Estimation of tissue blood flow from hyperthermia treatment data

During hyperthermia treatment of patients the delivered heat and the temperatures at several points in the tissue are often measured and recorded. These data contain information about thermal tissue parameters. A method for extracting this information, i.e. estimating the tissue parameters—in particular the blood perfusion rate—is described. The method applies a system identification technique, adjusting the unknown parameters in a thermal tissue model, until the predicted model output (temperature) coincides well with the measured temperature. Data from a number of patient treatments have been used to test the method, and although the accuracy of the method remains to be established conclusively it appears to give a good estimate of the model parameter representing blood flow. The obvious advantage of the method is that it requires no special transducers or experiments. The weak aspect is that it depends on the correctness of a thermal model of the perfused tissue.     

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data

Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance.     

优化教学方式:充分发挥教学对象的主观能动性

目的:通过寻求优化教学方式,以期实现更高效、更具有趣味性及更丰富的医学高等教育方式。方法:研究选择南京医科大学护理专业学生为研究对象,选择"营养学"为实验课程展开探索研究,采用新型教学方式。结果:教学实验组期末考试成绩高于其他平行班级;课堂表现优异者期末考试成绩亦较其他学生高。结论:通过丰富教学方法,有利于教学对象更好的理解知识,提高考试成绩;同时,参与度及配合度、完成度较高的学生能更好地掌握相关知识。     

Higher levels of greenness and biodiversity associate with greater subjective wellbeing in adults living in Melbourne,Australia

Natural environments may be important for subjective wellbeing, yet evidence is sparse and measures of nature are unspecific. We used linear regression models to investigate the relationship between greenness, biodiversity and blue space and subjective wellbeing in 4,912 adults living in metropolitan Melbourne, Australia. Greenness (overall, private and public) and biodiversity associated with subjective wellbeing. In particular, we highlight the importance of the private greenness-subjective wellbeing association. Our work has implications for urban policy and planning in the context of increased urban densification.     

Asymptotic accuracy of Bayesian estimation for a single latent variable

In data science and machine learning, hierarchical parametric models, such as mixture models, are often used. They contain two kinds of variables: observable variables, which represent the parts of the data that can be directly measured, and latent variables, which represent the underlying processes that generate the data. Although there has been an increase in research on the estimation accuracy for observable variables, the theoretical analysis of estimating latent variables has not been thoroughly investigated. In a previous study, we determined the accuracy of a Bayes estimation for the joint probability of the latent variables in a dataset, and we proved that the Bayes method is asymptotically more accurate than the maximum-likelihood method. However, the accuracy of the Bayes estimation for a single latent variable remains unknown. In the present paper, we derive the asymptotic expansions of the error functions, which are defined by the Kullback–Leibler divergence, for two types of single-variable estimations when the statistical regularity is satisfied. Our results indicate that the accuracies of the Bayes and maximum-likelihood methods are asymptotically equivalent and clarify that the Bayes method is only advantageous for multivariable estimations.     

About consistency of Solid's solubility data in supercritical CO2 and some thermodynamic properties estimation

In chemical industry, usual solvents are being replaced by supercritical fluids. Last few years, extraction by these environmentally benign solvents has had much attention and now is considered as the newest separation technology. However, developing new applications and improving existing ones is based on a set of thermodynamic and physical properties of pure solutes related to phase equilibrium for which experimental values cannot be found and consequently, there is an increase need for accurate estimates of these properties. This paper is interested firstly to a thermodynamic property which is the Krichevskii parameter and secondly to a thermophysical one which is the sublimation pressure. First parameter is considered as a governor of thermodynamic properties in binary dilute mixtures near the solvent's critical point and can be calculated from some rigorous relationships and in this paper a review and a new way for its estimation are presented based on consistency of solid's solubility data in supercritical fluids and dilute solution theory. Second parameter is considered as the predominant influencer on solubility in supercritical fluids and unavailability of its experimental values presents an obstacle to thermodynamic modeling of solubility data. For this reason and as a second step, in this paper we present a new manner for its estimation. Obtained results are relevant, very promising for each considered property and the methodology can be applied for other solutes with more complex structures as Pharmaceuticals (antibiotics, drugs, anti-inflammatories …), polycyclic aromatic hydrocarbons (PAHC) and dyestuffs.     

