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Context: Various agents are studied for their remineralization potential. Aim: To evaluate the effect of GC Tooth Mousse and Toothmin Tooth Cream on microhardness of bleached enamel. Settings and Design: In vitro- study. Methods and Material: Twenty freshly extracted anterior teeth were cut sagittally and impregnated in cold cure acrylic resin. Specimens were kept in artificial saliva to prevent from dehydration. After measuring baseline hardness, teeth were randomly divided into two groups. Everbrite In - Office Tooth whitening kit (Dentamerica) was used to demineralize the teeth following which hardness was measured again. Teeth in group one (n=10) and group two (n=10) were treated with GC tooth mousse (Recaldent) and Toothmin tooth cream (Abbott Healthcare Pvt.Ltd) daily for seven days and microhardness of enamel surface was measured. Statistical Analysis Used: Mean, SD, and percentage change in the microhardness were calculated. Student's paired t-test was used to evaluate the signifi cance of change from initial, after bleaching for 5 min and after 1-week remineralization Unpaired't' test was used to compare difference between groups. Results: Microhardness significantly decreased in both groups after bleaching (% change group one: 3.24% group two: 3.26% in group; P<0.01 in both groups). Both products significantly increased mineralization after seven days of treatment (P<0.01). Remineralization was numerically better in Toothmin group (Abbott Healthcare Pvt.Ltd ) compared to GC Mousse(Recaldent) (% change 3.27% vs 6.34%). However, difference was not significant (P >0.05). Conclusion: Both GC Tooth Mousse (Recaldent) and Toothmin Tooth cream (Abbott Healthcare Pvt.Ltd) increase the microhardness of bleached enamel. Toothmin tooth cream is a better agent for increasing microhardness, although difference is not significant.

Aim: The aim of this study is to evaluate and compare the coronal discoloration induced by two Triple antibiotic paste (TAP 1 and 2), when used with varying depths of 2 and 4 mm of temporary sealing materials at the end of 0, 3, and 6 weeks. Objectives: (1) To evaluate coronal discoloration induced by TAP-1 when the depth of the temporary restorative material is 2 mm below cementoenamel junction at the end of 0, 3, and 6 weeks. Materials and Methods: Forty extracted permanent maxillary central and lateral incisors or single-rooted tooth were collected and chosen for the study. They were then divided into two groups and each group was then subdivided into two subgroups. Results: Both the triple antibiotic paste showed discoloration but it reduced with increase in thickness of temporary cement. Conclusion: TAP 1 and TAP 2 both showed an increase in discoloration, greater discoloration was seen with TAP, containing minocycline. There was a steady change in the discoloration from 0 to 6thweek. In both the groups, TAP 1 and TAP 2, there was a reduction in discoloration with increase thickness of the temporary restorative material.

Context: Mineral trioxide aggregate (MTA) is a biocompatible repair material that is often used along with glass ionomer cement (GIC) in many clinical situations. Aims: In this study, the interface of GIC and MTA was examined, and the effect of time on this interface was tested. Settings and Design: Materials tested were set and plastic moulds and analysed. Materials and Methods: Forty 9-mm hollow cylindrical glass molds were filled with MTA and then according to the group either conventional GIC or resin-modified GIC (RMGIC) is filled immediately or after 45 min. The specimens were then sectioned, carbon coated, and examined using a scanning electron microscope (SEM) and the elemental analysis was done. Statistical Analysis: Observational study, no statistical analysis done. Results: The SEM showed that both the groups underwent adhesive separation and gap formation at the interface. The specimens in which GIC was condensed over freshly mixed MTA (group IIA and group IIB) also showed cohesive separation in MTA; however, it was more in the GIC condensed after 45 min over MTA groups (group IA and group IB). The results were better for conventional GIC than RMGIC. Conclusions: GIC can be applied over freshly mixed MTA with minimal effects on the MTA, but this effect decreases with time.

Introduction: Conventional Class II cavity preparations used for restoring small lesions with amalgam may be inappropriate for composite resin restorations due to the extensive cavity form, large occlusal contact area, and thin or missing margins of the tooth. Cavity preparation in the proximal areas as per the precepts of Clark is a conservative method of caries excavation and tooth preparation. Materials and Methods: Conventional Class II and Clark's Class II cavities were prepared on the mesial surfaces of 60 molars. All cavities were given a standard buccolingual width of 2 mm, an occlusogingival height of approximately 3.5 mm and an axial depth of 1.5 mm. These were then restored using flowable composites or resin-modified glass-ionomer cement liners and nanohybrid composites. The compressive bond strength was tested with a universal testing machine. Results: The compressive bond strength was the highest for Clarks Class II cavity preparation with a lining of flowable composites. Conventional Box only Class II cavities restored with flowable liners showed the next best result. Conclusion: Clark's class II cavity preparation can be used as efficiently as the conventional Class II box preparation with the advantage of preserving more tooth structure, more precise tooth preparation, good bond strength and better esthetics.

Restoring vital teeth with minimal sacrifice of sound tooth structure depends mainly on adhesives that provide strong and durable bonding to the remaining sound enamel and dentin. Laboratory reports have proven that modern adhesives do effectively bond to tooth tissue in the short term. This article shows the various materials available other than composites that may enhance the strength of the tooth after restoration.

