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The current numerical study suggests a novel multilayer surface plasmon resonance (SPR) sensor structure for detecting dental diseases. The suggested sensor is sensitive to changes in the sensing medium (SM) of the refractive index (RI). Over the SF11 prism, the nano-layers of silver (Ag), Zinc oxide (ZnO), and antimonene have been taken for the suggested sensor. Performance parameters sensitivity, full width at half maximum (FWHM), detection accuracy (DA), and figure of merit (FoM) are measured. Maximum sensitivity of 105.72/deg/RIU is attained with the sensing medium’s refractive index (RI) (1.33–1.631). Moreover, we have analyzed the human teeth layer enamel, dentin, and cementum detection. The value of FWHM is calculated as 1.85 deg, 1.91 deg, 1.88 deg, 1.87 deg and 1.86 deg for 0 nm, 25 nm, 50 nm, 100 nm, and 200 nm, respectively, the concentration of human teeth layer. The popular transfer matrix method is utilized for reflectance calculation: the teeth’ enamel, dentin, and cementum layer. SDG 3 pertains to health, ensures everyone has access to healthy living, and promotes well-being by establishing national goals and plans to enhance public health. This is a result of the connections between each SDG. [ABSTRACT FROM AUTHOR]

Osteoporosis is a disease in which bone mass and structural strength decrease, leading to increased fragility and susceptibility to fractures in the face, neck, spine, wrist, etc. It's a disease that doesn't display any symptoms until a break occurs; in other words, it's a silent illness. Sometime it also utilised frequently in dentistry application such that to detect osteoporosis during the operation or implanting on maxilla. This body of work shows that, despite major breakthroughs in medicine, there remains a unique role for the development of novel tools for the diagnosis of osteoporosis. In this work, we present an osteoporosis detection system developed using image processing and support vector machine (SVM) techniques. Compared to prior studies in this area, the data collected by the technology established in this study—which includes 50 sample photographs of the tibia—is of high quality. The proposed method achieves an impressively high level of accuracy (83.6% with 50 samples) because to the inclusion of the histogram feature and the use of tissue properties during feature extraction. [ABSTRACT FROM AUTHOR]

The article "Diagnosing osteoporosis using deep neural network-assisted optical image processing method" published in Optical & Quantum Electronics has been retracted by the Publisher due to concerns about compromised peer-review process, inappropriate references, and being out of scope for the journal. The corresponding author, Mohammad Khursheed Alam, disagrees with the retraction. The Publisher, in consultation with the Editors-in-Chief, no longer has confidence in the results and conclusions of the article. [Extracted from the article]

Photodynamic therapy (PDT) has been suggested as an adjunctive therapeutic approach for peri-implantitis. This systematic review aimed to assess the clinical and radiographic outcomes of adjunctive PDT (aPDT) for the treatment of peri-implantitis among diabetics and cigarette smokers. Randomized controlled trials (RCTs), which assessed the clinical and radiographic outcomes of aPDT versus other intervention(s) and/or MD alone among diabetics and smokers with peri-implantitis, were considered eligible for the review. Meta-analysis was performed for calculating the standard mean difference (SMD) with a 95% confidence interval (CI). The methodological quality of the included studies was evaluated using the modified Jadad quality scale. The meta-analysis revealed no significant differences between the influence of aPDT and other intervention/MD alone on the peri-implant PI among diabetics at the final follow-up. However, statistically significant improvements in the peri-implant PD, BOP, and CBL were observed after the application of aPDT among diabetics. Similarly, no significant differences were found between the influence of aPDT and other interventions/MD alone on the peri-implant PD among smokers with peri-implant diseases at the final follow-up. However, statistically significant improvements in the peri-implant PI, BOP, and CBL were observed after the application of aPDT among smokers. Significant improvements in the peri-implant PD, BOP, and CBL among diabetics and the peri-implant PI, BOP, and CBL among smokers after the application of aPDT at the final follow-up. However, large-scale, well-designed, and long-term RCTs are recommended in this domain. [ABSTRACT FROM AUTHOR]

The work presents a surface plasmon resonance biosensor employing bismuth telluride (Bi2Te3) and graphene layer overlaid on the Ag metal layer-based biosensor to detect disease in the teeth. The Ag layer, Bi2Te3, and graphene are assumed to have thicknesses of 35 nm, 1 nm, and 0. 5 nm, respectively. Using single-layer Bi2Te3 and single-layer graphene, the highest sensitivity of the sensor for enamel, dentin, and cementum is 79.310 deg/RIU, 118.88 deg/RIU, and 169.87 deg/RIU obtained, respectively. The other performance parameters are full width at half maximum, detection accuracy, and quality factor obtained as 6.723 deg, 0.11 deg−1, and 18.74 RIU−1. Graphene increases the biocompatibility of the analyte with the sensing layer. Consideration has been given to the aqueous solution as a sensing medium. The proposed sensor has great potential in the medical and chemical fields. [ABSTRACT FROM AUTHOR]