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Background This study aims to evaluate the levels of caspase-3 in the gingival crevicular fluid (GCF) of chronic periodontitis patients before and after phase I treatment and compare it with those of healthy controls. Methodology The study involved 40 participants who were divided into two groups. Group 1 consisted of 30 chronic periodontitis patients, and group 2 consisted of 10 healthy controls. GCF was collected at baseline for both groups and at three months for group 1. Periodontal parameters and caspase-3 levels were analyzed before and after non-surgical therapy. Results Caspase-3 levels were higher in patients with chronic periodontitis compared with healthy controls. However, comparing baseline and postoperative levels, there was a statistically significant reduction in periodontal parameters and caspase-3 levels, with 0.80 ± 0.03 at baseline and 0.44 ± 0.02 at three months after non-surgical periodontal therapy. Conclusions Caspase-3, being the key molecule in apoptosis, was found to be at lower concentrations in healthy gingiva and was increased in the presence of periodontal disease. However, with non-surgical periodontal therapy, caspase-3 levels decreased, proving that non-surgical periodontal therapy affects host immune mechanisms and reduces apoptosis, thereby preventing disease progression.
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The current advances in digitized data additions, machine learning and computing framework, lead to the swiftly emerging concept of "Artificial Intelligence" (AI), that are developing into areas that were formerly contemplated for human expertise. AI is a relatively rapid paced mechanics wherein the computer technology is tuned to perform human tasks. An auxiliary domain of AI is machine learning (ML), and Deep learning, a subclass of ML technique comprehends multi-layer mathematical operations. AI-based applications have tremendous potential to improve and systematize patient care thereby alleviating dentists from laborious regular tasks, and facilitate personalized, predictive and preventive dentistry. In the dental clinic, AI can execute a variety of easy tasks with greater accuracy, minimal manpower, and with fewer mistakes over human equivalents. These tasks range from appointment scheduling and coordination to helping with clinical evaluation and therapy. Besides, this could assist in the early diagnosis of dental and maxillofacial abnormalities like periodontal ailments, root caries, bony lesions, and facial malformations in addition to automatically identifying and classifying dental restorations on digital radiographs. This brusque narrative review describes the AI-based systems, their respective applications in periodontal diagnosis, the multifarious studies, possible limitations and the predictable future of AI-based dental diagnostics and treatment planning.
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In the realm of well-being, the essence of maintaining optimal oral health is gaining more recognition. This quantifying quotient is being compromised in cerebral palsy (CP) patients due to multitude variations. Spastic CP predominantly impacts bodily motions, muscle synchronization, command, muscle tone, reflexes, stance, equilibrium, and can additionally influence both delicate and large-scale motor abilities. For individuals with spastic CP, the rigidity extends its influence over both their upper and lower limbs. When this stiffness takes hold in the upper limb, it poses significant challenges in executing everyday activities, causing issues with precise grasping and coordination of muscle movements. Consequently, using a toothbrush effectively becomes a formidable task resulting in widespread caries and periodontal diseases in spastic CP patients. The central focus of this review is to explore the oral health challenges of spastic cerebral palsy patients and mapping out a path towards the most efficient time-tested and innovative dental management approaches for preserving oral health in these patients.