Nasal Tip Projection and Facial Attractiveness

Objectives/Hypothesis: Six nasal tip projection (NTP) ratios from Goode, Simons, Baum, Powell, and Crumley guide clinical and academic practice on quantifying NTP, but none have been empirically correlated with facial attractiveness. This study's objectives were to determine: 1) if there is a correlation between these ratios and facial attractiveness; and 2) which of the six ratios has the greatest linkage to overall facial attractiveness. Study Design: Basic research study. Methods: There were 300 digital portraits of women (ages 18-25 years) randomly paired and morphed to create 300 synthetic lateral facial images rated by 78 raters in the community. NTP ratios were measured in each portrait. Results: None of the ratios correlated with facial attractiveness. For the Baum, Powell, and Simons ratio, facial attractiveness increased as NTP deviated 1 and 2 standard deviations from the ideal, whereas facial attractiveness decreased as NTP deviated from the Goode and Crumley ideal ratios. The most attractive faces had NTP ratios consistent with previous expert opinion findings. Conclusions: To our knowledge, this is the first study to empirically correlate these six landmark NTP ratios with facial attractiveness. Although there was no correlation with any of the six ratios, the ideal ratios proposed by Goode and Crumley impacted facial aesthetics the most. Although the ideal ratios are useful in establishing rhinoplasty guidelines, they should only be used as a part of the management in achieving an aesthetic face on the whole, as they may not be robust enough to correlate with overall facial attractiveness

Deleterious Effects of Intermittent Recombinant Parathyroid Hormone on Cartilage Formation in a Rabbit Microfracture Model: a Preliminary Study

Intermittent parathyroid hormone administration can enhance fracture healing in an animal model. Despite the success of exogenous parathyroid hormone on fracture healing and spine fusion, few studies have examined the role of parathyroid hormone on cartilage formation. We determined the effects of intermittent parathyroid hormone on cartilage formation in a rabbit microfracture model of cartilage regeneration. Twelve rabbits were divided into three equal groups: (1) microfracture alone, (2) microfracture + parathyroid hormone daily for 7 days, and (3) microfracture + parathyroid hormone for 28 days. Nonoperated contralateral knees were used as controls. The animals were sacrificed at 3 months and gross and histologic analysis was performed. The microfracture alone group demonstrated the most healing on gross and histologic analysis. Treatment with either 1 or 4 weeks of parathyroid hormone inhibited cartilage formation. Although discouraging from a cartilage repair point of view, this study suggests that the role parathyroid hormone administration has in clinical fracture healing must be examined carefully. Although parathyroid hormone is beneficial to promote healing in spine fusion and midshaft fractures, its deleterious effects on cartilage formation suggests that it may have adverse effects on the outcomes of periarticular fractures such as tibial plateau injuries that require cartilage healing for a successful clinical outcome

EuReCa ONE—27 Nations, ONE Europe, ONE Registry A prospective one month analysis of out-of-hospital cardiac arrest outcomes in 27 countries in Europe

AbstractIntroductionThe aim of the EuReCa ONE study was to determine the incidence, process, and outcome for out of hospital cardiac arrest (OHCA) throughout Europe.MethodsThis was an international, prospective, multi-centre one-month study. Patients who suffered an OHCA during October 2014 who were attended and/or treated by an Emergency Medical Service (EMS) were eligible for inclusion in the study. Data were extracted from national, regional or local registries.ResultsData on 10,682 confirmed OHCAs from 248 regions in 27 countries, covering an estimated population of 174 million. In 7146 (66%) cases, CPR was started by a bystander or by the EMS. The incidence of CPR attempts ranged from 19.0 to 104.0 per 100,000 population per year. 1735 had ROSC on arrival at hospital (25.2%), Overall, 662/6414 (10.3%) in all cases with CPR attempted survived for at least 30 days or to hospital discharge.ConclusionThe results of EuReCa ONE highlight that OHCA is still a major public health problem accounting for a substantial number of deaths in Europe.EuReCa ONE very clearly demonstrates marked differences in the processes for data collection and reported outcomes following OHCA all over Europe. Using these data and analyses, different countries, regions, systems, and concepts can benchmark themselves and may learn from each other to further improve survival following one of our major health care events

Evolving attractive faces using morphing technology and a genetic algorithm: a new approach to determining ideal facial aesthetics.

ObjectivesThe objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face.Study designBasic research study incorporating focus group evaluations.MethodsDigital images were acquired of 250 female volunteers (18-25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Then, a focus group of 17 trained volunteers (18-25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cos-metology students (n = 44), and c) undergraduate students (n = 44). Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis.ResultsThe average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (+/-0.73), 5.50 (+/-0.62), 6.23 (+/-0.31), and 6.39 (+/-0.24) for P and F1-F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces.ConclusionsThe use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects

Evolving attractive faces using morphing technology and a genetic algorithm: a new approach to determining ideal facial aesthetics.

ObjectivesThe objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face.Study designBasic research study incorporating focus group evaluations.MethodsDigital images were acquired of 250 female volunteers (18-25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Then, a focus group of 17 trained volunteers (18-25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cos-metology students (n = 44), and c) undergraduate students (n = 44). Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis.ResultsThe average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (+/-0.73), 5.50 (+/-0.62), 6.23 (+/-0.31), and 6.39 (+/-0.24) for P and F1-F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces.ConclusionsThe use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects