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Peg-shaped lateral incisors are the most prevalent tooth size discrepancy, which can have a number of functional and aesthetic implications in affected people. This case report presents a conservative treatment approach to treat bilateral peg laterals and restore aesthetic harmony. A 21-year-old male patient complained about the shape and unaesthetic appearance of his two front teeth which negatively impacted his smile. The patient presented with bilateral peg laterals in the maxillary arch, and he had a stable occlusion with normal overjet and overlap and good periodontal health. Digital smile design (DSD) analysis revealed a discrepancy in crown width between Teeth #13 and #23 and gingival height discrepancy between Teeth #11 and #21, and #12 and #22. Accordingly, it was planned to perform a crown lengthening procedure to overcome the gingival height discrepancy of Teeth #12 and #21, place a full-contour resin composite restoration on Teeth #12 and # 22 and increase the mesiodistal width of Tooth #13. The patient underwent home teeth whitening for 2 weeks, followed by a 1-week observation period to ensure colour stability of the tooth. Laser gingivectomy was performed to correct the gingival height discrepancy, and incremental resin composite was used to restore the peg-shaped laterals. The restoration was contoured, finished and polished to obtain a smooth and glossy finish. The aesthetic treatment achieved excellent results, and the patient was pleased and excited with his new smile.

Restoration of structurally compromised teeth often requires cusp coverage, yet the influence of preparation design and material type on performance remains unclear. This study evaluated the effect of cusp coverage design and hybrid resin–ceramic material on the marginal adaptation and fracture resistance of partial coverage restorations in mandibular molars. Eighty extracted teeth were prepared for indirect restorations and allocated to four groups (n = 20) according to design, either functional cusp coverage (FC) or complete cusp coverage (CC) and material, either GC Cerasmart (CS) or VITA Enamic (EN). Restorations were bonded with dual-cure resin cement, thermocycled, and subjected to cyclic loading. Fracture load, marginal adaptation, and failure mode were evaluated (α = 0.05). CC-CS and CC-EN exhibited significantly higher fracture loads than FC-CS and FC-EN (p < 0.001), while no difference was found between materials within each design. For marginal adaptation, CS showed significantly greater marginal gaps than EN in both designs (p < 0.001). CC designs demonstrated a higher proportion of repairable failures (Type I and II), whereas EN showed more catastrophic fractures. Within the limitations of this in vitro study, cusp coverage design significantly affected fracture resistance, while material type primarily influenced marginal adaptation. Both hybrid resin–ceramics provided acceptable mechanical performance for partial coverage restorations.

Messenger RNA (mRNA) vaccine development for preventive and therapeutic applications has evolved rapidly over the last decade. The mRVNA vaccine has proven therapeutic efficacy in various applications, including infectious disease, immunotherapy, genetic disorders, regenerative medicine, and cancer. Many mRNA vaccines have made it to clinical trials, and a couple have obtained FDA approval. This emerging therapeutic approach has several advantages over conventional methods: safety; efficacy; adaptability; bulk production; and cost-effectiveness. However, it is worth mentioning that the delivery to the target site and in vivo degradation and thermal stability are boundaries that can alter their efficacy and outcomes. In this review, we shed light on different types of mRNA vaccines, their mode of action, and the process to optimize their development and overcome their limitations. We also have explored various delivery systems focusing on the nanoparticle-mediated delivery of the mRNA vaccine. Generally, the delivery system plays a vital role in enhancing mRNA vaccine stability, biocompatibility, and homing to the desired cells and tissues. In addition to their function as a delivery vehicle, they serve as a compartment that shields and protects the mRNA molecules against physical, chemical, and biological activities that can alter their efficiency. Finally, we focused on the future considerations that should be attained for safer and more efficient mRNA application underlining the advantages and disadvantages of the current mRNA vaccines.

