Repurposing ezetimibe as a neuroprotective agent in a rotenone-induced Parkinson's disease model in rats: Role of AMPK/SIRT-1/PGC-1α signaling and autophagy.

As a severe neurological disorder, Parkinson's disease (PD) is distinguished by dopaminergic neuronal degeneration in the substantia nigra (SN), culminating in motor impairments. Several studies have shown that activation of the AMPK/SIRT1/PGC1α pathway contributes to an increase in mitochondrial biogenesis and is a promising candidate for the management of PD. Furthermore, turning on the AMPK/SIRT1/PGC1α pathway causes autophagy activation, which is fundamental for maintaining neuronal homeostasis. Interestingly, ezetimibe is an antihyperlipidemic agent that was recently reported to possess pleiotropic properties in neurology by triggering the phosphorylation and activation of AMPK. Thus, our study aimed to investigate the neuroprotective potential of ezetimibe in rats with rotenone-induced PD by activating AMPK. Adult male Wistar rats received rotenone (1.5 mg/kg, s.c.) every other day for 21 days to induce experimental PD. Rats were treated with ezetimibe (5 mg/kg/day, i.p.) 1 h before rotenone. Ezetimibe ameliorated the motor impairments in open field, rotarod and grip strength tests, restored striatal dopamine and tyrosine hydroxylase in the SN, up-regulated p-AMPK, SIRT1, and PGC1α striatal expression, upsurged the expression of ULK1, beclin1, and LC3II/I, reduced Bax/Bcl2 ratio, and alleviated rotenone-induced histopathological changes in striatum and SN. Our findings also verified the contribution of AMPK activation to the neuroprotective effect of ezetimibe by using the AMPK inhibitor dorsomorphin. Together, this work revealed that ezetimibe exerts a neuroprotective impact in rotenone-induced PD by activating AMPK/SIRT-1/PGC-1α signaling, enhancing autophagy, and attenuating apoptosis. Thus, ezetimibe's activation of AMPK could hold significant therapeutic promise for PD management.

Fresh osteochondral allograft transplantation for knee full-thickness articular cartilage lesions using femoral head of living donors: short-term results.

BACKGROUND: Fresh osteochondral allograft transplantation is a good treatment option of cartilage defects. However, this treatment option is not available in all countries due to limited graft availability and tissue banks limitations. The purpose of this study is to assess the short term functional and imaging outcomes of fresh osteochondral allograft transplantation in the knee using the femoral head of living donors. HYPOTHESIS: Fresh osteochondral allografts from the femoral heads of living donors is a valid graft source for management of distal Femur cartilage defects. This technique can improve functional knee scores with good radiological outcomes. STUDY DESIGN: Prospective case series. METHODS: Fifteen patients with full thickness cartilage defects of the distal femur underwent osteochondral allograft transplantation from the femoral heads of living donors. Grafts were transplanted by both shell and multiple dowels techniques. The average follow up duration was 18.3 months (range, 12-25 months). Patients were evaluated by Lysholm and International Knee Documentation Committee (IKDC) scores, radiography and MR imaging using Osteochondral Allograft MRI Scoring System (OCAMRISS). RESULTS: There was a statistically significant improvement (P < 0.001) in both Lysholm and IKDC average scores at 6 months and 12 months postoperative. Postoperative MRI was done at an average 6.8 months (range, 5-11 months) postoperative. The mean total OCAMRISS score was 3.4 (range, 1-7). A second look arthroscopy was done in four patients and showed intact articular cartilage in all three patients. CONCLUSION: Femoral head of living donors is a valid new source for fresh osteochondral allograft transplantation of knee osteochondral lesions. Short term results showed improvement in clinical assessment scores. Follow up imaging showed graft incorporation and good MRI scores.

Performance Evaluation of Sinusoidal Power Supplies for Ozone Generation in Water Purification Applications.

