A comparative evaluation of frictional resistance and surface roughness of silver coated and uncoated stainless-steel bracket wire assembly- An in-vitro study

Silver ions act as potent antimicrobial agents. Silver coating of brackets and the archwires can help reduce the formation of white spot lesions and caries which is commonly seen with fixed orthodontic treatment. However, this may affect the friction and surface roughness of the bracket-wire assembly which in turn affects the biological tooth movement. MATERIAL AND METHODS: A total of 60 samples were included in the study which was divided into four groups. Group-1: * 15 silver coated 0.022 x 0.028" slot MBT prescription maxillary central incisor brackets * 15 silver coated 0.019 x 0.025" stainless-steel wires; Group-2: * 15 uncoated 0.022 x 0.028" slot MBT prescription maxillary central incisor brackets * 15 silver coated 0.019 x 0.025" stainless-steel wires; Group-3: * 15 silver coated 0.022 x 0.028" slot MBT prescription maxillary central incisor brackets * 15 uncoated 0.019 x 0.025" stainless-steel wires; Group-4: * 15 uncoated 0.022x0.028" slot MBT prescription maxillary central incisor brackets * 15 uncoated 0.019 x 0.025" stainless-steel wires. All brackets and wires used were of American Orthodontics, St. Paul, USA. Surface modification of wires and brackets was carried out using the Vacuum Coating Unit model by Thermal Vacuum Evaporation method with silver nanoparticles (10 nm size). The frictional resistance of all brackets and wires was checked using Universal Testing Machine. RESULTS: On comparison of maximum load, it was found that friction was highest in group 3, followed by group 1, group 4 and group 2. The mean difference between all groups was found to be statistically significant with a P value Group 1> Group 2> Group 3 *Wire roughness: Group 4> Group 1> Group 2> Group 3. CONCLUSIONS: This study concluded that friction was least when only the wire was coated with silver and the bracket was uncoated and it was the most when the bracket was coated and the wire was uncoated. The surface roughness after the friction test was the least when the wire was uncoated. Key words:Silver nanoparticles, Frictional Resistance, Surface Roughness

Exploring the Elusive: Locating the MB2 Canal in Maxillary First Molars

The maxillary first molar is renowned for its anatomical complexity particularly the presence of multiple canals including the elusive MB2 canal. Inability to identify and adequately treat this canal can result in treatment failure and subsequent complications. Therefore clinicians must possess a thorough understanding of anatomical variations and employ advanced techniques to improve success rates. This case report highlights the successful identification and negotiation of the MB2 canal in a maxillary first molar a challenging yet crucial aspect of endodontic treatment. A 25-year-old male presented with asymptomatic irreversible pulpitis in the maxillary right first molar. Clinical examination revealed deep caries without tenderness on percussion or palpation while radiographic examination showed extensive decay and periapical radiolucency. The MB2 canal was located and negotiated using a combination of hand files and rotary instruments under copious irrigation. Patency was confirmed and the canal was thoroughly debrided and shaped to facilitate obturation. Root canal filling was then completed with gutta-percha and sealer. This report underscores the significance of MB2 canal exploration in maxillary first molars and emphasizes the role of contemporary endodontic techniques in managing complex anatomical variations

Comparison of effectiveness of audio and VR distraction techniques in managing pediatric dental patients

Aim: In order to manage pediatric dental patients, this study set out to assess the effectiveness of two distraction techniques: audio and virtual reality (VR) with tell, show, and do technique (TSD). Materials and Methods: Forty-five children aged 6–10 years were selected for the present randomized control trial. They were split into three groups at random. Group 1 control group: tell-show-do, Group 2: audio distraction, and Group 3: VR distraction. Both pretreatment and postoperative anxiety levels were measured by modified Venham's anxiety rating scale (MVARS). Results: In each of the three groups, there was a statistically significant difference between the child's pre- and post-treatment anxiety levels. VR distraction group experienced the greatest reduction in anxiety. Conclusion: All three methods were similarly successful at lowering anxiety while virtual reality distraction outperformed compared to other techniques

Spatial Epidemiology of Signet-ring Cell Colorectal Cancer in India

Background: Signet-ring cell colorectal carcinoma (SRCC) is an extremely aggressive yet uncommon histologic subtype of colorectal cancer (CRC) with an unknown etiology. There is a stark difference in the prevalence of signet cancers between Western countries and the Indian subcontinent; however, India itself is a vast and diverse country with variable cancer incidence. Objective: To study the spatial epidemiology of SRCC in India for identifying regions with high prevalence. Methods: This retrospective study included all patients diagnosed with colorectal adenocarcinoma at Tata Memorial Hospital, the largest colorectal cancer referral unit in India, between January 2020 and December 2022. Geocoding based on the location of the residence was done to map the incidences. Comparisons were performed between the proportion of signet cell and non-signet colorectal cancers. Results: A total of 4100 patients with colon or rectal adenocarcinomas were included, of which signet cell histology was found in 624 (15%) patients. SRCC accounted for the highest proportions of CRCs in the Central (19%) and Northern (19%) regions, and the lowest in the North-Eastern (10%) and Western (12%) regions of India (P < 0.001), with non-overlapping confidence intervals. Compared with patients with non-signet CRCs, those with SRCC more commonly had colon cancers (22% vs. 17%; P = 0.003) and belonged to a lower socioeconomic background (67% vs. 59%; P < 0.001). Conclusions: This study found that SRCCs accounted for a significant proportion of CRC cases in India, but there was no substantial disparity in distribution across regions

A Method Noise-Based Convolutional Neural Network Technique for CT Image Denoising

Medical imaging is a complex process that capitulates images created by X-rays, ultrasound imaging, angiography, etc. During the imaging process, it also captures image noise during image acquisition, some of which are extremely corrosive, creating a disturbance that results in image degradation. The proposed work addresses the challenge to eliminate the corrosive Gaussian additive white noise from computed tomography (CT) images while preserving the fine details. The proposed approach is synthesized by amalgamating the concept of method noise with a deep learning-based framework of a convolutional neural network (CNN). The corrupted images are obtained by explicit addition of Gaussian additive white noise at multiple noise variance levels (σ = 10, 15, 20, 25). The denoised images obtained are then evaluated according to their visual quality and quantitative metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These metrics for denoised CT images are then compared with their respective values for the reference CT image. The average PSNR value of the proposed method is 25.82, the average SSIM value is 0.85, and the average computational time is 2.8760. To better understand the proposed approach’s effectiveness, an intensity profile of denoised and original medical images is plotted and compared. To further test the performance of the proposed methodology, the results obtained are also compared with that of other non-traditional methods. The critical analysis of the results shows the commendable efficiency of the proposed methodology in denoising the medical CT images corrupted by Gaussian noise. This approach can be utilized in multiple pragmatic areas of application in the field of medical image processing