Background Medical students have higher risk of psychological disorders due to the relatively stressful environment. Educators are becoming increasingly aware of the impact of stresses on the students general well-being. The objective of the current study was to examine the prevalence of and risk factors for depressive and anxiety symptoms among first-year and fifth-year medical students. Additionally, we aimed to determine whether the COVID-19 pandemic has affected students’ mental well-being. Methods A cross-sectional study was performed at the College of Medicine at King Saud University between September 2020 and January 2021. The target population was first-year and fifth-year medical students. Depressive symptoms were screened using the 9-item Patient Health Questionnaire (PHQ-9), while anxiety symptoms were screened using the 7-item Generalized Anxiety Disorder assessment (GAD-7). Students were also directly asked about the effect of the COVID-19 pandemic on their mental well-being. Outcomes were compared between groups using the chi-squared test and Student’s t test. Multivariate logistic regression analysis was performed to identify factors associated with depressive and anxiety symptoms. Results A total of 182 medical students were included. Depressive symptoms (52.9% versus 35.8%, p  = 0.020) and anxiety symptoms (35.6% versus 26.3%, p  = 0.176) were higher in the first-year students than in the fifth-year students. Approximately 19.2% of the students were worried about acquiring COVID-19, 49.4% were worried about academic performance, and 30.8% were feeling sad, depressed or anxious during the COVID-19 pandemic. Independent risk factors for depressive symptoms included having concomitant anxiety, being worried about acquiring COVID-19, being worried about academic performance, and feeling sad, depressed or anxious. Independent risk factors for anxiety included having a lower grade point average and having concomitant depressive symptoms. Conclusion Medical students have an alarmingly high prevalence of depressive and anxiety symptoms, which might have been negatively impacted by the COVID-19 pandemic. There is a need for a special mental health program targeting new and current medical students.

Wound treatment is a significant health burden in any healthcare system, which requires proper management to minimize pain and prevent bacterial infections that can complicate the wound healing process. There is a need to develop innovative therapies to accelerate wound healing cost-effectively. Herein, two polymer-based nanofibrous systems were developed using poly-lactic-co-glycolic-acid (PLGA) and polyvinylpyrrolidone (PVP) loaded with a combination of an antibiotic (Fusidic acid, FA) and a local anesthetic (Lidocaine, LDC) via electrospinning technique for an expedited healing process by preventing bacterial infections while reducing the pain sensation. The fabricated nanofibers showed an excellent morphology with an average fiber diameter of 556 ± 71 nm and 291 ± 87 nm for the dual drug-loaded PLGA/PVP and PVP nanofibers, respectively. The encapsulation efficiency (EE%) and drug loading (DL) studies revealed that PLGA/PVP loaded with FA and LDC exhibited EE% of 92% and 75%, respectively, while the DL was measured at 40 ± 8 µg/mg for FA and 32 ± 7 µg/mg for LDC. Furthermore, both drugs were fully released from the nanofibers within 48 hours. In contrast, FA/LDC-loaded PVP nanofibers exhibited EE% of 100% for FA and 84% for LDC; DL was measured at 85 ± 3 µg/mg for FA and 70 ± 3 µg/mg for LDC, while both drugs were completely released within 24 hours. The in vitro cytotoxicity study demonstrated a safe concentration of FA and LDC at ≤ 125 μg/mL. The prepared nanofibers were tested in vivo in an -infected wound mice model to assess their efficacy, and the results showed that the FA/LDC-PVP had a faster wound closure and the lowest bacterial counts compared to other groups. These findings showed the potential application of the fabricated dual drug-loaded nanofibers as a wound-healing plaster against infected acute wounds.

The emergence of phytosome nanotechnology has a potential impact in the field of drug delivery and could revolutionize the current state of topical bioactive phytochemicals delivery. The main challenge facing the translation of the therapeutic activity of phytochemicals to a clinical setting is the extremely low absorption rate and poor penetration across biological barriers (i.e., the skin). Phytosomes as lipid-based nanocarriers play a crucial function in the enhancement of pharmacokinetic and pharmacodynamic properties of herbal-originated polyphenolic compounds, and make this nanotechnology a promising tool for the development of new topical formulations. The implementation of this nanosized delivery system could enhance the penetration of phytochemicals across biological barriers due to their unique physiochemical characteristics, improving their bioavailability. In this review, we provide an outlook on the current knowledge of the biological barriers of phytoconstituents topical applications. The great potential of the emerging nanotechnology in the delivery of bioactive phytochemicals is reviewed, with particular focus on phytosomes as an innovative lipid-based nanocarrier. Additionally, we compared phytosomes with liposomes as the gold standard of lipid-based nanocarriers for the topical delivery of phytochemicals. Finally, the advantages of phytosomes in topical applications are discussed.

The development of continuous pharmaceutical manufacturing is crucial and can be analyzed via advanced computational models. Machine learning is a strong computational paradigm that can be integrated into a continuous process to enhance the drugs’ solubility and efficacy. In this research, a simulation method for estimating pharmaceutical solubility was considered in green solvents to develop the idea of continuous pharmaceutical manufacturing. Artificial intelligence strategies were utilized to apply models for fitting several solubility datasets. Using machine learning techniques, the solubility of Clobetasol Propionate (CP) was modeled at temperature values between 308 K and 348 K, and pressures in the range of 12.2 MPa to 35.5 MPa. In this research, two models—a neural network-based model called MLP (Multilayer Perceptron) and a probabilistic model called GPR (Gaussian Process Regression)—along with an ensemble voting model based on these two, were considered for modeling. A GWO (Grey Wolf Optimization) method was also used to tune their hyperparameters. All three models have significant performances on estimation of CP solubility. But the voting model, which is a combination of the other two models, is better than the other two models in terms of accuracy. The ensemble voting model, integrating MLP and GPR with GWO optimization, offers superior accuracy for predicting CP solubility, advancing continuous pharmaceutical manufacturing.