Ozone generation is a water disinfection method, superior to chlorine in terms of fewer byproducts and no residual taste. However, its high production cost limits its widespread adoption. This paper designs an ozone generation sinusoidal power supply for water treatment. Ozone generation requires a high-frequency and high-voltage power supply to produce ozone from oxygen molecules. The study evaluates two power supply topologies, one with a parallel LC filter and the other with an LCL filter, assessing their feasibility, effectiveness, and reliability. Theoretically, the LCL filter achieves higher gains than the parallel LC filter. The larger inductance in the parallel LC filter reduces gain, while the larger inductance in the LCL filter increases gain. Simulation and practical results validate these findings, achieving gains of 40 for the parallel LC filter and 150 for the LCL filter.

Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G smart cities' IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework.

The growing importance of edge and fog computing in the modern IT infrastructure is driven by the rise of decentralized applications. However, resource allocation within these frameworks is challenging due to varying device capabilities and dynamic network conditions. Conventional approaches often result in poor resource use and slowed advancements. This study presents a novel strategy for enhancing resource allocation in edge and fog computing by integrating machine learning with the blockchain for reliable trust management. Our proposed framework, called CyberGuard, leverages the blockchain's inherent immutability and decentralization to establish a trustworthy and transparent network for monitoring and verifying edge and fog computing transactions. CyberGuard combines the Trust2Vec model with conventional machine-learning models like SVM, KNN, and random forests, creating a robust mechanism for assessing trust and security risks. Through detailed optimization and case studies, CyberGuard demonstrates significant improvements in resource allocation efficiency and overall system performance in real-world scenarios. Our results highlight CyberGuard's effectiveness, evidenced by a remarkable accuracy, precision, recall, and F1-score of 98.18%, showcasing the transformative potential of our comprehensive approach in edge and fog computing environments.

Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs.

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients' chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model's input requirements, we enhanced them through data augmentation techniques for training purposes. We evaluated the model's performance by analyzing the precision, recall, and F1 scores across training, validation, and testing datasets. The results show that the ResNet50 model outperformed VGG16 with accuracy and resilience. It displayed superior ROC AUC values in both validation and test scenarios. Particularly impressive were ResNet50's precision and recall rates, nearing 0.99 for all conditions in the test set. On the hand, VGG16 also performed well during testing-detecting tuberculosis with a precision of 0.99 and a recall of 0.93. Our study highlights the performance of our deep learning method by showcasing the effectiveness of ResNet50 over traditional approaches like VGG16. This progress utilizes methods to enhance classification accuracy by augmenting data and balancing them. This positions our approach as an advancement in using state-of-the-art deep learning applications in imaging. By enhancing the accuracy and reliability of diagnosing ailments such as COVID-19 and tuberculosis, our models have the potential to transform care and treatment strategies, highlighting their role in clinical diagnostics.

AI-Driven Real-Time Classification of ECG Signals for Cardiac Monitoring Using i-AlexNet Architecture.

The healthcare industry has evolved with the advent of artificial intelligence (AI), which uses advanced computational methods and algorithms, leading to quicker inspection, forecasting, evaluation and treatment. In the context of healthcare, artificial intelligence (AI) uses sophisticated computational methods to evaluate, decipher and draw conclusions from patient data. AI has the potential to revolutionize the healthcare industry in several ways, including better managerial effectiveness, individualized treatment regimens and diagnostic improvements. In this research, the ECG signals are preprocessed for noise elimination and heartbeat segmentation. Multi-feature extraction is employed to extract features from preprocessed data, and an optimization technique is used to choose the most feasible features. The i-AlexNet classifier, which is an improved version of the AlexNet model, is used to classify between normal and anomalous signals. For experimental evaluation, the proposed approach is applied to PTB and MIT_BIH databases, and it is observed that the suggested method achieves a higher accuracy of 98.8% compared to other works in the literature.

Correction: Synthesis, docking and biological evaluation of purine-5-N-isosteres as anti-inflammatory agents.

[This corrects the article DOI: 10.1039/D4RA02970D.].

Side-specific factors for intraoperative hemodynamic instability in laparoscopic adrenalectomy for pheochromocytoma: a comparative study.

BACKGROUND: Adrenalectomy for pheochromocytoma (PHEO) is challenging because of the high risk of intraoperative hemodynamic instability (HDI). This study aimed to compare the incidence and risk factors of intraoperative HDI between laparoscopic left adrenalectomy (LLA) and laparoscopic right adrenalectomy (LRA). METHODS: We retrospectively analyzed two hundred and seventy-one patients aged > 18 years with unilateral benign PHEO of any size who underwent transperitoneal laparoscopic adrenalectomy at our hospitals between September 2016 and September 2023. Patients were divided into LRA (N = 122) and LLA (N = 149) groups. Univariate and multivariate logistic regression analyses were used to predict intraoperative HDI. In multivariate analysis for the prediction of HDI, right-sided PHEO, PHEO size, preoperative comorbidities, and preoperative systolic blood pressure were included. RESULTS: Intraoperative HDI was significantly higher in the LRA group than in the LLA (27% vs. 9.4%, p < 0.001). In the multivariate regression analysis, right-sided tumours showed a higher risk of intraoperative HDI (odds ratio [OR] 5.625, 95% confidence interval [CI], 1.147-27.577, p = 0.033). The tumor size (OR 11.019, 95% CI 3.996-30.38, p < 0.001), presence of preoperative comorbidities [diabetes mellitus, hypertension, and coronary heart disease] (OR 7.918, 95% CI 1.323-47.412, p = 0.023), and preoperative systolic blood pressure (OR 1.265, 95% CI 1.07-1.495, p = 0.006) were associated with a higher risk of HDI in both LRA and LLA, with no superiority of one side over the other. CONCLUSION: LRA was associated with a significantly higher intraoperative HDI than LLA. Right-sided PHEO was a risk factor for intraoperative HDI.

Exploring chromone-2-carboxamide derivatives for triple-negative breast cancer targeting EGFR, FGFR3, and VEGF pathways: Design, synthesis, and preclinical insights.

Chromone-based compounds have established cytotoxic, antiproliferative, antimetastatic, and antiangiogenic effects on various cancer cell types via modulating different molecular targets. Herein, 17 novel chromone-2-carboxamide derivatives were synthesized and evaluated for their in vitro anticancer activity against 15 human cancer cell lines. Among the tested cell lines, MDA-MB-231, the triple-negative breast cancer cell line, was found to be the most sensitive, where the N-(2-furylmethylene) (15) and the α-methylated N-benzyl (17) derivatives demonstrated the highest growth inhibition with GI50 values of 14.8 and 17.1 µM, respectively. In vitro mechanistic studies confirmed the significant roles of compounds 15 and 17 in the induction of apoptosis and suppression of EGFR, FGFR3, and VEGF protein levels in MDA-MB-231 cancer cells. Moreover, compound 15 exerted cell cycle arrest at both the G0-G1 and G2-M phases. The in vivo efficacy of compound 15 as an antitumor agent was further investigated in female mice bearing Solid Ehrlich Carcinoma. Notably, administration of compound 15 resulted in a marked decrease in both tumor weight and volume, accompanied by improvements in biochemical, hematological, histological, and immunohistochemical parameters that verified the repression of both angiogenesis and inflammation as additional Anticancer mechanisms. Moreover, the binding interactions of compounds 15 and 17 within the binding sites of all three target receptors (EGFR, FGFR3, and VEGF) were clearly illustrated using molecular docking.

Copper-Vit B3 MOF preparation, characterization and catalytic evaluation in a one-pot synthesis of benzoxanthenones with docking validation as anti H. pylori.

Copper-Vit B3 MOF was successfully prepared by efficient and eco hydrothermal method. The prepared MOF was characterized as a tetragonal crystal copper-MOF nanoparticles by FTIR, SEM, TEM, EDX and XRD. The prepared nanoparticles were used as an effective, inexpensive and low-toxic catalyst in the one-pot synthesis of some new benzoxanthenone derivatives. As example 4-(9,9-dimethyl-11-oxo-8,10,11,12-tetrahydro-9H-benzo[a]xanthen-12-yl)phenyl benzoate (4h) was synthesized in high yield 92%. The MOF catalyst's role is activating the nucleophilic attack by increasing the carbonyl polarization, and this generally improves the reaction time, which ranges between 20-60 minutes and products' yields ranging between 80-92%. Prepared compounds (4a-4j) undergo molecular docking scanning as Helicobacter pylori type II dehydroquinase inhibitors, and the data obtained showed that there are three promises of the prepared compounds 4d, 4e, 4h and 4j compared with amoxicillin.

