Frontal facial analysis of female celebrity attractiveness standards through artificial intelligence.

The contemporary significance of celebrities' facial aesthetics underscores their heightened importance in shaping attractiveness standards. This retrospective study aimed to investigate the impact of patterns on aesthetic canons in the profile views of female celebrities, using artificial intelligence. The study sought to compare different races and propose standards for attractive faces. In this retrospective cohort study, a Python-based algorithm was used to analyze frontal patterns and evaluate their influence on aesthetic norms in publicly accessible images of female global celebrities. Ten ideal angular or proportional measures were gathered from the literature, and were trained to serve as a benchmark for the analysis of facial attractiveness. Demographic characteristics were described statistically. A one-way ANOVA test was employed to assess data distribution. Differences in means between groups were evaluated using nonparametric independent-sample tests, with statistical significance set at < 0.05. The study involved facial analyses for 115 female celebrities. It revealed variations in facial features among races. The mean golden ratio differed, with African and Asian individuals showing lower ratios. Symmetry varied, with Latin and Caucasian faces considered the most symmetrical. The zygomatic-to-mandibular width ratio was similar across races, with a ratio close to 80% being associated with more attractive faces. Differences in nose-to-mouth ratio, lips, alar base width, and chin angle were noted among race groups. The study concluded that, regardless of race, an attractive female face is characterized by specific ratios and angles. Facial symmetry, though desirable, is not strictly necessary. Irrespective of race background, an appealing female face is characterized by a zygomatic-to-mandibular width ratio nearing 80%, a mid-facial third that is slightly larger than the lower third, and a distinctive chin angle of approximately 138°, contributing to a trapezoidal facial shape. The findings contribute valuable insights into attractiveness standards and the impact of frontal patterns on aesthetic canons in female celebrities.

Haptic devices as an educational approach for oral and maxillofacial surgical procedures.

OBJECTIVE: Developing the skills of a proficient surgeon with a deep understanding of force requires extensive training and repetitive practice. Traditionally, dental students and surgical trainees observed and participated in procedures using models, animals, or cadavers under expert supervision before performing the procedures independently. To address these challenges, interactive simulators with visuo-haptic features have been introduced in surgical training, providing visual and tactile feedback that replicates the sense of touch through applied forces, vibrations, or motions. STUDY DESIGN: Two independent reviewers employed a specific search strategy to explore online databases such as PubMed, Scopus, and Web of Science (WoS). This strategy included keywords such as "haptic device," "education," "oral surgery," "surgery," and "maxillofacial surgery." All types of studies related to maxillofacial surgery, except for case reports, reviews, and eBooks, were considered for inclusion. RESULTS: A total of 22 articles meeting the screening criteria were identified. The use of haptic devices for training dental students in oral surgery, anesthesia, as well as oral and maxillofacial trainees and surgeons in various surgical procedures, was evaluated. CONCLUSION: Incorporating tactile devices into the training of residents and maxillofacial surgeons offers numerous advantages, including improved technical skills and enhanced patient safety.

The butterfly effect in oral and maxillofacial surgery: Understanding and applying chaos theory and complex systems principles.

The present paper provides a historical context for chaos theory, originating in the 1960s with Edward Norton Lorenz's efforts to predict weather patterns. It introduces chaos theory, fractal geometry, nonlinear dynamics, and the butterfly effect, highlighting their exploration of complex systems. The authors aim to bridge the gap between chaos theory and oral and maxillofacial surgery (OMFS) through a literature review, exploring its applications and emphasizing the prevention of minor deviations in OMFS to avoid significant consequences. A comprehensive literature review was conducted on PubMed, Web of Science, and Google Scholar databases. The selection process adhered to the PRISMA-ScR guidelines and Leiden Manifesto principles. Articles focusing on chaos theory principles in health sciences, published in the last two decades, were included. The review encompassed 37 articles after screening 386 works. It revealed applications in outcome variation, surgical planning, simulations, decision-making, and emerging technologies. Potential applications include predicting infections, malignancies, dental fractures, and improving decision-making through disease prediction systems. Emerging technologies, despite criticisms, indicate advancements in AI integration, contributing to enhanced diagnostic accuracy and personalized treatment strategies. Chaos theory, a distinct scientific framework, holds potential to revolutionize OMFS. Its integration with advanced techniques promises personalized, less traumatic surgeries and improved patient care. The interdisciplinary synergy of chaos theory and emerging technologies presents a future in which OMFS practices become more efficient, less traumatic, and achieve a level of precision never seen before.

