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Influence of different finishing and polishing protocols of composite CAD CAM blocks on surface roughness and biological response of gingival mesenchymal stem cells
No full textThe surface quality of composite CAD/CAM restorations is vital in aesthetics, longevity, and the biological response of
surrounding gingival tissues. Yet, little is known about how different finishing and polishing techniques influence cellular
behavior at the tissue interface. This study aimed to evaluate how various finishing and polishing systems affect the surface
roughness of composite CAD/CAM blocks, and how these differences influence the attachment, viability, and inflammatory
response of gingival mesenchymal stem cells (GMSCs). Seventy-seven composite CAD/CAM specimens were prepared and
subjected to one-step, two-step, and multi-step finishing/polishing protocols, with or without polishing paste. Surface rough-
ness was measured using a digital profilometer. GMSCs were isolated from healthy donors, characterized, and cultured on the
composite surfaces. Cell viability was assessed by MTT assay, adhesion was evaluated using scanning electron microscopy
(SEM), and inflammation-related gene expression (IL-1β and TGF-β) was analyzed via q-PCR. Polished surfaces significantly
reduced roughness and improved biological outcomes. Two-step finishing and polishing with paste resulted in the smooth-
est surfaces. GMSCs showed greater attachment and viability on polished composites, particularly in the two-step group.
Inflammatory gene expression was lowest in polished groups, with IL-1β expression highest in unpolished specimens and
TGF-β expression highest in the one-step groups. Finishing and polishing protocols directly impact the surface roughness
as well as the biocompatibility of CAD/CAM composite surfaces. Smoother surfaces achieved through proper finishing and
polishing enhance cell attachment and viability, and reduce inflammatory responses, highlighting the critical role of finishing
in restorative success beyond aesthetics
Low dose cone beam computed tomography versus high dose cone beam computed tomography in measuring furcation involvements: (diagnostic accuracy study)
No full textAccurate diagnosis of furcation defect is essential in periodontal therapy planning. Cone beam computed tomography (CBCT) provides three-dimensional visualization, but higher radiation doses remain a concern. This study aims to assess and compare the diagnostic accuracy of low-dose CBCT (LD-CBCT) and high-dose CBCT (HD-CBCT) in detecting and measuring furcation defect using a pig mandible. Detection and accurate assessment of periodontal disease is important to determine the tooth prognosis and treatment. Radiographic assessment provides information about the pattern and extent of the furcation defect. CBCT provides unique 3D images used for diagnosis and treatment plans, but its use in periodontology not well-reviewed as there is few numbers of studies searched about the role of CBCT in periodontology. Fifteen molars from nine pig mandibles with naturally occurring and simulated furcation involvements were scanned using both LD-CBCT and HD-CBCT protocols. Real measurements obtained with periodontal probes and digital calipers served as the gold standard. Furcation defect were recorded and compared across the both doses (LD-CBCT & HD- CBCT). Inter- and intra-observer reliability were assessed. The results indicated that the mean furcation measurements were highest in the gold standard group (8.61 ± 1.90 mm), followed by HD-CBCT (7.22 ± 2.27 mm) and LD-CBCT (6.99 ± 2.15 mm). Differences between HD-CBCT and gold standard were not statistically significant (p = 0.062), whereas LD-CBCT showed a significant difference from the gold standard (p = 0.008). However, diagnostic agreement between HD and LD protocols was high, with acceptable variability. In conclusion it was found that LD-CBCT demonstrates acceptable diagnostic accuracy for measuring furcation defect, suggesting that reduced-dose protocols may be viable in clinical settings to limit radiation exposure without compromising diagnostic outcomes
Coumarin/nitrogen-bearing heterocyclic hybridloaded electrospun PMMA/PVP nanofibrous scaffolds for accelerating topical wound healing rates: synthesis and in vitro bio-evaluation
No full textCoumarin-nitrogen heterocyclic compounds (e.g. quinoline, acridine, and phthalazine) were synthesized by facile reactions and elucidated by FTIR, 1H, and 13C-NMR analyses, which showed consistency with the expected structures. Coumarin-quinoline (drug A)- and coumarin-acridine (drug B)-loaded electrospun PMMA/PVP nanofibrous scaffolds were fabricated using electrospinning techniques. Results showed a successful PMMA/PVP blend, which formed the matrix that was used as the main scaffold for drug loading/release. The drugs (A and B) were encapsulated within the matrix as verified by IR and SEM results. Bio-evaluation through cytotoxicity and anticancer screening was conducted using the MTT assay against lung fibroblast (Wi-38), colon carcinoma (Caco-2), lung carcinoma (A549) and breast carcinoma (MDA) cell lines. Notably, the IC50 values of the synthesized derivatives against Wi-38 cells were found in the range of 126.3–195.0 mg mL−1, indicating a high level of safety for the synthesized compounds toward the treated human normal (Wi-38) cell line. The IC50 values of these potent derivatives against Caco-2 cells were estimated in the range of 4.87–38.23 mg mL−1, with SI values ranging from 4.59 to 25.93. Their IC50 values against A549 cells were estimated to be in the range of 5.74–32.05 mg mL−1, with SI values ranging from 5.47 to 18.09. However, their IC50 values against MDA cells were estimated to be in the range of 4.27–14.91 mg mL−1, with SI values ranging from 11.76 to 29.58 mg mL−1. The antimicrobial activities of the two synthesized compounds toward Gram-positive compared to Gram-negative bacteria were estimated; the highest antimicrobial activity was achieved at inhibition zones of ∼19.5 ± 2.3 and 17.2 ± 1.3 mm toward S. aureus and S. mutans, respectively, followed by S. typhimurium (∼15.5 ± 1.1 mm). According to the obtained findings, coumarin-nitrogen heterocyclic compounds (quinoline, acridine)-loaded PMMA/PVP electrospun NFs can be regarded as good antimicrobial biomaterials for different biomedical applications, particularly for wound dressings
Emotional intelligence: the key to managing cognitive overload and enhancing quality of life
No full textPurpose
This study investigates the mediating role of Emotional Intelligence in the relationship between Quality of Life and Cognitive Overload.
