Effectiveness of Audiovisual Distraction Technique and Filmed Modeling on Anxiety and Fear in Pediatric Dental Patients.

Aim: To evaluate the effectiveness of the audiovisual distraction (AVD) technique and filmed modeling (FM) on anxiety and fear in pediatric dental patients. Materials and methods: This experimental in vivo study was conducted on 80 subjects of age-groups 5-8 years coming to the Department of Pediatric and Preventive Dentistry for their first dental visit. Study subjects were subjected to noninvasive restorative treatment under AVD in group I, FM in group II, and a combination of AVD and FM in groups III and IV (control 0). To assess the level of pre and postoperative anxiety and fear, various biological parameters like pulse rate, oxygen saturation, body temperature, respiratory rate, and salivary cortisol estimation along with facial image scale (FIS), and fear assessment picture scale (FAPS) were used. Results: Group III (a combination of AVD and FM) came out to be better than other experimental groups and control groups in reducing dental anxiety and fear in pediatric dental patients. Conclusion: A combination of AVD and FM techniques can be recommended to be used as an effective behavior management technique. Clinical significance: A child's disruptive behavior due to dental anxiety causes difficulty in delivering effective dental treatment. Thus, a child's behavior management is of paramount importance in the pediatric dental setup. Nonpharmacological behavior management techniques, that is, a combination of AVD and FM techniques can be recommended to be used as an effective behavior management technique to reduce dental anxiety and fear in pediatric dental patients. How to cite this article: Jamil F, Khan SY, Jindal MK. Effectiveness of Audiovisual Distraction Technique and Filmed Modeling on Anxiety and Fear in Pediatric Dental Patients. Int J Clin Pediatr Dent 2023;16(4):598-602.

Construction of a comprehensive protein-protein interaction map for multi drug resistant klebsiella pneumoniae to identify drug targets: A computational approach.

Klebsiella pneumoniae is an encapsulated rod-shaped, Gram-negative microbe that can form biofilm. It is an opportunistic Enterobacter usually involved in nosocomial infection, conferring resistance to almost all antibiotics and hence become therapeutically challenging. In the current study, the Protein Interaction Network (PIN) of MDR K. pneumoniae has been identified. The proteins are the building blocks of all organisms. Proteins interact with each other to carry out their physiological functions. The interactions are integrated to form Protein Interaction Network (PIN). The strain DA48896 has been selected as it was isolated from Pakistan and harboring bla-oxa-181, conferring resistance to carbapenem. Total 20,936 high confidence interactions of 3782 proteins have been predicted from the STRING database. The predicted interactions were annotated functionally and mapped on their corresponding pathways. The predicted PIN was verified using semantic similarity between the Gene Ontology. The topological properties were calculated and retrieved topologically significant proteins consisting of 390 proteins. Among them 49 proteins are non-homologous essential that can serve as the potential drug targets. These proteins were further explored for druggability, their association with pathways involved in drug resistance and eventually prioritized as potential drug targets. This study will be helpful to design drug candidates against prioritized proteins.

Protein Integrated Network Analysis to Reveal Potential Drug Targets Against Extended Drug-Resistant Mycobacterium tuberculosis XDR1219.

The reconstruction and analysis of the protein-protein interaction (PPI) network is a powerful approach to understand the complex biological and molecular functions in normal and disease states of the cell. The interactome of most organisms is largely unidentified except some model organisms. The current study focused on the construction of PPI network for the human pathogen Mycobacterium tuberculosis (MTB)-resistant strain XDR1219 using computational methods. In this work, a bioinformatics approach was employed to reveal potential drug targets. The pipeline adopted the combination of an extensive integrated network analysis that led to identify 22 key proteins involved in drug resistance, resistant metabolic pathways, virulence, pathogenesis and persistency of the infection. The MTB XDR1219 interactome consists of 11,383 non-redundant PPIs among 1499 proteins covering 38% of the entire MTB XDR1219 proteome. The overall quality of the network was assessed and topological parameters of the PPI were calculated. The predicted interactions were functionally annotated and their relevance was assessed with the functional similarity. The study attempts to present the interactome of previously unidentified MTB XDR1219 and revealed potential drug targets that can be further explored by scientific community.

Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network.

Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa.

Evidence for general and domain-specific elements of teacher-child interactions: associations with preschool children's development.

This study evaluates a model for considering domain-general and domain-specific associations between teacher-child interactions and children's development, using a bifactor analytic strategy. Among a sample of 325 early childhood classrooms there was evidence for both general elements of teacher-child interaction (responsive teaching) and domain-specific elements related to positive management and routines and cognitive facilitation. Among a diverse population of 4-year-old children (n = 1,407) responsive teaching was modestly associated with development across social and cognitive domains, whereas positive management and routines was modestly associated with increases in inhibitory control and cognitive facilitation was associated with gains in early language and literacy skills. The conceptual and methodological contributions and challenges of this approach are discussed.