Health care disparities, CBD, and bat ears.
All bats—about 1,440 species, most of which use echolocation—belong to one of two genetic lineages: Yinpterochiroptera (Yin) and Yangochiroptera (Yang). Scientists have speculated that the branches use echolocation in different ways, and in the February 17 issue of Nature, UChicago biologist Zhe-Xi Luo and lead author Benjamin Sulser, SB’16, present anatomical evidence that Yin and Yang bats do “see” the world differently. Using CT scans, the team discovered that Yin and Yang bats have distinct architecture of the inner ear, where nerve cells carry sound to the brain. In Yin bats, as in most other mammals, nerves run through a bony canal, which is porous like a coffee filter. That canal in Yang bats, if not completely absent, has larger holes, like a colander. This more flexible configuration may drive evolution, explaining Yang diversity in behavior, habitat, and diet—and why roughly 80 percent of bats that echolocate are Yang bats.
In addition to vaccines, COVID-19 treatments are vital to managing the pandemic. A study published February 23 in Science Advances presents evidence that cannabidiol (CBD) can inhibit SARS-CoV-2 infection. Researchers including Marsha Rosner, the Charles B. Huggins Professor in the Ben May Department of Cancer Research, treated human lung cells with CBD before exposing them to SARS-CoV-2. They found that with higher concentrations of CBD, the virus could enter the cells but replication was suppressed. The team also treated mice with CBD for a week prior to infection and found less virus in their noses and lungs. In a parallel analysis, the researchers found that patients with epilepsy who took medical CBD—of far higher purity and concentration than most commercially available products—tested positive for COVID-19 at substantially lower rates, further supporting the case for human clinical trials.
The language used in medical charts can expose health care providers’ unconscious biases. A study published in the February Health Affairs reveals that, even after controlling for socioeconomic factors and health characteristics, Black patients were 2.54 times as likely as White patients to have at least one negative descriptor in their records. A UChicago Medicine team used machine learning to search health records of more than 18,000 adult patients, looking for words such as “noncompliant,” “aggressive,” “combative,” “defensive,” and “hysterical.” The team used natural language processing techniques to determine when these terms were used in the context of describing patients or their behavior. The study also found higher rates of negative language for people on Medicare or Medicaid and unmarried patients. The terminology health care providers use can exacerbate existing health care disparities; the researchers hope to encourage them to reconsider how they talk—and think—about patients.