Emerging Trends in Virtual Surgical Planning for Orthognathic Surgery: A Global Overview of Research and Publication Patterns.

PURPOSE: Anticipating trends and pursuing innovative ideas are imperative for the advancement of science. The objective of this study was to conduct a bibliometric analysis of 3-dimensional virtual simulation in orthognathic surgery, explore its implications for clinical practice, and identify future publication trends through digital tools. METHODS: This study employed a retrospective bibliometric analysis using data obtained from the Web of Science database. The search strategy focused on articles related to orthognathic surgery and virtual simulation techniques. RStudio and bibliometrix tools were used to data mining. The independent variables retrieved from digital analysis were the emerging themes related to virtual planning in orthognathic surgery. The trends that we identified were facial esthetics, digital workflow, personalized treatments, and complex cases. The primary outcome variable was the number of publications dedicated to virtual simulation in orthognathic surgery, along with secondary outcomes such as citation rates, language of publication, country of origin, institutional affiliations, and emerging research themes. Covariates included variables related to publication characteristics, author affiliations, and geographic distribution of publications. Publication analyses over time involved descriptive statistics, regression analysis, Pearson correlation tests, and graphical representation techniques. Statistical significance was set at a 95% confidence interval (P value < .05). RESULTS: A comprehensive analysis of 987 articles reveals the impact of included authors, with a mean h-index of 62 (SD = 18.4). The analysis further illuminates a discernible upward trend in publications on this subject, showcasing a linear pattern with a notable R2 value of 0.88 (P = .021). English remains the predominant language of publication, accounting for 97.97% of articles, while contributions hailed from a diverse spectrum of 56 countries. Interestingly, a moderate correlation emerges between publication numbers and gross domestic product per capita (r = 0.30, P = .044) and total area (r = 0.30, P = .032), whereas a more substantial correlation is evident with total population (r = 0.61, P = .034). Notably, the most cited article amassed 254 citations. Furthermore, a Pearson correlation coefficient of 0.97 underscores the correlation between citation density and the year of publication. CONCLUSION: The bibliometric indicators provided insights for evaluating research productivity and the quality of research output. Emerging themes included facial esthetics, 3-dimensional printing, and the utilization of custom-made templates and implants. This study holds relevance for maxillofacial surgeons, academics, and researchers alike.

Shaping the 4D frontier in maxillofacial surgery with faceMesh evolution.

OBJECTIVES: This work aims to introduce a Python-based algorithm and delve into the recent paradigm shift in Maxillofacial Surgery propelled by technological advancement. The provided code exemplifies the utilization of the MediaPipe library, created by Google in C++, with an additional Python interface available as a binding. TECHNICAL NOTE: The advent of FaceMesh coupled with artificial intelligence (AI), has brought about a transformative wave in contemporary maxillofacial surgery. This cutting-edge deep neural network, seamlessly integrated with Virtual Surgical Planning (VSP), offers surgeons precise 4D facial mapping capabilities. It accurately identifies facial landmarks, tailoring surgical interventions to individual patients, and streamlining the overall surgical procedure. CONCLUSION: FaceMesh emerges as a revolutionary tool in modern maxillofacial surgery. This deep neural network empowers surgeons with detailed insights into facial morphology, aiding in personalized interventions and optimizing surgical outcomes. The real-time assessment of facial dynamics contributes to improved aesthetic and functional results, particularly in complex cases like facial asymmetries or reconstructions. Additionally, FaceMesh has the potential for early detection of medical conditions and disease prediction, further enhancing patient care. Ongoing refinement and validation are essential to address limitations and ensure the reliability and effectiveness of FaceMesh in clinical settings.

The online attention analysis on orthognathic surgery research.

OBJECTIVES: Altmetrics is one of the fields of bibliometrics that seeks to assess the impact and interest of a given subject through Internet users. The aim of this study is to make an altmetric analysis of the orthognathic surgery literature. METHODS: A literature search was conducted using Dimensions app up to December 2023. A list of the 100 most mentioned articles on the topic was compiled. A Google Trends search was performed with same strategy to visualize important data regarding internet search. Charts and tables were created using Microsoft Excel and VOSviewer software to allow bibliometric visualization. RESULTS: There was a very poor correlation between the number of mentions and the number of citations (r = 0.0202). Most articles discussed on technical innovations associated to orthognathic surgery, majority related to virtual planning (n = 26). Other topics considered interesting to internet readers were complications (n = 18), surgical technique (n = 14), and psychological aspects/quality of life (n = 13). CONCLUSION: Online interest in orthognathic surgery closely aligns with the level of academic interest but is also influenced by factors such as location and economic status. The internet is a powerful tool for disseminating scientific research to a broad audience, making it more accessible and engaging than traditional academic channels.