Tailoring neo/adjuvant systemic therapy in breast cancer: "The advent of a personalized approach"-The Breast-Gynecological and Immuno-Oncology International Cancer Conference (BGICC) consensus and recommendations.

BACKGROUND: The management of early breast cancer (BC) has witnessed an uprise in the use of neoadjuvant therapy and a remarkable reshaping of the systemic therapy postneoadjuvant treatment in the last few years, with the evolution of many controversial clinical situations that require consensus. METHODS: During the 14th Breast-Gynecological and Immuno-Oncology International Cancer Conference held in Egypt in 2022, a panel of 44 BC experts from 13 countries voted on statements concerning debatable challenges in the neo/adjuvant treatment setting. The recommendations were subsequently updated based on the most recent data emerging. A modified Delphi approach was used to develop this consensus. A consensus was achieved when ≥75% of voters selected an answer. RESULTS AND CONCLUSIONS: The consensus recommendations addressed different escalation and de-escalation strategies in the setting of neoadjuvant therapy for early BC. The recommendations recapitulate the available clinical evidence and expert opinion to individualize patient management and optimize therapy outcomes. Consensus was reached in 63% of the statements (52/83), and the rationale behind each statement was clarified.

Facile synthesis of silver doped manganese oxide nanocomposite with superior photocatalytic and antimicrobial activity under visible spectrum.

Water pollution and antimicrobial resistance (AMR) have become two global threats; 80% of diseases and 50% of child deaths are due to poor water quality. In this study, hydrothermal processing was employed to manufacture manganese oxide nanorods. Silver dopant was deposited on the surface of manganese oxide. XRD diffractogram confirmed the facile synthesis of Ag/Mn2O3 nanocomposite. XPS survey analysis demonstrated silver content of 9.43 atom %. Photocatalytic measurements demonstrated the outstanding efficiency of the Ag-Mn2O3 compared to virgin oxide particles under visible radiation. Degradation efficiencies Mn2O3 and Ag/Mn2O3 on methyl orange (MO) dye was found to be 53% and 85% under visible spectrum. Silver dopant was found to decrease the binding energy of valence electrons; this action could support electron-hole pair generation under visible spectrum and could promote catalytic performance. Ag/Mn2O3 NPs demonstrated most effective performance (95% removal efficiency) at pH 3; this could be ascribed to the electrostatic attraction between positively charged catalyst and the negatively charged MO. Ag/Mn2O3 demonstrated enhanced antibacterial activity against Gram-positive Staphylococcus aureus (S. aureus) (19 mm ZOI), and Gram-negative Escherichia coli (E. coli) (22 mm ZOI) respectively; the developed nanocomposite demonstrated advanced anti-film activity with inhibition percentage of 95.5% against E. coli followed by 89.5% against S. aureus.

A hybrid model for the detection of retinal disorders using artificial intelligence techniques.

The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularization, diabetic macular edema, drusen, and normal cases. This study proposed a new framework that combines machine learning and deep learning-based techniques. The utilized classifiers were support vector machine (SVM), K-nearest neighbor (K-NN), decision tree (DT), and ensemble model (EM). A feature extractor, the InceptionV3 convolutional neural network, was also employed. The performance of the models was evaluated against nine criteria using a dataset of 18000 OCT images. For the SVM, K-NN, DT, and EM classifiers, the analysis exhibited state-of-the-art performance, with classification accuracies of 99.43%, 99.54%, 97.98%, and 99.31%, respectively. A promising methodology has been introduced for the automatic identification and classification of retinal disorders, leading to reduced human error and saved time.

Experimental investigation of multi-step airfoils in low Reynolds numbers applications.

