AIM: To evaluate the fracture resistance and failure pattern of three different cavity designs restored with monolithic zirconia.
MATERIALS AND METHODS: Human maxillary premolars atraumatically extracted for orthodontic reasons were chosen. A total of 40 teeth were selected and divided into four groups (n=10). Group I-Sound teeth (control with no preparation). Group II-MOD Inlay, Group III-Partial Onlay, Group IV-Complete Onlay. Restorations were fabricated with monolithic partially sintered zirconia CAD (SAGEMAX- NexxZr). All the 30 samples were cemented using Multilink Automix (Ivoclar) and subjected to fracture resistance testing using Universal Testing Machine (UTM) (Instron) with a steel ball of 3.5 mm diameter at crosshead speed of 0.5 mm/minute. Stereomicroscope was used to evaluate the modes of failure of the fractured specimen. Fracture resistance was tested using parametric one way ANOVA test, unpaired t-test and Tukey test. Fracture patterns were assessed using non-parametric Chi-square test.
RESULTS: Group IV (Complete Onlay) presented highest fracture resistance and showed statistical significant difference. Group II (MOD Inlay) and Group III (Partial Onlay) showed significantly lower values than the Group I (Sound teeth). However, Groups I, II and III presented no significant difference from each other. Coming to the modes of failure, Group II (MOD Inlay) and Group III (Partial Onlay) presented mixed type of failures; Group IV (Complete Onlay) demonstrated 70% Type I failures.
CONCLUSION: Of the three cavity designs evaluated, Complete Onlay had shown a significant increase in the fracture resistance than the Sound teeth.
METHOD: Two hundred sixty eight serum specimens collected from patients that were diagnosed for dengue fever were confirmed for dengue virus serotyping by real-time polymerase chain reaction. Clinical, laboratory and demographic data were extracted from the hospital database to identify patients with confirmed leptospirosis infection among the dengue patients. Thus, frequency of co-infection was calculated and association of the dataset with dengue-leptospirosis co-infection was statistically determined.
RESULTS: The frequency of dengue co-infection with leptospirosis was 4.1%. Male has higher preponderance of developing the co-infection and end result of shock as clinical symptom is more likely present among co-infected cases. It is also noteworthy that, DENV 1 is the common dengue serotype among all cases identified as dengue-leptospirosis co-infection in this study.
CONCLUSION: The increasing incidence of leptospirosis among dengue infected patients has posed the need to precisely identify the presence of co-infection for the betterment of treatment without mistakenly ruling out either one of them. Thus, anticipating the possible clinical symptoms and laboratory results of dengue-leptospirosis co-infection is essential.
METHODS: The development of the FitSight fitness tracker involved the designing of two components: (1) the smartwatch with custom-made FitSight watch application (app) to log the instant light illuminance levels the wearer is exposed to, and (2) a companion smartphone app that synchronizes the time outdoors recorded by the smartwatch to smartphone via Bluetooth communication. Smartwatch wear patterns and tracker-recorded daily light illuminance levels data were gathered over 7 days from 23 Singapore children (mean ± standard deviation age: 9.2 ± 1.4 years). Feedback about the tracker was obtained from 14 parents using a three-level rating scale: very poor/poor/good.
RESULTS: Of the 14 parents, 93% rated the complete "FitSight fitness tracker" as good and 64% rated its wearability as good. While 61% of 23 children wore the watch on all study days (i.e., 0 nonwear days), 26% had 1 nonwear day, and 4.5% children each had 3, 4, and 5 nonwear days, respectively. On average, children spent approximately 1 hour in light levels greater than 1000 lux on weekdays and 1.3 hours on weekends (60 ± 46 vs. 79 ± 53 minutes, P = 0.19). Mean number of outdoor "spurts" (light illuminance levels >1000 lux) per day was 8 ± 3 spurts with spurt duration of 34 ± 32 minutes.
CONCLUSION: The FitSight tracker with its novel features may motivate children to increase time outdoors and play an important role in supplementing community outdoor programs to prevent myopia.
TRANSLATIONAL RELEVANCE: If the developed noninvasive, wearable, smartwatch-based fitness tracker, FitSight, promotes daytime outdoor activity among children, it will be beneficial in addressing the epidemic of myopia.
METHODS: Data from the World Health Survey conducted in 2002-2004, across 70 low-, middle- and high-income countries was used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as outcome variable. The potential determinants of individual-level BMI were participants' sex, age, marital-status, education, occupation, household-wealth and location(rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP) and income inequality (Gini-index). A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries was fitted, treating BMI as a continuous outcome.
RESULTS: The weighted mean BMI and standard-error of the 206,266 people from 70-countries was 23.90 (4.84). All the low-income countries were below the 25.0 mean BMI level and most of the high-income countries were above. All wealthier quintiles of household-wealth had higher scores in BMI than lowest quintile. Each USD10000 increase in GNI-PPP was associated with a 0.4 unit increase in BMI. The Gini-index was not associated with BMI. All these variables explained 28.1% of country-level, 4.9% of individual-level and 7.7% of total variance in BMI. The cross-level interaction effect between GNI-PPP and household-wealth was significant. BMI increased as the GNI-PPP increased in first four quintiles of household-wealth. However, the BMI of the wealthiest people decreased as the GNI-PPP increased.
CONCLUSION: Both individual-level and country-level factors made an independent contribution to the BMI of the people. Household-wealth and national-income had significant interaction effects.