Development of a 3-Step theory of suicide ontology to facilitate 3ST factor extraction from clinical progress notes.

OBJECTIVE: Suicide risk prediction algorithms at the Veterans Health Administration (VHA) do not include predictors based on the 3-Step Theory of suicide (3ST), which builds on hopelessness, psychological pain, connectedness, and capacity for suicide. These four factors are not available from structured fields in VHA electronic health records, but they are found in unstructured clinical text. An ontology and controlled vocabulary that maps psychosocial and behavioral terms to these factors does not exist. The objectives of this study were 1) to develop an ontology with a controlled vocabulary of terms that map onto classes that represent the 3ST factors as identified within electronic clinical progress notes, and 2) to determine the accuracy of automated extractions based on terms in the controlled vocabulary. METHODS: A team of four annotators did linguistic annotation of 30,000 clinical progress notes from 231 Veterans in VHA electronic health records who attempted suicide or who died by suicide for terms relating to the 3ST factors. Annotation involved manually assigning a label to words or phrases that indicated presence or absence of the factor (polarity). These words and phrases were entered into a controlled vocabulary that was then used by our computational system to tag 14 million clinical progress notes from Veterans who attempted or died by suicide after 2013. Tagged text was extracted and machine-labelled for presence or absence of the 3ST factors. Accuracy of these machine-labels was determined for 1000 randomly selected extractions for each factor against a ground truth created by our annotators. RESULTS: Linguistic annotation identified 8486 terms that related to 33 subclasses across the four factors and polarities. Precision of machine-labeled extractions ranged from 0.73 to 1.00 for most factor-polarity combinations, whereas recall was somewhat lower 0.65-0.91. CONCLUSION: The ontology that was developed consists of classes that represent each of the four 3ST factors, subclasses, relationships, and terms that map onto those classes which are stored in a controlled vocabulary (https://bioportal.bioontology.org/ontologies/THREE-ST). The use case that we present shows how scores based on clinical notes tagged for terms in the controlled vocabulary capture meaningful change in the 3ST factors during weeks preceding a suicidal event.

ß-Cyclodextrin Nanosponges Inclusion Compounds Associated with Silver Nanoparticles to Increase the Antimicrobial Activity of Quercetin.

This work aimed to synthesize and characterize a nanocarrier that consisted of a ternary system, namely ß-cyclodextrin-based nanosponge (NS) inclusion compounds (ICs) associated with silver nanoparticles (AgNPs) to increase the antimicrobial activity of quercetin (QRC). The nanosystem was developed to overcome the therapeutical limitations of QRC. The host-guest interaction between NSs and QRC was confirmed by field emission scanning electron microscopy (FE-SEM), X-ray powder diffraction (XRPD), thermogravimetric analysis (TGA), and proton nuclear magnetic resonance (1H-NMR). Moreover, the association of AgNPs with the NS-QRC was characterized using FE-SEM, energy-dispersive spectroscopy (EDS), transmission electron microscopy (TEM), dynamic light scattering (DLS), ζ-potential, and UV-Vis. Finally, the antimicrobial activity of the novel formulations was tested, which depicted that the complexation of QRC inside the supramolecular interstices of NSs increases the inhibitory effects against Escherichia coli ATCC25922, as compared to that observed in the free QRC. In addition, at the same concentrations used to generate an antibacterial effect, the NS-QRC system with AgNPs does not affect the metabolic activity of GES-1 cells. Therefore, these results suggest that the use of NSs associated with AgNPs resulted in an efficient strategy to improve the physicochemical features of QRC.

Changes in Food Environment Patterns in the Metropolitan Area of the Valley of Mexico, 2010-2020.

The concept of food environment refers to the opportunities; environments; and physical, economic, political, and socio-cultural conditions that frame the interaction of people with the food system and shape decisions about food acquisition and consumption. This study analyzes the relationships between the characteristics of urban environments and the availability of retail food through the evaluation of physical and financial access to food in the Metropolitan Area of the Valley of Mexico (MAVM) between 2010 and 2020. Using Geographic Information Systems (GISs), both physical access through network distance to economic food retail units and financial access through socioeconomic status at the block scale were evaluated. The network distance and socioeconomic status results were used as criteria for the spatially explicit classification of the MAVM into food deserts, oases, and swamps. Food deserts are the most abundant food environments but only increased in the third and fourth metropolitan contours. Swamps have increased throughout the city, related to the proliferation of convenience stores that have replaced grocery stores. This study contributes evidence at a local and regional scale required for the future urban planning of the MAVM and for public health and sustainability programs focusing on treating food-related diseases.