Design/methodology/approach
This quantitative deductive study analysed 500 questionnaires through convenience sampling. The data collection provides a snapshot of Egyptian private universities’ academic staff members through a cross-sectional time horizon. After collecting the necessary data, statistical analyses were conducted through SPSS and AMOS.
Findings
Findings indicate that cognitive overload is directly related to mental noise because individuals cannot focus on several dimensions of life, job, and family. Academic staff members need to eliminate possible intrinsic, extraneous, and germane cognitive overload to enhance their working memory and amplify their performance at work. Findings also show that emotional intelligence can mediate such relationships by managing cognitive overload and enhancing quality of life.
Practical implications
Universities’ management and academic staff may use this study to understand how emotional intelligence can help balance quality of life aspects and eliminate cognitive overload by controlling attention, monitoring mental, physical, and psychological health, creating a relaxing atmosphere for work, and enhancing teaching and learning.
Originality/value
This study provides a comprehensive understanding of the three different types of cognitive overload and how to manage each type in the workplace. It addressed the literature gap by developing measurements for quality of life and cognitive overload, contributing to the conceptual clarity of the constructs and their measurements. It also reflects on how emotional intelligence could solve the mental burden faced at the workplace while enhancing satisfaction
Accelerating Deep Learning-Based Morphological Biometric Recognition with Field-Programmable Gate Arrays
No full textConvolutional neural networks (CNNs) are increasingly recognized as an important and potent artificial intelligence approach, widely employed in many computer vision applications, such as facial recognition. Their importance resides in their capacity to acquire hierarchical features, which is essential for recognizing complex patterns. Nevertheless, the intricate architectural design of CNNs leads to significant computing requirements. To tackle these issues, it is essential to construct a system based on field-programmable gate arrays (FPGAs) to speed up CNNs. FPGAs provide fast development capabilities, energy efficiency, decreased latency, and advanced reconfigurability. A facial recognition solution by leveraging deep learning and subsequently deploying it on an FPGA platform is suggested. The system detects whether a person has the necessary authorization to enter/access a place. The FPGA is responsible for processing this system with utmost security and without any internet connectivity. Various facial recognition networks are accomplished, including AlexNet, ResNet, and VGG-16 networks. The findings of the proposed method prove that the GoogLeNet network is the best fit due to its lower computational resource requirements, speed, and accuracy. The system was deployed on three hardware kits to appraise the performance of different programming approaches in terms of accuracy, latency, cost, and power consumption. The software programming on the Raspberry Pi-3B kit had a recognition accuracy of around 70–75% and relied on a stable internet connection for processing. This dependency on internet connectivity increases bandwidth consumption and fails to meet the required security criteria, contrary to ZYBO-Z7 board hardware programming. Nevertheless, the hardware/software co-design on the PYNQ-Z2 board achieved an accuracy rate of 85% to 87%. It operates independently of an internet connection, making it a standalone system and saving costs
Cuproptosis Regulation by Long Noncoding RNAs: Mechanistic Insights and Clinical Implications in Cancer
No full textAlthough survival rates have been improved in recent years, the prognosis of many cancer types remains inadequate, mostly owing to treatment resistance. Moreover, there is a continued need for exploring novel and reliable tumor markers to achieve accurate diagnosis. Understanding the molecular complexity of cancer allows for the development of more effective and personalized treatments and facilitates the discovery of biomarkers that surpass traditional ones and assist in cancer diagnosis and monitoring disease progression and response to treatment. Recent studies exploring the complexity of cancer biology have identified a new form of cell death, known as cuproptosis, which is driven by the accumulation of copper and subsequent stress induced by dysregulation of copper homeostasis. Increased copper level enables cancer cells to maintain their accelerated growth rates and metastatic potential, yet these cells can evade cuproptosis. Long noncoding RNAs (lncRNAs) have been recognized for their pivotal role in different hallmarks of cancer, including resistance to cell death. They have been found to be implicated in controlling copper balance and cuproptosis. Besides, lncRNAs associated with cuproptosis pathway have demonstrated their potential as diagnostic and prognostic cancer biomarkers as well as indicators of treatment response. Our review aims to summarize recent studies focusing on the intricate relationship between lncRNAs and cuproptosis and explore the mechanisms by which lncRNAs can modulate copper homeostasis and regulate cuproptosis pathway. We also highlight recent discoveries concerning the role of cuproptosis-related lncRNAs in diagnosis, prognosis, and therapy of different types of cancer. By elucidating the significance of cuproptosis-related lncRNAs, this review provides insights into how these lncRNAs can be used to develop new therapeutic strategies to improve treatment outcomes
