Machine learning in the prediction of human wellbeing.

Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine Learning (ML) algorithms to provide a better understanding of respondents' self-reported wellbeing.

Proportion of foetal and placental implantation abnormalities in Madagascar: A cross-sectional study of 35,919 women at public-sector primary healthcare facilities in central and southern Madagascar, 2017-2020.

Background: Like other countries in sub-Saharan Africa, Madagascar has a high burden of maternal and neonatal mortality. However, as the proportion of foetal and placental abnormalities among the Malagasy population is unknown, strategies aimed at reducing maternal and neonatal mortality are challenging to define and implement.

Methods: We conducted a multi-year, cross-sectional study using secondary NGO data on obstetric ultrasound, including patient records of all pregnant women who received an obstetric ultrasound screening between July 1st, 2017, and September 30th, 2020, at 62 public-sector primary care facilities in urban and rural regions of Madagascar.

Multitarget ligands that comprise opioid/nonopioid pharmacophores for pain management: Current state of the science.

Chronic pain, which affects more than one-third of the world's population, represents one of the greatest medical challenges of the 21st century, yet its effective management remains sub-optimal. The 'gold standard' for the treatment of moderate to severe pain consists of opioid ligands, such as morphine and fentanyl, that target the µ-opioid receptor (MOP). Paradoxically, these opioids also cause serious side effects, including constipation, respiratory depression, tolerance, and addiction.

Design, Synthesis, and Characterization of Proteolytically-Stable Opioid-Neurotensin Hybrid Peptidomimetics.

Linking an opioid to a nonopioid pharmacophore represents a promising approach for reducing opioid-induced side effects during pain management. Herein, we describe the optimization of the previously reported opioid-neurotensin hybrids (OPNT-hybrids), & , containing the μ-/δ-opioid agonist H-Dmt-d-Arg-Aba-β-Ala-NH and NT(8-13) analogs optimized for NTS2 affinity. In the present work, the constrained dipeptide Aba-β-Ala was modified to investigate the optimal linker length between the two pharmacophores, as well as the effect of expanding the aromatic moiety within constrained dipeptide analogs, via the inclusion of a naphthyl moiety.