlled trials for long-COVID: what's in the pipeline? A systematic and critical review

Yong SJ, Halim A, Halim M, Ming LC, Goh KW, Alfaresi M, et al.

Expert Opin Investig Drugs, 2023;32(7):655-667.
PMID: 37534972 DOI: 10.1080/13543784.2023.2242773

INTRODUCTION: Over three years have passed since the emergence of coronavirus disease 2019 (COVID-19), and yet the treatment for long-COVID, a post-COVID-19 syndrome, remains long overdue. Currently, there is no standardized treatment available for long-COVID, primarily due to the lack of funding for post-acute infection syndromes (PAIS). Nevertheless, the past few years have seen a renewed interest in long-COVID research, with billions of dollars allocated for this purpose. As a result, multiple randomized controlled trials (RCTs) have been funded in the quest to find an effective treatment for long-COVID.
AREAS COVERED: This systematic review identified and evaluated the potential of current drug treatments for long-COVID, examining both completed and ongoing RCTs.
EXPERT OPINION: We identified four completed and 22 ongoing RCTs, investigating 22 unique drugs. However, most drugs were deemed to not have high potential for treating long-COVID, according to three pre-specified domains, a testament to the ordeal of treating long-COVID. Given that long-COVID is highly multifaceted with several proposed subtypes, treatments likely need to be tailored accordingly. Currently, rintatolimod appears to have modest to high potential for treating the myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) subtype, LTY-100 and Treamid for pulmonary fibrosis subtype, and metformin for general long-COVID prevention.
Pooled rates and demographics of POTS following SARS-CoV-2 infection versus COVID-19 vaccination: Systematic review and meta-analysis

Yong SJ, Halim A, Liu S, Halim M, Alshehri AA, Alshahrani MA, et al.

Auton Neurosci, 2023 Dec;250:103132.
PMID: 38000119 DOI: 10.1016/j.autneu.2023.103132

PURPOSE: To address recent concerns of postural orthostatic tachycardia syndrome (POTS) occurring after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination.
METHODS: We searched PubMed, Web of Science, and Scopus as of 1st June 2023. We performed a systematic review and meta-analysis of pooled POTS rate in SARS-CoV-2-infected and COVID-19-vaccinated groups from epidemiological studies, followed by subgroup analyses by characteristic. Meta-analysis of risk ratio was conducted to compare POTS rate in infected versus uninfected groups. Meta-analysis of demographics was also performed to compare cases of post-infection and post-vaccination POTS from case reports and series.
RESULTS: We estimated the pooled POTS rate of 107.75 (95 % CI: 9.73 to 273.52) and 3.94 (95 % CI: 0 to 16.39) cases per 10,000 (i.e., 1.08 % and 0.039 %) in infected and vaccinated individuals based on 5 and 2 studies, respectively. Meta-regression revealed age as a significant variable influencing 86.2 % variance of the pooled POTS rate in infected population (P