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76), respectively. The 5-year event-free survival was 52.94% (95% CI 41.83, 62.87). In multivariate analysis, the independent prognostic factors were presence of metastasis and completion of treatment for both 5-year and 10-year overall survival. Good histological response was only significant for multivariate analysis at 5 years. Patients with metastasis had a hazard ratio of 20.4 at 5 years and 3.26 at 10 years. CONCLUSION Overall survival rate for osteosarcoma patients at our centre was comparably higher than other centres in the region. Two independent risk factors for survival are metastatic status and completion of treatment. A standardized chemotherapy regime is essential for long-term survival.Early diagnosis is the most important determinant of oral and oropharyngeal squamous cell carcinoma (OPSCC) outcomes, yet most of these cancers are detected late, when outcomes are poor. Typically, nonspecialists such as dentists screen for oral cancer risk, and then they refer high-risk patients to specialists for biopsy-based diagnosis. Because the clinical appearance of oral mucosal lesions is not an adequate indicator of their diagnosis, status, or risk level, this initial triage process is inaccurate, with poor sensitivity and specificity. The objective of this study is to provide an overview of emerging optical imaging modalities and novel artificial intelligence-based approaches, as well as to evaluate their individual and combined utility and implications for improving oral cancer detection and outcomes. The principles of image-based approaches to detecting oral cancer are placed within the context of clinical needs and parameters. A brief overview of artificial intelligence approaches and algorithms is presented, and studies that use these 2 approaches singly and together are cited and evaluated. In recent years, a range of novel imaging modalities has been investigated for their applicability to improving oral cancer outcomes, yet none of them have found widespread adoption or significantly affected clinical practice or outcomes. Artificial intelligence approaches are beginning to have considerable impact in improving diagnostic accuracy in some fields of medicine, but to date, only limited studies apply to oral cancer. These studies demonstrate that artificial intelligence approaches combined with imaging can have considerable impact on oral cancer outcomes, with applications ranging from low-cost screening with smartphone-based probes to algorithm-guided detection of oral lesion heterogeneity and margins using optical coherence tomography. Combined imaging and artificial intelligence approaches can improve oral cancer outcomes through improved detection and diagnosis.We compared socioeconomic life course models to decompose the direct and mediated effects of socioeconomic status (SES) in different periods of life on late-life oral health. We used data from 2 longitudinal Swedish studies the Level of Living Survey and the Swedish Panel Study of Living Conditions of the Oldest Old. Two birth cohorts (older, 1925 to 1934; younger, 1944 to 1953) were followed between 1968 and 2011 with 6 waves. SES was measured with 4 indicators of SES and modeled as a latent variable. Self-reported oral health was based on a tooth conditions question. Variables in the younger and older cohorts were grouped into 4 periods childhood, young/mid-adulthood, mid /late adulthood, late adulthood/life. D34-919 cost We used structural equation modeling to fit the following into lagged-effects life course models 1) chain of risk, 2) sensitive period with late-life effect, 3) sensitive period with early- and late-life effects, 4) accumulation of risks with cross-sectional effects, and 5) accumulation of risks. Chain long-lasting effects on health if they help prevent people from becoming trapped in a chain of risks.Aim Micelles are one of the most promising nanoplatforms for drug delivery, and here, cholesterol-conjugated polyoxyethylene sorbitol oleate (CPSO) micelles have been fabricated for the pulmonary delivery of paclitaxel (PTX). Materials & methods PTX-CPSO micelles were prepared by a dialysis-ultrasonic method, and a single-factor experiment with a Box-Behnken design was conducted to optimize the formulation. Furthermore, intracellular and phagocytosis escape studies of the optimized formulation were performed on A549 and NR8383 cells. Results The optimal micelles exhibited satisfactory encapsulation efficiency (78.48 ± 2.36%) and drug loading (17.06 ± 1.71%). In vitro studies showed enhanced CPSO micelle A549 cellular uptake and their ability to escape macrophages. Conclusion PTX-CPSO micelles could be a promising system for pulmonary targeting by intravenous administration.Background The aim of this study is to investigate the relationship between metabolic syndrome (MetS) and bone fracture risk assessed by the Fracture Risk Algoritham (FRAX) tool in mid-aged Korean women. Methods Retrospectively, the study reviewed medical records of 1,975 female patients with or without MetS, who underwent routine medical checkups from 2010 to 2016 at Pusan National University Hospital. The MetS group included the patients who met diagnostic criteria for MetS based on the revised National Cholesterol Education Program reported in Adult Treatment Panel III (NCEP-ATPIII), and the control group was composed of those patients without MetS. Each of the patients was assessed through self-report questionnaires and individual interview with a health care provider. The FRAX tool was used for bone fracture risk. Results Univariate logistic regression analysis of various parameters for MetS showed increase in both FRAX1 and FRAX2 with odds ratio of 1.387 and 1.474 with P  less then  0.0001 each, respectively. Through Pearson's correlation coefficient study, correlation of patient's high-risk status of bone fracture with age was found. Multivariate analysis of such variables confirmed that only the age of patients was statistically significant in relationship to high-risk of fracture by FRAX tool. Conclusion MetS was not significantly associated with the patient's high-risk status of bone fracture analyzed by using FRAX; however, the absolute values of FRAX scores were increased in MetS patients (FRAX1 = 4.10 and FRAX2 = 0.40%) compared to their control group (FRAX1 = 3.20% and FRAX2 = 0.20%).

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