It is usually believed that root canal therapy fails because of failure to follow treatment protocols. However, sometimes even after following the highest standards of treatment the outcome of the therapy is not good. The cause for this might be intra radicular or extra radicular. Clinicians mostly concern themselves with the root canal only and forget the periapical area. The aim of this review is to discuss the commonly neglected extra radicular causes of root canal therapy failure.

Rice ( Oryza sativa L.), a staple food for over half of the global population, is highly sensitive to low temperatures, particularly during early growth stages, resulting in significant yield losses. Addressing cold stress during the early stages of rice cultivation by screening rice genotypes can ensure optimal crop establishment and subsequent growth. An experiment was carried out by selecting ten rice genotypes for evaluation for cold tolerance through laboratory-based germination assays followed by subsequent screening with respect to biometric and biochemical parameters. Meher exhibited the highest germination rate (95%) under cold stress conditions, while Jajati and Ranidhana showed minimal variation in germination (2–7%). PERCOL (Percentage of seeds with coleoptile superior to 5 mm) and REDCOL (Percentage of reduction in coleoptile length) values remained consistent for Jajati and Pradeep. Cold stress led to notable reductions in plant height (9.2–31.1%) and the number of productive tillers per plant (36.8–37.1%). Samanta and Birupa recorded the highest number of productive tillers under control and cold stress conditions, respectively. Panicle exsertion was marginally impacted in Ranidhana (2.9%) and substantial decline recorded in Meher (19.2%), highlighting genotype-specific resilience. Spikelet fertility and 100-seed weight declined by 5.2–7.2% and 15–18%, respectively, in Samanta, and Jajati. Seed yield per plant was highest in Birupa (12.25 g/plant) under cold stress conditions. GGE biplot analysis indicated Kharavela and Birupa as high yielders under control and cold stress, respectively. Highest proline (4.6 mg/g) and carbohydrate content (18.08%) were noted in Samanta. Ranidhana and Samanta resulted in stable yield across environments indicating broader adaptability.

PurposeThis study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination drive, location of vaccination station, assignment of demand group to vaccination station, allocation of the scarce medical professional teams to station and number of optimal days a vaccination station to be functional in a week.Design/methodology/approachThe authors propose a mixed-integer nonlinear programming model. However, to handle nonlinearity, the authors devise a heuristic and then propose a two-stage mixed-integer linear programming (MILP) formulation to optimize the allocation of vaccination centers or stations to demand groups in the first stage and the allocation of vaccination centers to cold storage links in the second stage. The first stage optimizes the cost and average distance traveled by people to reach the vaccination center, whereas the second stage optimizes the vaccine’s holding and storage and transportation cost by efficiently allocating cold storage links to the centers.Findings The model is studied for the real-world case of Chandigarh, India. The results obtained validate that the proposed approach can immensely help government agencies and policymaking body for a successful vaccination drive. The model tries to find a tradeoff between loss due to underutilized medical teams and the distance traveled by a demand group to get the vaccination.Originality/value To the best of our knowledge, there are hardly any studies on a vaccination program at such a scale due to sudden outbreaks such as Covid-19.

Purpose The purpose of the paper is to explore the relationship between workplace empowerment and employee commitment with quality of work life (QWL) as a mediator in the case of private healthcare employees in India. Design/methodology/approach The study used a structured questionnaire to collect primary data from 279 employees of private healthcare units in India. AMOS 20 was used to analyse the data. Findings Results of data analysis confirm that the proposed hypotheses of the study were significant. Structural equation modelling revealed a best-fit model that demonstrated QWL to be a significant partial mediator between workplace empowerment and employee commitment. Practical implications This work provides a pragmatic view about the action mechanism through which workplace empowerment can aid in generating commitment among healthcare employees. The paper also offers insights for healthcare managers, administrators and practitioners. Originality/value The research is an attempt to integrate the employees as the core long-term assets of the healthcare system. The study establishes the triadic and symbiotic alliance of workplace empowerment, QWL and employee commitment in the novel context of healthcare.

Psychological disorders have increased globally at an alarming rate. Among these disorders, depression stands out as one of the leading and most prevalent conditions that have affected more than 280 million people. However, it remains widely undiagnosed and untreated due to lack of sensitive and reliable diagnostic tools. This underscores the imperative for the development of a sensitive and accurate diagnostic tool facilitating the early diagnosis of depression symptoms to mitigate the impending mental illness epidemic. To address this need, we developed an artificial intelligence (AI)-assisted tool utilizing facial expression-based emotion recognition and electroencephalogram (EEG) analysis for the detection of depression symptoms along with their severity level assessment. Our approach yielded successful detection of depression symptoms with an accuracy of 93.58%, a sensitivity of 92.70%, a specificity of 93.40%, and an f1-score of 93.68% through facial emotion recognition task. Additionally, severity level detection employing EEG biomarkers achieved an accuracy of 99.75%, a sensitivity of 99.75%, a specificity of 99.92%, and an f1-score of 99.75%. Consequently, a graphical user interface (GUI) tool was developed that seamlessly integrated the AI with facial image and EEG data inputs, enabling efficient recognition of depression from both real-time and pre-recorded data. The resulting AI assistant demonstrates high sensitivity, precision, and accuracy in the early detection of depression, establishing its potential as a reliable diagnostic tool. The application of our tool may be extended to clinicians, therapists, and hospitals for the identification of depression at its early stage.