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Preclinical PET studies of β-amyloid (Aβ) accumulation are of growing importance, but comparisons between research sites require standardized and optimized methods for quantitation. Therefore we aimed to evaluate systematically the 1) impact of an automated algorithm for spatial brain normalization, and 2) intensity scaling methods of different reference regions for Aβ-PET in a large dataset of transgenic mice. PS2APP mice in a six week longitudinal setting (N = 37) and another set of PS2APP mice at a histologically assessed narrow range of Aβ burden (N = 40) were investigated by [18F]-florbetaben PET. Manual spatial normalization by three readers at different training levels was performed prior to application of an automated brain spatial normalization and inter-reader agreement was assessed by Fleiss Kappa (κ). For this method the impact of templates at different pathology stages was investigated. Four different reference regions on brain uptake normalization were used to calculate frontal cortical standardized uptake value ratios (SUVRCTX/REF), relative to raw SUVCTX. Results were compared on the basis of longitudinal stability (Cohen’s d), and in reference to gold standard histopathological quantitation (Pearson’s R).Application of an automated brain spatial normalization resulted in nearly perfect agreement (all κ ≥ 0.99) between different readers, with constant or improved correlation with histology. Templates based on inappropriate pathology stage resulted in up to 2.9% systematic bias for SUVRCTX/REF. All SUVRCTX/REF methods performed better than SUVCTX both with regard to longitudinal stability (d ≥ 1.21 vs. d = 0.23) and histological gold standard agreement (R ≥ 0.66 vs. R ≥ 0.31). Voxel-wise analysis suggested a physiologically implausible longitudinal decrease of global mean scaling. The hindbrain white matter reference (Rmean = 0.75) was slightly superior to the brainstem (Rmean = 0.74) and the cerebellum (Rmean = 0.73). Automated brain normalization with reference region templates presents an excellent method to avoid the inter-reader variability in preclinical Aβ-PET scans. Intracerebral reference regions lacking Aβ pathology serve for precise longitudinal in vivo quantification of [18F]-florbetaben PET. Hindbrain white matter reference performed best when considering the composite of quality criteria.

Individuals may develop different attitudes on bioethics in general and reproductive ethics in particular, due to the effects of different sociocultural environments. Individuals' attitudes toward surrogacy are affected positively or negatively depending on religious and cultural environments. This study was conducted to determine and compare the attitudes of different religions toward surrogacy. This study is cross-sectional and collected from individuals living in Turkey, India, Iran, the Turkish Republic of Northern Cyprus, Madagascar, Nepal, Nigeria, Pakistan, Mexico, England, and Japan between May 2022 and December 2022. The study was conducted with individuals belonging to Islam, Christianity, Hinduism, Buddhism, and Atheism. The study was conducted with 1177 individuals from different religions who agreed to participate in the study by snowball sampling method. The introductory Information Form and "Attitude Questionnaire Toward Surrogacy" were used as data collection tools. R programming language 4.1.3 was used for regression analysis with machine learning approach and artificial neural networks, and SPSS-25 was used for other statistical analyses. There was a significant difference between the total mean score of the individuals' Attitudes toward Surrogacy Questionnaire and their religious beliefs (p < 0.05). When the results of the analysis of the regression model with the dummy variable, which was carried out with the aim of revealing the effects of religious belief on the attitude toward surrogacy, are examined, statistical estimates of the regression model show that the model is significant and usable F(4,1172) = 5.005, p = 0.001). It explains 1.7% of the total variance of the level of religious belief's attitude toward surrogacy. In the regression model, when the t-test results regarding the significance of the regression coefficient are examined, among the participants, it was determined that the mean score of those who believed in Islam (t =  - 3.827, p < 0.001) and those who believed in Christianity (t =  - 2.548, p < 0.001) was lower than the mean score of those who believed in Hinduism (Constant) (p < 0.05). Individuals' attitudes toward surrogacy differ according to their religion. The best performing algorithm for the prediction model was random forest (RF) regression. The contributions of the variables to the model were calculated with Shapley values (Shapley Additive Explanations (SHAP)). The SHAP values of the variables in the best performing model were examined to avoid bias in terms of comparison in the performance criterion. SHAP values (Shapley Additive Explanations) show the contribution or importance of each variable in the estimation of the model. It is determined that the most important variable that should be in the model to predict the Attitude Toward Surrogacy Survey variable is the Nationality variable. It is recommended that studies on attitudes toward surrogacy should be conducted by taking religious and cultural values into consideration., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)