The current laboratory study is evaluating the effect of hydrofluoric acid etching duration on the surface characteristics of five silica-based glass ceramics. Changes in the pore pattern, crystal structure, roughness, and wettability were compared and evaluated. Seventy-five rectangularly shaped specimens were cut from each material (IPS e-max™, Dentsply Celtra™, Vita Suprinity™, Vita mark II™, and Vita Suprinity FC™); the sectioned samples were finished, polished, and ultrasonically cleaned. Specimens were randomly assigned into study groups: control (no etching) and four experimental groups (20, 40, 80 and 160 s of etching). The etched surfaces’ microstructure including crystal structure, pore pattern, pore depth, and pore width was studied under a scanning electron microscope, and the surface roughness and wettability were analyzed using a non-contact surface profilometer and a contact angle measuring device, respectively. The results were statistically analyzed using one-way analysis of variance (ANOVA) and the post hoc Tukey’s test. The results showed a significant change in the pore number, pore pattern, crystal structure, surface roughness, and wettability with increased etching duration. Etching for a short time resulted in small pores, and etching for longer times resulted in wider, irregular grooves. A significant increase in the surface roughness and wettability was observed with an increase in the etching duration. The findings also suggested a strong association between the surface roughness and wettability.

Oral cancer (OC) is a deadly disease with a high mortality and complex etiology. Artificial intelligence (AI) is one of the outstanding innovations in technology used in dental science. This paper intends to report on the application and performance of AI in diagnosis and predicting the occurrence of OC. In this study, we carried out data search through an electronic search in several renowned databases, which mainly included PubMed, Google Scholar, Scopus, Embase, Cochrane, Web of Science, and the Saudi Digital Library for articles that were published between January 2000 to March 2021. We included 16 articles that met the eligibility criteria and were critically analyzed using QUADAS-2. AI can precisely analyze an enormous dataset of images (fluorescent, hyperspectral, cytology, CT images, etc.) to diagnose OC. AI can accurately predict the occurrence of OC, as compared to conventional methods, by analyzing predisposing factors like age, gender, tobacco habits, and bio-markers. The precision and accuracy of AI in diagnosis as well as predicting the occurrence are higher than the current, existing clinical strategies, as well as conventional statistics like cox regression analysis and logistic regression.

Cadmium (Cd) stress is increasing at a high pace and is polluting the agricultural land. As a result, it affects animals and the human population via entering into the food chain. The aim of this work is to evaluate the possibility of amelioration of Cd stress through chitosan nanoparticles (CTS-NPs). After 15 days of sowing (DAS), Solanum lycopersicum seedlings were transplanted into maintained pots (20 in number). Cadmium (0.8 mM) was providing in the soil as CdCl₂·2.5H₂O at the time of transplanting; however, CTS-NPs (100 µg/mL) were given through foliar spray at 25 DAS. Data procured from the present experiment suggests that Cd toxicity considerably reduces the plant morphology, chlorophyll fluorescence, in addition to photosynthetic efficiency, antioxidant enzyme activity and protein content. However, foliar application of CTS-NPs was effective in increasing the shoot dry weight (38%), net photosynthetic rate (45%) and SPAD index (40%), while a decrease in malondialdehyde (24%) and hydrogen peroxide (20%) was observed at the 30 DAS stage as compared to control plants. On behalf of the current results, it is demonstrated that foliar treatment of CTS-NPs might be an efficient approach to ameliorate the toxic effects of Cd.

Nanoworld is an attractive sphere with the potential to explore novel nanomaterials with valuable applications in medicinal science. Herein, we report an efficient and ecofriendly approach for the synthesis of Nickel oxide nanoparticles (NiO NPs) via a solution combustion method using Areca catechu leaf extract. As-prepared NiO NPs were characterized using various analytical tools such as powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and UV-Visible spectroscopy (UV-Vis). XRD analysis illustrates that synthesized NiO NPs are hexagonal structured crystallites with an average size of 5.46 nm and a hexagonal-shaped morphology with slight agglomeration. The morphology, size, and shape of the obtained material was further confirmed using SEM and TEM analysis. In addition, as-prepared NiO NPs have shown potential antidiabetic and anticancer properties. Our results suggest that the inhibition of α-amylase enzyme with IC 50 value 268.13 µg/mL may be one of the feasible ways through which the NiO NPs exert their hypoglycemic effect. Furthermore, cytotoxic activity performed using NiO NPs exhibited against human lung cancer cell line (A549) proved that the prepared NiO NPs have significant anticancer activity with 93.349 μg/mL at 50% inhibition concentration. The biological assay results revealed that NiO NPs exhibited significant cytotoxicity against human lung cancer cell line (A549) in a dose-dependent manner from 0–100 μg/mL, showing considerable cell viability. Further, the systematic approach deliberates the NiO NPs as a function of phenolic extracts of A. catechu with vast potential for many biological and biomedical applications.

Controllable 2D luminescence tuning and single-phase white emission were realized in Eu²⁺,Mn²⁺-doped (Ca,Sr)₉Sc(PO₄)₇ by a method combining crystal field regulation and energy transfer.