Health care workers working in Covid-19 vacciantion centers due to their exponential demand experience burnout and stress. Burnout, a psychological syndrome is characterized by emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA). It can adversely affect professional and personal well being of an individual. Aim of this study was to check prevalence of burnout among health care workers, to identify personal and work-related factors, and to compare the risk factors associated with the different dimensions of burnout (EE, DP, and PA). This cross-sectional study was carried out among 180 employees of various COVID-19 vaccination centers. Three dimensions of burnout (EE, DP, and PA) were evaluated usinge Maslach Burnout Inventory (MBI), and association between burnout and other factors were assessed using logistic regression analysis with 95% confidence intervals (CI). Prevalence rate of burnout among health care workers was 73.3%. Emotional exhaustion being the highest dimension (38.4%) followed by Depersonalization (30.8%) and personal accomplishment (33.1%). Young employees (<30 years) had significantly higher prevalence of burnout compared to old employees (82.4% vs. 52.4%, p = 0.033). Additionally, employees working more than 8 hours/day (OR = 9.98, p = 0.032) and employess with less than 6 hours of sleep/night (OR = 0.39, p = 0.042) had more likely to experience burnout. There was an increase prevalence rate of burnout observedamong employees at COVID-19 vaccination centers. There was a significant association between personal and work-related factors such as age, working hours, and sleep patterns. Addressing these factors, particularly by promoting better work-life balance and mental health support, is essential to mitigate burnout and improve employee well-being.

An investigation of the structural, morphological, magnetic, and optical properties of Ni0.6Mg0.2Co0.2FeCrO4 spinel ferrites prepared by the sol–gel method at different annealing temperatures conducted. The grain size and the unit cells parameters of the synthesized samples exhibit an increasing trend as the annealing temperature increases. A low coercive field was obtained from the hysteresis loops, making Ni0.6Mg0.2Co0.2FeCrO4 ferrites suitable candidates for soft magnetic devices. The bands associated with the tetrahedral (A) and octahedral [B] sites shift toward higher wavenumbers as the annealing temperature increases. In addition, the optical band gap energy decreases with annealing temperature due to the increase in grain size. From the absorbance and the Tauc method, the samples present direct optical transitions. Moreover, the determined Urbach energies are significantly low and decrease with annealing temperature. This implies that the degree of disorder and defects in the prepared samples decreases by increasing the annealing temperature. A detailed study has also been conducted on the variations versus wavelength of penetration depth, refractive index, extinction coefficient, dielectric constants, conductivity, and loss factor. From the variations of these optical parameters, some interesting optoelectronic applications were deduced for the prepared samples.

Decoupled data and control planes in Software Defined Networks (SDN) allow them to handle an increasing number of threats by limiting harmful network links at the switching stage. As storage, high-end servers, and network devices, Network Function Virtualization (NFV) is designed to replace purpose-built network elements with VNFs (Virtualized Network Functions). A Software Defined Network Function Virtualization (SDNFV) network is designed in this paper to boost network performance. Stateful firewall services are deployed as VNFs in the SDN network in this article to offer security and boost network scalability. The SDN controller’s role is to develop a set of guidelines and rules to avoid hazardous network connectivity. Intruder assaults that employ numerous socket addresses cannot be adequately protected by these strategies. Machine learning algorithms are trained using traditional network threat intelligence data to identify potentially malicious linkages and probable attack targets. Based on conventional network data (DT), Bayesian Network (BayesNet), Naive-Bayes, C4.5, and Decision Table (DT) algorithms are used to predict the target host that will be attacked. The experimental results shows that the Bayesian Network algorithm achieved an average prediction accuracy of 92.87%, Native–Bayes Algorithm achieved an average prediction accuracy of 87.81%, C4.5 Algorithm achieved an average prediction accuracy of 84.92%, and the Decision Tree algorithm achieved an average prediction accuracy of 83.18%. There were 451 k login attempts from 178 different countries, with over 70 k source IP addresses and 40 k source port addresses recorded in a large dataset from nine honeypot servers.