Monitoring sound and light continuously in an intensive care unit patient room: A pilot study.

PURPOSE: To determine the feasibility of continuous recording of sound and light in the intensive care unit (ICU). MATERIALS AND METHODS: Four 1-hour baseline scenarios in an empty ICU patient room by day and night (doors open or closed and maximal or minimal lighting) and two daytime scenarios simulating a stable and unstable patient (quiet or loud devices and staff) were conducted. Sound and light levels were continuously recorded using a commercially available multisensor monitor and transmitted via the hospital's network to a cloud-based data storage and management system. RESULTS: The empty ICU room was loud with similar mean sound levels of 45 to 46 dBA for the day and night simulations. Mean levels for maximal lighting during day and night ranged from 1306 to 1812 lux and mean levels for minimum lighting were 1 to 3 lux. The mean sound levels for the stable and unstable patient simulations were 61 and 81 dBA, respectively. The mean light levels were 349 lux for the stable patient and 1947 lux for the unstable patient. CONCLUSIONS: Combined sound and light can be continuously and easily monitored in the ICU setting. Incorporating sound and light monitors in ICU rooms may promote an enhanced patient- and staff-centered healing environment.

Small open reading frames: current prediction techniques and future prospect.

Evidence is accumulating that small open reading frames (sORF, <100 codons) play key roles in many important biological processes. Yet, they are generally ignored in gene annotation despite they are far more abundant than the genes with more than 100 codons. Here, we demonstrate that popular homolog search and codon-index techniques perform poorly for small genes relative to that for larger genes, while a method dedicated to sORF discovery has a similar level of accuracy as homology search. The result is largely due to the small dataset of experimentally verified sORF available for homology search and for training ab initio techniques. It highlights the urgent need for both experimental and computational studies in order to further advance the accuracy of sORF prediction.