ABSTRACT
BACKGROUND: The success of any dental prosthesis depends on aesthetics and function. A proper shade selection is a prime requisite for providing aesthetics to dental patients. PURPOSE: This study aims to compare the photographic method of shade selection with that of a digital spectrophotometer. MATERIALS AND METHODS: The study included 50 participants. The primary inclusion criterion was the presence of the maxillary left central incisor without a history of restorative or endodontic procedures. The shade of the left maxillary central incisor was determined using the VITA Easyshade V spectrophotometer (VITA Zahnfabrik, BadSäckingen, Germany) and the digital photography method for all the selected participants. The CIELAB colour space utilizes three values (L*, a*, and b*) to objectively measure colour. While the digital photography approach used Adobe Photoshop software (Adobe Systems Incorporated, San Jose, CA) to report solely the L*, a*, and b* values, the spectrophotometer reported the L*, a*, and b* values along with the actual shade. After obtaining the values of L*, a*, and b*, ΔE, which is their difference, was calculated using a standard formula. Statistical analysis was carried out by using Student's t-test and proportion z-test. RESULTS: When the comparison of the L*a*b* values was done, Student's t-test showed similar (P>0.05) L(t=0.16, P=0.872), a (t=0.52, P=0.607), and b (t=0.23, P=0.820) values between the two groups; that is, they did not differ significantly or showed perfect matching. There was agreement (ΔE≤2) in 42 (84.0%) cases and disagreement (ΔE>2) in eight (16.0%) cases. The proportion z-test showed an agreement of 84.0%, which was statistically highly significant (z=20.44, P<0.001). CONCLUSION: The true shade of the teeth can be depicted using standardized digital images.
ABSTRACT
The contribution of de novo variants as a cause of intellectual disability (ID) is well established in several cohorts reported from the developed world. However, the genetic landscape as well as the appropriate testing strategies for identification of de novo variants of these disorders remain largely unknown in low-and middle-income countries like India. In this study, we delineate the clinical and genotypic spectrum of 54 families (55 individuals) with syndromic ID harboring rare de novo variants. We also emphasize on the effectiveness of singleton exome sequencing as a valuable tool for diagnosing these disorders in resource limited settings. Overall, 46 distinct disorders were identified encompassing 46 genes with 51 single-nucleotide variants and/or indels and two copy-number variants. Pathogenic variants were identified in CREBBP, TSC2, KMT2D, MECP2, IDS, NIPBL, NSD1, RIT1, SOX10, BRWD3, FOXG1, BCL11A, KDM6B, KDM5C, SETD5, QRICH1, DCX, SMARCD1, ASXL1, ASXL3, AKT3, FBN2, TCF12, WASF1, BRAF, SMARCA4, SMARCA2, TUBG1, KMT2A, CTNNB1, DLG4, MEIS2, GATAD2B, FBXW7, ANKRD11, ARID1B, DYNC1H1, HIVEP2, NEXMIF, ZBTB18, SETD1B, DYRK1A, SRCAP, CASK, L1CAM, and KRAS. Twenty-four of these monogenic disorders have not been previously reported in the Indian population. Notably, 39 out of 53 (74%) disease-causing variants are novel. These variants were identified in the genes mainly encoding transcriptional and chromatin regulators, serine threonine kinases, lysosomal enzymes, molecular motors, synaptic proteins, neuronal migration machinery, adhesion molecules, structural proteins and signaling molecules.
