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Introduction: To determine the pattern of antibiotic prescription and to assess the knowledge of antibiotic resistance among dentists. Material and Methods: An electronic version of the questionnaire regarding antibiotic use and knowledge on antibiotic resistance was created using google forms and a link was mailed to dental surgeons and their response was recorded. Data obtained was recorded and analysed using descriptive statistics. Results: Out of 130 responses recorded 45.4% of dentists prefer prescribing antibiotics daily. Amoxicillin was the most often recommended antibiotic by majority (49.6%) of the practitioners, While 54.6% of dentists considered a duration of 3 days course of antibiotics for odontogenic infections. 43.7% of the respondent's considered clindamycin as an alternative in penicillin-allergic patients. Abscess was the most common (67.2%) condition considered for antibiotic prescription, 49.6% of the participants stated that availability of a particular brand as a primary factor for prescription of antibiotics. 40.3% of dental surgeons felt that failure to prescribe antibiotics was the main reason for the spread of infection. Almost 91.8% of dental surgeons were aware that antibiotic resistance was becoming a global concern. Conclusion: Antibiotics revolutionized the way infections are being treated, Although incorrect and inappropriate use of antibiotics could be a contributing factor for the development of Antibiotic Resistance. Anti-microbial stewardship should be deeply integrated into dental practice and oral health care, to reduce the number of unnecessary prescriptions and educational intervention is utmost essential to limit non-medical prescriptions. [ABSTRACT FROM AUTHOR]

Objectives: This study was conducted to analyze and identify differences in the palatal rugae patterns and to identify gender wise changes in the palatal rugae shapes in populations of five different states of India. Study Design: Study was conducted in five different Indian states. 500 sample subjects from Andhra Pradesh, Tamil Nadu, Karnataka, Madhya Pradesh and Maharashtra were included. Rugae patterns with predominant shapes were analyzed and categorized according to different states and both genders, data was statistically analyzed using SPSS software 15.0 and the results were obtained by Chi-square analysis. Results: "Wavy" type of palatal rugae pattern is the most predominant variant in five different study groups in both the genders. Conclusion: This study could identify variations in distribution of various palatal rugae pattern in five different states and confirmed the "wavy" type of palatal rugae patterns to be the most predominant variant in five different study groups. [ABSTRACT FROM AUTHOR]

Periapical radiographs are routinely used in dental practice for diagnosis and treatment planning purposes. However, they often suffer from artifacts, distortions, and superimpositions, which can lead to potential misinterpretations. Thus, an automated detection system is required to overcome these challenges. Artificial intelligence (AI) has been revolutionizing various fields, including medicine and dentistry, by facilitating the development of intelligent systems that can aid in performing complex tasks such as diagnosis and treatment planning. The purpose of the present study was to verify the diagnostic performance of an AI system for the automatic detection of teeth, caries, implants, restorations, and fixed prosthesis on periapical radiographs. A dataset comprising 1000 periapical radiographs collected from 500 adult patients was analyzed by an AI system and compared with annotations provided by two oral and maxillofacial radiologists. A strong correlation (R > 0.5) was observed between AI perception and observers 1 and 2 in carious teeth (0.7-0.73), implants (0.97-0.98), restored teeth (0.85-0.89), teeth with fixed prosthesis (0.92-0.94), and missing teeth (0.82-0.85). The automatic detection by the AI system was comparable to the oral radiologists and may be useful for automatic identification in periapical radiographs.

Objective: The purpose of the present study was to verify the diagnostic performance of an AI system for the automatic detection of teeth, caries, implants, restorations, and fixed prosthesis on panoramic radiography., Methods: This is a cross-sectional study. A dataset comprising 1000 panoramic radiographs collected from 500 adult patients was analyzed by an AI system and compared with annotations provided by two oral and maxillofacial radiologists., Results: A strong correlation (R > 0.5) was observed between AI perception and observers 1 and 2 in carious teeth (0.691-0.878), implants (0.770-0.952), restored teeth (0.773-0.834), teeth with fixed prostheses (0.972-0.980), and missing teeth (0.956-0.988)., Discussion: Panoramic radiographs are commonly used for diagnosis and treatment planning. However, they often suffer from artifacts, distortions, and superimpositions, leading to potential misinterpretations. Thus, an automated detection system is required to tackle these challenges. Artificial intelligence (AI) has revolutionized various fields, including dentistry, by enabling the development of intelligent systems that can assist in complex tasks such as diagnosis and treatment planning., Conclusion: The automatic detection by the AI system was comparable to oral radiologists and may be useful for automatic identifications in panoramic radiographs. These findings signify the potential for AI systems to enhance diagnostic accuracy and efficiency in dental practices, potentially reducing the likelihood of diagnostic errors caused by unexperienced professionals., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Studies were carried out to determine the relationship between metabolic histopathological changes in the gastrocnemius muscle of rats in which an acute exudative inflammation had been induced by alkyldimethylbenzylammonium chloride (alkyl-DBAC, a cationic surfactant). Succinate respiration, Na+-K+-Mg2+ ATPase activity and ATP, ADP and AMP levels were determined as the index of metabolic changes. Myofascial edematous swelling with the acceleration of succinate oxidation and Na+-K+-Mg2+ ATPase activity was noted at 30 minutes in the inflamed muscle. The ATP level was also transiently reduced. On the other hand, Na+-K+-Mg2+ ATPase activity and succinate oxidation were inhibited by alkyl-DBAC, at this concentration, in vitro. These results support the possibility that enhancement of energy metabolism is not directly initiated by alkyl-DBAC but may be the result of certain chemical mediators released by alkyl-DBAC. The enhancement of energy metabolism continued after 1 hour and this energy may initiate leukocyte migration as well as increase vascular permeability and edema.