A global landscape analysis of the impact, trends, and dissemination in oral and maxillofacial surgery research.

OBJECTIVE: This study aims to comprehensively analyze the global landscape of oral and maxillofacial surgery (OMFS) literature through bibliometrics. The research focuses on evaluating publication trends, influential topics, and the impact of scholarly works within the field. METHODS: Following the principles of the Leiden Manifesto, a literature search was conducted using the Web of Science database, encompassing seven OMFS journals. A total of 18,218 publications were analyzed, with indicators such as publication language, geographic location, specialty, year, citation, and authorship examined. Statistical analyses, including Pearson correlation tests and angular coefficient calculations, were performed in RStudio. RESULTS: The study revealed a strong upward trend in publications related to orthognathic surgery, trauma, and infections. Geographic analysis indicated a dominance of European and Asian contributions, with the USA leading in overall publications. The impact of self-citations was explored, emphasizing nuanced perspectives on their role in scholarly impact metrics. The data provided insights into the scholarly impact of OMFS publications, including the H-index, number of citations, and citing articles. CONCLUSION: The findings underscored potential global discrepancies in OMFS research, both geographically and in terms of topics covered. The study discussed the influence of language and journal impact on citation counts, emphasizing the role of English publications. Specific topics, such as trauma and infections, exhibited high scholarly interest and citation rates. Recommendations were made to encourage submissions on specific topics, such as cosmetic surgery and pathology, to enhance the diversity of OMFS literature. The study aims to foster international collaboration and leverage bibliometrics for evidence-based decision-making, educational strategies, and advancements in the dynamic field of oral and maxillofacial surgery.

Optimizing drug regimens and supplementation in orthognathic surgery: A comprehensive and practical guide.

OBJECTIVE: This study aimed to comprehensively review the literature and provide a practical guide for optimizing drug regimens and supplementation related to orthognathic surgery. METHODS: The authors conducted a thorough review of the existing literature, following the PRISMA-ScR guidelines. Various types of studies except case reports and reviews were included. The study applied specific inclusion criteria, focusing on perioperative and/or postoperative drugs, medications, or supplementation related to orthognathic surgery. RESULTS: This guide included 78 studies on various medications in orthognathic surgery. It encompasses clinical trials, cohort studies, cross-sectional studies, prospective and retrospective studies. The topics covered include antibiotics, analgesics, corticosteroids, antiemetics, hemostatic agents, local anesthetics, herbal medicine, and botulinum toxin. Pain and edema control involved specific medications, while local anesthesia utilized ropivacaine and bupivacaine. The guide also discusses mineral and vitamin supplementation. The effectiveness of hemostatic agents and antiemetics was highlighted. CONCLUSION: Pain management, reduced swelling, enhanced wound healing, and faster recovery are among the advantages. In addition to the standard drugs and medications, the inclusion of vitamin and mineral supplements, tranexamic acid, postoperative anesthetic blocks, and preemptive antiemetics is anticipated to offer various benefits in orthognathic surgery, despite the limited available evidence.

Wine corks decontamination using plasma activated water.

Cork taint provides off-odors and changes negatively wine composition. In fact, it is one of the most important causes of discarding bottled wine. 2,4,6-Trichloroanisole (TCA) is the most known molecule responsible of that problem. In this study, cork stoppers were artificially contaminated with a multi-pattern solution which contained different chloroanisoles and chlorophenols. Contaminated corks were immersed for 3 h in four Plasma Activated Water (PAW) generated during 1.5 min, 5 min, 15 min and 30 min. The products of OH•, NO• and NO2• with phenol were determined by HPLC for each PAW. After treating contaminated corks with PAW generated during 5 min, more than 72 % of TCA was removed and it was suggested OH• as the main reactive species decomposing TCA. Finally, other chloroanisole and chlorophenol molecules were examined after PAW treatments showing successful reductions in almost every molecule. Thus, it was presented PAW treatment as an easy solution for solving cork taint problems in wine industry.

Pervasive gaps in Amazonian ecological research.

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.

Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

For more than three decades, major efforts in sampling and analyzing tree diversity in South America have focused almost exclusively on trees with stems of at least 10 and 2.5 cm diameter, showing highest species diversity in the wetter western and northern Amazon forests. By contrast, little attention has been paid to patterns and drivers of diversity in the largest canopy and emergent trees, which is surprising given these have dominant ecological functions. Here, we use a machine learning approach to quantify the importance of environmental factors and apply it to generate spatial predictions of the species diversity of all trees (dbh ≥ 10 cm) and for very large trees (dbh ≥ 70 cm) using data from 243 forest plots (108,450 trees and 2832 species) distributed across different forest types and biogeographic regions of the Brazilian Amazon. The diversity of large trees and of all trees was significantly associated with three environmental factors, but in contrasting ways across regions and forest types. Environmental variables associated with disturbances, for example, the lightning flash rate and wind speed, as well as the fraction of photosynthetically active radiation, tend to govern the diversity of large trees. Upland rainforests in the Guiana Shield and Roraima regions had a high diversity of large trees. By contrast, variables associated with resources tend to govern tree diversity in general. Places such as the province of Imeri and the northern portion of the province of Madeira stand out for their high diversity of species in general. Climatic and topographic stability and functional adaptation mechanisms promote ideal conditions for species diversity. Finally, we mapped general patterns of tree species diversity in the Brazilian Amazon, which differ substantially depending on size class.

Advances in the Application of Cold Plasma Technology in Foods.

In the last two decades, non-thermal processing technologies have gained widespread attention from the food industry, which is interested in mild and effective processes [...].

The background microbiota and sanitization agent drive the fate of Listeria monocytogenes in multispecies biofilms formed on a plasma-polymerized coating applied on stainless steel.

The present study evaluates the anti-biofilm activity of a coating applied with an atmospheric-pressure plasma jet system on AISI 316 stainless steel (SS) against multispecies biofilms containing Listeria monocytogenes (using background microbiota from three different meat industries) using culture-dependent and culture-independent approaches. Also, the disinfection effectiveness and biofilm evolution after sanitization with two food industry biocides were assessed. The anti-biofilm activity of the coating against L. monocytogenes, observed on mono-species biofilms (p < 0.05), was lost on the multispecies biofilms developed for 7 days at 12 °C (p > 0.05), with L. monocytogenes counts ranging from 5.5 ± 0.7 to 6.1 ± 0.5 CFU/cm2 on the uncoated SS and from 4.4 ± 0.2 to 6.4 ± 0.5 CFU/cm2 on the coated SS. The taxonomic composition of the formed biofilms was highly dependent on the industry but not affected by the artificial inoculation with L. monocytogenes and the nature of the surface (coated vs uncoated SS). When L. monocytogenes was artificially inoculated, its growth was partially controlled in the biofilms developed, with the magnitude of this effect being lower (p < 0.05 on coated SS) for the industry with the lowest taxonomy richness and diversity (3.8 ± 0.2 CFU/cm2), as compared the other two sampled industries (2.4 ± 0.4 and 1.6 ± 0.2 CFU/cm2). The 15-min disinfection treatments with either sodium hypochlorite or peracetic acid at 0.5 % resulted in total viable and L. monocytogenes counts below the limit of detection in most cases, immediately after treatment. The subsequent incubation of the sanitized plates for another 7 days at 12 °C in fresh BHI media led to the development of biofilms with lower bacterial richness and alpha diversity, and higher beta diversity. Even though sodium hypochlorite was in general slightly less effective than peracetic acid immediately after application, it caused a stronger growth control (p < 0.05) of the naturally present L. monocytogenes on the multispecies biofilms developed. This finding highlights the importance of understanding the interspecific competitive relationships between the members of the background microbiota and L. monocytogenes for the long-term control of this pathogen in food processing facilities.

Dextrose Prolotherapy for Symptomatic Grade IV Knee Osteoarthritis: A Pilot Study of Early and Longer-Term Analgesia and Pain-Specific Cytokine Concentrations.

Background: Neurocytokines may upregulate or downregulate neuropathic pain. We hypothesized that dextrose (D-glucose) injections for therapeutic purposes (dextrose prolotherapy: DPT) in painful knee osteoarthritis (KOA) would favorably affect synovial-fluid neurocytokine concentrations. Methods: Twenty participants with grade IV symptomatic KOA received synovial-fluid aspiration followed by dextrose or simulated dextrose injections, followed by the reverse after one week. All participants then received open-label dextrose injections monthly for 6 months, with serial assessments of walking pain at 20 min for 9 months, as well as synovial-neurocytokine-concentration measurements (calcitonin gene-related peptide, substance P (SP), and neuropeptide Y (NPY)) at one week and three months. Results: Clinically important analgesia was observed at 20 min and for 9 months post dextrose injection. One -week synovial-fluid SP concentration rose by 111% (p = 0.028 within groups and p = 0.07 between groups) in the dextrose-injected knees compared to synovial-fluid aspiration only. Three-month synovial-fluid NPY concentration dropped substantially (65%; p < 0.001) after open-label dextrose injection in all knees. Conclusions: Prompt and medium-term analgesia after intra-articular dextrose injection in KOA was accompanied by potentially favorable changes in synovial-fluid neurocytokines SP and NPY, respectively, although these changes were isolated. Including neurocytokines in future assessments of DPT to elucidate mechanisms of action is recommended.

