With the global pandemic driving the adoption of digital health, understanding the predictors or determinants of digital health usage and information sharing gives an opportunity to advocate for broader adoption. We examined the prevalence and predictors of digital health usage and information-sharing behaviors among American adults. Data were from the Health Information National Trends Survey 5 Cycle 4. More than two-thirds used a digital resource for health-related activities (eg, to check test results). About 81% were willing to share their digital data with their provider, 75% with family, and 58% with friends. Only 14% shared health information on social media. Gender, education, device types, and performance expectancy of digital health were common factors associated with both digital health usage and information-sharing behaviors. Other predictors included rurality, patient portal access, income, and having a chronic disease. Of note, we found that Asian American Pacific Islanders, compared with Whites, were less likely to share information with providers. Performance expectancy was a significant determinant of information sharing. Those diagnosed with diabetes were 4% less likely to share information with their providers. With the growing digital divide, there is a need to advocate for more usable and accessible digital health to assist with person-centered care.

Hypoxia causes a series of responses supporting cells to survive in harsh environments. Substantial post-transcriptional and translational regulation during hypoxia has been observed. However, detailed regulatory mechanism in response to hypoxia is still far from complete. RNA m⁶A modification has been proven to govern the life cycle of RNAs. Here, we reported that total m⁶A level of mRNAs was decreased during hypoxia, which might be mediated by the induction of m⁶A eraser, ALKBH5. Meanwhile, expression levels of most YTH family members of m⁶A readers were systematically down-regulated. Transcriptome-wide analysis of m⁶A revealed a drastic reprogramming of m⁶A epitranscriptome during cellular hypoxia. Integration of m⁶A epitranscriptome with either RNA-seq based transcriptome analysis or mass spectrometry (LC-MS/MS) based proteome analysis of cells upon hypoxic stress revealed that reprogramming of m⁶A epitranscriptome reshaped the transcriptome and proteome, thereby supporting efficient generation of energy for adaption to hypoxia. Moreover, ATP production was blocked when silencing an m⁶A eraser, ALKBH5, under hypoxic condition, demonstrating that m⁶A pathway is an important regulator during hypoxic response. Collectively, our studies indicate that crosstalk between m⁶A and HIF1 pathway is essential for cellular response to hypoxia, providing insights into the underlying molecular mechanisms during hypoxia.

We describe a new approach for infectious disease surveillance that facilitates rapid identification of known and emerging pathogens. The process uses broad-range polymerase chain reaction (PCR) to amplify nucleic acid targets from large groupings of organisms, electrospray ionization mass spectrometry for accurate mass measurements of PCR products, and base composition signature analysis to identify organisms in a sample. We demonstrate this principle by using 14 isolates of 9 diverse Coronavirus spp., including the severe acute respiratory syndrome-associated coronavirus (SARS-CoV). We show that this method could identify and distinguish between SARS and other known CoV, including the human CoV 229E and OC43, individually and in a mixture of all 3 human viruses. The sensitivity of detection, measured by using titered SARS-CoV spiked into human serum, was approximate, equals1 PFU/mL. This approach, applicable to the surveillance of bacterial, viral, fungal, or protozoal pathogens, is capable of automated analysis of >900 PCR reactions per day.