This study provides a detailed analysis of the aerodynamic performance of various airfoil configurations, focusing on lift coefficient, stall characteristics, and maximum lift-to-drag ratio. The investigation includes the NACA23012C profile and configurations with different step geometries, ranging from one-step to five-step designs. Experimental measurements were conducted using a well-equipped aerodynamic laboratory, Institute of Aviation Engineering and Technology (IAET), Giza, Egypt. The lab features a wind tunnel, propeller test rig, and data acquisition system. The experiments were conducted meticulously to ensure accuracy and reproducibility, with a standardized method employed for uncertainty analysis. The results reveal distinct aerodynamic behaviors among the different configurations, highlighting the significant impact of design variations on aerodynamic performance. Notably, the three-step configuration consistently exhibited high performance, with a competitive or superior lift coefficient across a range of Reynolds numbers, showing an improvement of up to 35.1 %. Similarly, the four-step configuration demonstrated substantial increases in lift-to-drag ratios, reaching up to 53.2 %, while the five-step configuration exhibited varying trends with a minimum drag coefficient. The study also investigated stall characteristics and sensitivity to Reynolds numbers, revealing the complex trade-offs inherent in airfoil design. The findings provide valuable insights into optimizing airfoil performance under different operational conditions. Additionally, the adoption of two and three stepped airfoils resulted in significant reductions in blade material and associated costs for turbine blades.

Engineering of the Central Core on DBD-Based Materials with Improved Power-Conversion Efficiency by Using the DFT Approach.

Developing proficient organic solar cells with improved optoelectronic properties is still a matter of concern. In the current study, with an aspiration to boost the optoelectronic properties and proficiency of organic solar cells, seven new small-molecule acceptors (Db1-Db7) are presented by altering the central core of the reference molecule (DBD-4F). The optoelectronic aspects of DBD-4F and Db1-Db7 molecules were explored using the density functional theory (DFT) approach, and solvent-state calculations were assessed utilizing TD-SCF simulations. It was noted that improvement in photovoltaic features was achieved by designing these molecules. The results revealed a bathochromic shift in absorption maxima (λmax) of designed molecules reaching up to 776 nm compared to 736 nm of DBD-4F. Similarly, a narrow band gap, low excitation energy, and reduced binding energy were also observed in newly developed molecules in comparison with the pre-existing DBD-4F molecule. Performance improvement can be indicated by the high light-harvesting efficiency (LHE) of designed molecules (ranging from 0.9992 to 0.9996 eV) compared to the reference having a 0.9991 eV LHE. Db4 and Db5 exhibited surprisingly improved open-circuit voltage (V OC) values up to 1.64 and 1.67 eV and a fill factor of 0.9198 and 0.9210, respectively. Consequently, these newly designed molecules can be considered in the future for practical use in manufacturing OSCs with improved optoelectronic and photovoltaic attributes.

Acute Appendicitis Incidence, Diagnostic Markers, and Sequelae; Dallah Hospital-Based Study in Riyadh, Saudi Arabia.

Background: Acute appendicitis is currently considered one of the most common acute surgical diseases of the abdomen and requires emergency surgery. It is also one of the most common abdominal emergencies in both developed and developing countries. The current study is aimed at assessing the specificity and sensitivity of Ultrasound and Computed Tomography in the diagnosis of appendicitis as well as the prevalence of its complications. The association of appendicitis with several laboratory findings will also be evaluated. Methodology: A retrospective study was conducted at Dallah-Namar Hospital, Riyadh City, Saudi Arabia. Results: 720 patients were differentially diagnosed with appendicitis in the study area. Of these, 618 patients had US abdomen/pelvis, with 15 (2.4%) showing positive findings. Amongst the 203 patients noted to have undergone abdominal CT,8 (4.0%) was found to have positive findings. Conclusion: The sensitivity of the US was determined to be relatively low. Also, serum creatinine was found to be elevated among all patients diagnosed with appendicitis. Further research with a larger sample size is needed to be conducted to further support the current findings.

Comparison of Coronary Artery Calcium and Quantitative Coronary Plaque in Predicting Obstructive Coronary Artery Disease: Subgroup Analysis of the CLARIFY Study.