Assessment of constructed wetland projects as a multifunction landscape: a case study in Egypt
No full textThis research aims to develop a conceptual framework and assessment tool to assess sustainability of Multifunction Constructed Wetlands Projects (MCWP). First, by literature review to analyze the main points and identify the gaps in existing research to what concerns viewing constructed wetlands as multifunction sustainable landscape projects. To assess the performance of MCWP, urban sustainability indicators are proposed examining interconnections between environmental, economic and social aspects and their effects on each other. 12 environmental, 9 socio-cultural and 7 economic indicators are selected according to their relevance to the United Nations and National Sustainable Development Goals, the impacts of their weights according to a distributed questionnaire showed these percentages: environmental aspects 42%, Socio-cultural aspects 29% and the economic aspects 28%. Also, performance-oriented assessment tools for MCWPs were designed for wastewater treatment. The impacts of proposed indicators are then assessed using the adapted Leopold Matrix method. Hence, this study aims to establish an assessment model to evaluate the sustainability features of MCWPs, by proposing sustainability indicators to be assessed by measurement metrics and respective weights for indicators and sub-indicators
Carboxymethyl cellulose assisted reforming of poly acrylic acid co methyl methacrylate composite for wastewater treatment and effective hosting of antimicrobial silver
No full textHerein, novel polymer composite is fabricated by hybridizing poly (acrylic acid-co-methyl methacrylate) filaments with carboxymethyl cellulose, which efficiently reorients and strictly ties the fibrous chains to form polymeric units of plate-like morphology. This innovative hybrid polymer composite is analyzed using XRD, FT-IR, swelling and contact angle studies, DLS, AFM, and SEM. Removal efficiency of such polymer composite is scrutinized in colored wastewater treatment. Langmuir and pseudo-first-order kinetic models best describe safranine dye removal from wastewater, adopting exothermic adsorption progression with elevated capacity (~ 59.47 mg/g) and accelerated rate (~ 1.06 h− 1). Such polymer composite exhibits persistent removal efficiency of ~ 90% within 10 min for five consecutive cycles. Hybrid polymer composite is good candidate platform for hosting Ag particles to heighten their antimicrobial activity against Escherichia coli and Staphylococcus aureus, far exceeding 75% reduction. Future studies on applicability of oxygen-rich polymer composites in wastewater treatment and disinfection are optimistic and extremely competent
An integrated framework for third party logistic evaluation by using fuzzy analytical hierarchy process and technique for order preference by similarity to ideal solution
No full textThis paper provides an integrated approach for evaluating and selecting third party logistics (3PLs) service providers. It contains two phases: the first phase employs a fuzzy analytical hierarchy process to specify the weights of the evaluation criteria, while the second phase uses the technique for order preference by similarity to ideal solution to evaluate the alternatives, sequence them, and select the best option. Finally, the proposed approach was implemented for a case study with four criteria and three alternatives. After that, sensitivity analysis was developed to get deeper insights. The results manifest the impact of using different methods to find the fuzzy sets on the value of criteria. The most important factors in 3PL selection were found to be compatibility (47.17%), financial performance (25.49%), reputation (16.52%) and long-term relationship (10.82%). The paper compares between using the extent analysis method and the geometric mean technique to find the fuzzy numbers
Leveraging Bayesian and Classical Techniques for Survival Analysis Using the Weibull-Rayleigh Distribution
No full textThis paper contributes to an extensive analysis of the Weibull-Rayleigh distribution (WRD), including Bayesian inference for randomly censored data. The WRD is a versatile model that fits various types of survival data, especially in situations including censoring, commonly found in biostatistics and engineering reliability research. The research investigates the derivation of the WRD’s probability density and cumulative distribution functions, employing maximum likelihood estimation (MLE) and Bayesian estimating techniques to accurately infer parameters. Gamma priors are utilized in Bayesian analysis, and approximate Bayesian estimates are derived by Gibbs sampling and Lindley’s approximation methods. An actual dataset that represents leukemia-free survival times for patients undergoing allogeneic bone marrow transplants is used to demonstrate the practical application of the WRD and to validate the proposed methods. The Kolmogorov-Smirnov test confirms the WRD’s superior fit compared to alternative models. This paper provides a robust framework for applying the WRD in survival analysis and highlights the efficacy of Bayesian inference in handling complex censored data structures