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Abstract The hypothalamus plays an important role in aging, but it remains unclear regarding the underlying epigenetics and whether this hypothalamic basis can help address aging-related diseases. Here, by comparing mouse hypothalamus with two other limbic system components, we show that the hypothalamus is characterized by distinctively high-level DNA methylation during young age and by the distinct dynamics of DNA methylation and demethylation when approaching middle age. On the other hand, age-related DNA methylation in these limbic system components commonly and sensitively applies to genes in hypothalamic regulatory pathways, notably oxytocin (OXT) and gonadotropin-releasing hormone (GnRH) pathways. Middle age is associated with transcriptional declines of genes which encode OXT, GnRH and signaling components, which similarly occur in an Alzheimer’s disease (AD)-like model. Therapeutically, OXT-GnRH combination is substantially more effective than individual peptides in treating AD-like disorders in male 5×FAD model. In conclusion, the hypothalamus is important for modeling age-related DNA methylation and developing hypothalamic strategies to combat AD.

Abstract This paper proposes a new method for predicting the stage of osteoporosis by estimating bone-density parameters using an ultrasonic-bone densitometer. Using the developed ultrasonic bone densitometer, the ultrasonic signal passing through the phalanx of the finger was measured, and the measured signal was preprocessed to generate input data for parameter estimation. The Nakagami probability-density function was used for modeling this data, and optimal bone-density parameters were estimated using an optimization problem – to predict the stage of osteoporosis. The proposed method was verified through in vitro and in vivo experiments. In phantom experiments, cubes with different materials (ABS plastic, PLA plastic, Nylon) were used, and each cube had a different density through internal density so that it could mimic bones. The experiments were conducted using them and the results were compared. The experimental results confirmed that there was a correlation between the density and estimated parameters for all three materials. In the in vivo experiment, the osteoporosis stages were classified as normal, osteopenia, and osteoporosis, and the bone-density parameters were estimated for the participants of each group. Thus, a basis for predicting the stage of osteoporosis was created, and data from new participants were collected and verified as test data. As a result, normal and abnormal groups (osteopenia and osteoporosis) were predicted.