Prediction of the length of the femur from its fragments in a Sri Lankan population

ABSTRACT

In many forensic circumstances, the femur is fragmented due to decomposition and mutilation, thus necessitating development and application of regression equations to estimate the length of the femur from its fragments. In this study, regression equations were derived for the prediction of the femoral length, utilizing 11 standard femoral measurements (maximum length of femur, epicondylar breadth, vertical head diameter, transverse head diameter, vertical neck diameter, transverse neck diameter, neck length, subtrochanteric anterior–posterior diameter, subtrochanteric transverse diameter, mid-shaft anterior–posterior diameter and mid-shaft transverse diameter) obtained from 86 femora belonging to a contemporary Sri Lankan population. Univariate regression equations with moderate to high correlations (0.226 to 0.714) were formulated for the estimation of the maximum femoral length from the measurements of fragments of the femur. Of the single variables, the transverse neck diameter emerged as the best predictor (r = 0.714, SEE = 18.6596) of the maximum length of the femur. The multiple regression equations using a combination of variables yielded higher correlations (0.774–0.857) with lower error estimates (14.18–16.96). The regression equations presented in this study can be used to estimate the length of the femur of unknown, mutilated and dismembered human skeletal remains with considerable accuracy.     

A randomized controlled trial of two simple mind-body programs,Kirtan Kriya meditation and music listening,for adults with subjective cognitive decline: Feasibility and acceptability

Purpose of the studyIn this randomized controlled trial (RCT), we assessed the feasibility and acceptability of two simple home-based relaxation programs in adults experiencing subjective cognitive decline, a strong predictor of Alzheimer's disease.Design and methodsSixty participants were randomized to a beginner Kirtan Kriya meditation (KK) program or a music listening (ML) program. Participants were asked to practice 12 min daily for the first 12 weeks, then as often as they liked for the following 3 months. Participants underwent assessments at baseline, 12 weeks, and 6 months to evaluate changes in key outcomes. Feasibility and acceptability were evaluated by measuring recruitment and retention rates, assessment visit attendance, practice adherence, and treatment expectancy; exit questionnaires completed at 12 weeks and 6 months provided additional data regarding participant experience with the study, perceived barriers to and facilitators of practice, reasons for drop-out, and views regarding the assigned intervention.ResultsFifty-three participants (88%) completed the 6 month study. Adherence in both groups was excellent, with participants completing 93% (91% KK, 94% ML) of sessions on average in the first 12 weeks, and 71% (68% KK, 74% ML) during the 3 month, practice-optional, follow-up period. At week 12, over 80% of participants indicated they were likely to continue practicing following study completion. Responses to both structured and open-ended exit questionnaire items also suggested high satisfaction with both programs.ConclusionsFindings of this RCT of a beginner meditation practice and a simple ML program suggest that both programs were well accepted and the practices are feasible in adults with early memory loss.     

Is Subjective Outcome Evaluation Related to Objective Outcome Evaluation? Insights from a Longitudinal Study in Hong Kong

Study ObjectivesEmpirical studies investigating the inter-relationships among subjective outcomes and objective outcomes are sparse in the scientific literature. This study examined the relationship between these 2 forms of outcome evaluation data in Chinese adolescents, utilizing longitudinal data.DesignIn Wave 3 and Wave 4 of a randomized group trial, 2,784 Chinese secondary school students responded to the Chinese Positive Youth Development Scale (CPYDS) assessing objective outcome at pretest (Wave 3) and posttest (Wave 4). Students in the experimental schools also responded to a measure of client satisfaction assessing the subjective outcome of a positive youth development program at posttest (Wave 4).ResultsSubjective outcome evaluation measures (eg, process, program, and effectiveness) at Wave 3 were significantly correlated with CPYDS scores at Wave 4 and difference scores. Subjective outcome evaluation measures also predicted changes in the objective outcome evaluation measures scores across time.ConclusionsThe present findings replicated the previous findings that subjective outcome and objective outcome evaluation findings were intimately related, and subjective outcome measures predicted posttest measures and their changes over time. The present study suggests that subjective outcome evaluation findings may yield useful information regarding program effectiveness in youth work settings.