Mask disinfection using atmospheric pressure cold plasma.

OBJECTIVES: Mask usage has increased over the last few years due to the COVID-19 pandemic, resulting in a mask shortage. Furthermore, their prolonged use causes skin problems related to bacterial overgrowth. To overcome these problems, atmospheric pressure cold plasma was studied as an alternative technology for mask disinfection. METHODS: Different microorganisms (Pseudomonas aeruginosa, Escherichia coli, Staphylococcus spp.), different gases (nitrogen, argon, and air), plasma power (90-300 W), and treatment times (45 seconds to 5 minutes) were tested. RESULTS: The best atmospheric pressure cold plasma treatment was the one generated by nitrogen gas at 300 W and 1.5 minutes. Testing of breathing and filtering performance and microscopic and visual analysis after one and five plasma treatment cycles, highlighted that these treatments did not affect the morphology or functional capacity of the masks. CONCLUSION: Considering the above, we strongly believe that atmospheric pressure cold plasma could be an inexpensive, eco-friendly, and sustainable mask disinfection technology enabling their reusability and solving mask shortage.

Strong floristic distinctiveness across Neotropical successional forests.

Forests that regrow naturally on abandoned fields are important for restoring biodiversity and ecosystem services, but can they also preserve the distinct regional tree floras? Using the floristic composition of 1215 early successional forests (≤20 years) in 75 human-modified landscapes across the Neotropic realm, we identified 14 distinct floristic groups, with a between-group dissimilarity of 0.97. Floristic groups were associated with location, bioregions, soil pH, temperature seasonality, and water availability. Hence, there is large continental-scale variation in the species composition of early successional forests, which is mainly associated with biogeographic and environmental factors but not with human disturbance indicators. This floristic distinctiveness is partially driven by regionally restricted species belonging to widespread genera. Early secondary forests contribute therefore to restoring and conserving the distinctiveness of bioregions across the Neotropical realm, and forest restoration initiatives should use local species to assure that these distinct floras are maintained.

Development and characterization of anti-biofilm coatings applied by Non-Equilibrium Atmospheric Plasma on stainless steel.

Biofilm-mediated microbial persistence of pathogenic and spoilage bacteria is a serious problem in food industries. Due to the difficulty of removing mature biofilms, great efforts are being made to find new strategies to prevent bacterial adherence to surfaces, the first step for biofilm development. In this study, coatings of (3-aminopropyl)triethoxysilane (APTES), tetraethyl orthosilicate (TEOS) and acrylic acid (AA) were applied by Non-Equilibrium Atmospheric Plasma on stainless steel (SS) AISI 316, the SS most commonly used in food industry equipment. Their anti-biofilm activity was assessed against Listeria monocytogenes CECT911 and Escherichia coli CECT515 after incubation at 37 °C. The best results were obtained for L. monocytogenes, with coatings consisting of a base coating of APTES and a functional coating of TEOS (AP10 + TE6) or AA (AP10 + AA6) that reduced biofilm production by 45% and 74%, respectively, when compared with the uncoated SS. These coatings were further characterized, together with a variation of the best one that replaced the acrylic acid with succinic acid (AP10 + SA6). Their anti-biofilm activity was assessed under different incubation conditions, including two strains of L. monocytogenes isolated from processing environments of a meat industry. The coating AP10 + AA6 reduced the biofilm formation by 90% after incubation at 12 °C, a temperature more representative of those commonly found in food processing environments. The morphological and physico-chemical characterization of the selected coatings showed that the coating with the highest anti-biofilm activity (i.e., AP10 + AA6) had lower surface roughness and higher hydrophilicity. This suggests that the formation of a hydration layer prevents the adherence of L. monocytogenes, an effect that seems to be enhanced by low temperature conditions, when the wettability of the strains is increased.

Height-diameter allometry for tropical forest in northern Amazonia.

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.