ObjectivesThis study aimed to determine the prevalence of certain oral characteristics usually associated with Down syndrome and to determine the oral health status of these patients.MethodsThe cross-sectional study was conducted among patients attending a special education program at Faculty of Dentistry, Jamia Millia Islamia, Delhi, India. The study design consisted of closed-ended questions on demographic characteristics (age, sex, and education and income of parents), dietary habits, and oral hygiene habits. Clinical examination included assessment of oral hygiene according to Simplified Oral Hygiene Index (OHI-S), dental caries according to decayed, missing, and filled teeth (DMFT) index, periodontal status according to the Community Periodontal Index of Treatment Needs (CPITN), and malocclusion according to Angles classification of malocclusion. Examinations were carried out using a using a CPI probe and a mouth mirror in accordance with World Health Organization criteria and methods. Craniometric measurements, including maximum head length and head breadth were measured for each participant using Martin spreading calipers centered on standard anthropological methods.ResultsThe majority of the patients were males (n = 63; 82%) with age ranging from 6–40 years. The Intelligence Quotient (IQ) score of the patients indicated that 31% had moderate mental disability and 52% had mild mental disability. 22% exhibited hearing and speech problems.12% had missing teeth and 15% had retained deciduous teeth in adult population. The overall prevalence of dental caries in the study population was 78%. DMFT, CPITN and OHI scores of the study group were 3.8 ± 2.52, 2.10 ± 1.14 and 1.92 ± 0.63 respectively. The vast majority of patients required treatment (90%), primarily of scaling, root planing, and oral hygiene education. 16% of patients reported CPITN scores of 4 (deep pockets) requiring complex periodontal care. The prevalence of malocclusion was 97% predominantly of Class III malocclusions. Further 14% presented with fractured anterior teeth primarily central incisor. The percentage means of cephalic index was 84.6% in the study population. The brachycephalic and hyperbrachycephalic type of head shape was dominant in the Down syndrome individuals (90%).ConclusionThe most common dentofacial anomaly seen in these individuals was fissured tongue followed by macroglossia.
To realize the promise of ubiquitous embedded deep network inference, it is essential to seek limits of energy and area efficiency. To this end, low-precision networks offer tremendous promise because both energy and area scale down quadratically with the reduction in precision. Here, for the first time, we demonstrate networks on the ImageNet classification benchmark that, at 8-bit precision exceed the accuracy of the full-precision baseline networks after one epoch of finetuning, thereby leveraging the availability of pretrained models. We also demonstrate ResNet-18, ResNet-34, ResNet-50, ResNet-152, Densenet-161, and VGG-16bn 4-bit models that match the accuracy of the full-precision baseline networks -the highest scores to date. Surprisingly, the weights of the low-precision networks are very close (in cosine similarity) to the weights of the corresponding baseline networks, making training from scratch unnecessary. We find that gradient noise due to quantization during training increases with reduced precision, and seek ways to overcome this noise. The number of iterations required by stochastic gradient descent to achieve a given training error is related to the square of (a) the distance of the initial solution from the final plus (b) the maximum variance of the gradient estimates. By drawing inspiration from this observation, we (a) reduce solution distance by starting with pretrained fp32 precision baseline networks and fine-tuning, and (b) combat noise introduced by quantizing weights and activations during training by training longer and reducing learning rates. Sensitivity analysis indicates that these simple techniques, coupled with proper activation function range calibration to take full advantage of the limited precision, are sufficient to discover low-precision networks, if they exist, close to fp32 precision baseline networks. The results herein provide evidence that 4bits suffice for classification.
Prosthetic rehabilitation of acquired maxillary defects can be achieved satisfactorily if all facets of treatment planning and design considerations are taken into account before the rehabilitation process. Complications associated with maxillary defects limit treatment protocols to a great extent. The prosthodontist has to identify these problem areas and suitably devise feasible options and incorporate them in the design. In this report, an acquired maxillary defect with unfavorable undercuts in the defect was successfully treated by making a two-piece sectional obturator. The two pieces were connected by the use of double-die pin system. The methodology greatly reduced chairside time and number of visits, and effective obturation was satisfactorily achieved.
Aims. Silver stainable nucleolar organizer regions (AgNORs) have received a great deal of attention recently as their frequency within the nuclei is significantly higher in malignant cells than in normal, reactive or benign neoplastic cells. The objective of this study was to carry out a quantitative assessment of large and small AgNORs in oral normal mucosa, precancerous lesions and infiltrating squamous cell carcinomas. Methods. The study comprised 110 formalin-fixed, paraffin-embedded oral mucosal biopsies consisting of 30 oral dysplasia, 60 oral squamous cell carcinomas and 20 normal oral mucosa. AgNORs were counted in each nucleus, categorized as small, large and total number of AgNORs in each cell and their means were calculated. Results. The mean value of small AgNORs, large AgNORs and total AgNORs increased gradually from normal mucosa to dysplastic lesions to squamous cell carcinomas. The study clearly indicates that in oral squamous cell carcinomas, AgNORs diminish in size as they increase in number. Further, AgNOR counts increase as the degree of malignant potential of the cell increases. Conclusions. By combining both the enumeration of AgNORs and their size, good distinction can be made between normal, dysplastic and infiltrating squamous cell carcinomas. This could help in the early diagnosis and prognosis of dysplastic mucosal lesions and their malignant transformation.
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