Surges in infections caused by respiratory pathogens have been documented in multiple settings after relaxation of pandemic restrictions. Antibodies to major antigens from respiratory syncytial virus and Group A Streptococcus waned significantly in a longitudinal adult cohort throughout the pandemic. This waning may have contributed to the pathogen-surges that followed.
View Article and Find Full Text PDFFunctional Near-Infrared Spectroscopy (fNIRS) holds transformative potential for research and clinical applications in neuroscience due to its non-invasive nature and adaptability to real-world settings. However, despite its promise, fNIRS signal quality is sensitive to individual differences in biophysical factors such as hair and skin characteristics, which can significantly impact the absorption and scattering of near-infrared light. If not properly addressed, these factors risk biasing fNIRS research by disproportionately affecting signal quality across diverse populations.
View Article and Find Full Text PDFFunctional near-infrared spectroscopy (fNIRS) technology has been steadily advancing since the first measurements of human brain activity over 30 years ago. Initially, efforts were focused on increasing the channel count of fNIRS systems and then to moving from sparse to high density arrays of sources and detectors, enhancing spatial resolution through overlapping measurements. Over the last ten years, there have been rapid developments in wearable fNIRS systems that place the light sources and detectors on the head as opposed to the original approach of using fiber optics to deliver the light between the hardware and the head.
View Article and Find Full Text PDFObjective: To assess risk factors associated with loss to follow up in patients referred for colposcopy after abnormal cervical cytology during pregnancy in a Southern safety net hospital population.
Methods: An urban colposcopy center was queried for patients referred for follow up of abnormal cervical cytology during pregnancy and the postpartum period. Patients were identified through a standardized referral code in the electronic medical record.