Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α-Synuclein Secondary Nucleation.

The high attrition rate in drug discovery pipelines is an especially pressing issue for Parkinson's disease, for which no disease-modifying drugs have yet been approved. Numerous clinical trials targeting α-synuclein aggregation have failed, at least in part due to the challenges in identifying potent compounds in preclinical investigations. To address this problem, we present a machine learning approach that combines generative modeling and reinforcement learning to identify small molecules that perturb the kinetics of aggregation in a manner that reduces the production of oligomeric species. Training data were obtained by an assay reporting on the degree of inhibition of secondary nucleation, which is the most important mechanism of α-synuclein oligomer production. This approach resulted in the identification of small molecules with high potency against secondary nucleation.

Maternal and infant outcomes of Syrian and Palestinian refugees, Lebanese and migrant women giving birth in a tertiary public hospital in Lebanon: a secondary analysis of an obstetric database.

OBJECTIVES: This study aims to assess whether the characteristics, management and outcomes of women varied between Syrian and Palestinian refugees, migrant women of other nationalities and Lebanese women giving birth at a public tertiary centre in Beirut, Lebanon. METHODS: This was a secondary data analysis of routinely collected data from the public Rafik Hariri University Hospital (RHUH) between January 2011 and July 2018. Data were extracted from medical notes using text mining machine learning methods. Nationality was categorised into Lebanese, Syrian, Palestinian and migrant women of other nationalities. The main outcomes were diabetes, pre-eclampsia, placenta accreta spectrum, hysterectomy, uterine rupture, blood transfusion, preterm birth and intrauterine fetal death. Logistic regression models estimated the association between nationality and maternal and infant outcomes, and these were presented using ORs and 95% CIs. RESULTS: 17 624 women gave birth at RHUH of whom 54.3% were Syrian, 39% Lebanese, 2.5% Palestinian and 4.2% migrant women of other nationalities. The majority of women had a caesarean section (73%) and 11% had a serious obstetric complication. Between 2011 and 2018, there was a decline in the use of primary caesarean section (caesarean section performed for the first time) from 7% to 4% of births (p<0.001). The odds of preeclampsia, placenta abruption and serious complications were significantly higher for Palestinian and migrant women of other nationalities compared to Lebanese women, but not for Syrian women. Very preterm birth was higher for Syrians (OR: 1.23, 95% CI: 1.08 to 1.40) and migrant women of other nationalities (OR: 1.51, 95% CI: 1.13 to 2.03) compared to Lebanese women. CONCLUSION: Syrian refugees in Lebanon had similar obstetric outcomes compared to the host population, except for very preterm birth. However, Palestinian women and migrant women of other nationalities appeared to have worse pregnancy complications than the Lebanese women. There should be better healthcare access and support for migrant populations to avoid severe complications of pregnancy.