Background: Agatston coronary artery calcium (CAC) score is a strong predictor of mortality. However, the relationship between CAC and quantitative calcified plaque volume (CPV), which is measured on coronary computed tomography angiography (CCTA), is not well understood. Furthermore, there is limited evidence evaluating the difference between CAC versus CPV and CAC versus total plaque volume (TPV) in predicting obstructive coronary artery disease (CAD). Methods: This study included 147 subjects from the CLARIFY registry, a multicentered study of patients undergoing assessment using CCTA and CAC score as part of acute and stable chest pain evaluation. Automated software service (Cleerly.Inc, Denver, CO, USA) was used to evaluate the degree of vessel stenosis and plaque quantification on CCTA. CAC was measured using the standard Agatston method. Spearman correlation and receiver operating characteristic curve analysis was performed to evaluate the diagnostic ability of CAC, CPV and TPV in detecting obstructive CAD. Results: Results demonstrated a very strong positive correlation between CAC and CPV (r=0.76, p=0.0001) and strong correlation between CAC and TPV (r=0.72, p<0.001) at per-patient level analysis. At per-patient level analysis, the sensitivity of CAC (68%) is lower than CPV (77%) in predicting >50% stenosis, but negative predictive value is comparable. However, the sensitivity of TPV is higher compared with CAC in predicting >50% stenosis, and the negative predictive value of TPV is also higher. Conclusion: CPV and TPV are more sensitive in predicting the severity of obstructive CAD compared with the CAC score. However, the negative predictive value of CAC is comparable to CPV, but is lower than TPV. This study elucidates the relationship between CAC and quantitative plaque types, and especially emphasizes the differences between CAC and CPV which are two distinct plaque measurement techniques that are utilized in predicting obstructive CAD.

The pharmacists' interventions after a Drug and Therapeutics Committee (DTC) establishment during the COVID-19 pandemic.

Introduction: Healthcare systems in developing countries faced significant challenges during COVID-19, grappling with limited resources and staffing shortages. Assessment of the impact of pharmaceutical care expertise, particularly in critical care units during the pandemics, in developing countries remains poorly explored. The principal aim of our study was to assess the impact of the Drug and Therapeutics Committee (DTC), comprising clinical pharmacists, on the incidence, types, and severity of medication errors and associated costs in using COVID-19 medications, especially antibiotics. Methods: An interventional pre-post study was carried out at a public isolation hospital in Egypt over 6 months. Results: Out of 499 medication orders, 238 (47.7%) had medication errors, averaging 2.38 errors per patient. The most frequent were prescribing errors (44.9%), specifically incorrect drug choice (57.9%), excessive dosage (29.9%), treatment duplication (4.5%), inadequate dosage (4.5%), and overlooked indications (3.6%). Linezolid and Remdesivir were the most common medications associated with prescribing errors. Pharmacists intervened 315 times, primarily discontinuing medications, reducing doses, introducing new medications, and increasing doses. These actions led to statistically significant cost reductions (p < 0.05) and better clinical outcomes; improved oxygen saturation, decreased fever, stabilised respiratory rates, and normalised white blood cell counts. So, clinical pharmacist interventions made a notable clinical and economic difference (66.34% reduction of the expenses) in antibiotics usage specifically and other medications used in COVID-19 management during the pandemic. Conclusion: Crucially, educational initiatives targeting clinical pharmacists can foster judicious prescribing habits.

Effectiveness of buccal administration of dexmedetomidine and ketamine combination in paediatric dental sedation: A randomized controlled clinical trial.

BACKGROUND: Pain and anxiety can be considerable obstacles while treating paediatric dental patients. Moderate sedation is needed to treat uncooperative patients. AIM: This study aimed to compare the effectiveness of buccal administration of dexmedetomidine-ketamine combination versus dexmedetomidine. DESIGN: Fifty-six uncooperative children were randomly assigned into two groups: Group I received buccal dexmedetomidine (2 µg/kg) and ketamine (2 mg/kg) (DEX-KET), whereas Group II received buccal dexmedetomidine (4 µg/kg) (DEX). The effects of drugs were evaluated based on changes in vital signs, onset and duration of sedation, sedation level, analgesia, ease of treatment and procedural adverse effects. RESULTS: There were no significant differences in vital signs or sedation onset between the two groups. DEX-KET group showed shorter recovery time than DEX group (p < .0001). There were no statistically significant differences between both groups regarding sedation level at optimum sedation and during operative procedure (p = .064, p = .069 respectively). The ease of treatment was significantly better in DEX-KET group than in DEX group (p = .048). Procedural side effects and analgesic effects of the sedative drugs were comparable between both groups. CONCLUSION: The combination of dexmedetomidine and ketamine delivered buccally provided a better method of delivering care to uncooperative children with more rapid recovery than dexmedetomidine.