Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial.

Context: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge.

Objectives: To assess the effectiveness on clinical outcomes of an artificial intelligence (AI)/machine learning (ML) decision support tool for predicting patient need for palliative care services in the hospital.

Methods: The study design was a pragmatic, cluster-randomized, stepped-wedge clinical trial in 12 nursing units at two hospitals over a 15-month period between August 19, 2019, and November 17, 2020.

Performance of Expanded Newborn Screening in Norway Supported by Post-Analytical Bioinformatics Tools and Rapid Second-Tier DNA Analyses.

In 2012, the Norwegian newborn screening program (NBS) was expanded (eNBS) from screening for two diseases to that for 23 diseases (20 inborn errors of metabolism, IEMs) and again in 2018, to include a total of 25 conditions (21 IEMs). Between 1 March 2012 and 29 February 2020, 461,369 newborns were screened for 20 IEMs in addition to phenylketonuria (PKU). Excluding PKU, there were 75 true-positive (TP) (1:6151) and 107 (1:4311) false-positive IEM cases.

Dynamic nuclear polarization by electrical spin injection in ferromagnet-semiconductor heterostructures.

Electrical spin injection from Fe into AlxGa1-xAs quantum well heterostructures is demonstrated in small (<500 Oe) in-plane magnetic fields. The measurement is sensitive only to the component of the spin that precesses about the internal magnetic field in the semiconductor. This field is much larger than the applied field and depends strongly on the injection current density.

Follow-up of protein release from Pseudoplusia includens hemocytes: a first step toward identification of factors mediating encapsulation in insects.

Hemocyte types involved in encapsulation were characterized using monoclonal antibodies (mAbs). This approach revealed that four hemocyte types in Pseudoplusia includens could be classified into two antigenically distinct cell lines. The first line comprised granulocytes (GR) and spherulocytes (SP) and the second line comprised plasmatocytes (PL) and oenocytoids (OE).