FBD were more common and severe among rotating shift nurses. The FBD symptom score was positively and independently correlated with the sleep disturbance score, suggesting that poor sleep might be associated with increased FBD symptoms in rotating shift nurses.

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Ventilator-associated pneumonia (VAP) is a common complication and cause of death in neonates on mechanical ventilation. However, it is difficult to define the causes of VAP. To understand the causes of VAP, we undertook a prospective study based on the diversity of the microflora in VAP. The experimental group consisted of newborns who suffered from respiratory distress syndrome (RDS) and VAP, while the control group suffered from RDS without VAP. Sputa were collected within 1, 3, and 5 days of ventilation and were divided into six groups. DNA was extracted from the samples, and the 16S rDNA was PCR amplified, separated using denaturing gradient gel electrophoresis (DGGE), cloned and sequenced. The resulting sequences were compared using BLAST. The DGGE pictures were measured, and the richness, Shannon-Wiener index, and cluster maps were analyzed. No differences were found regarding the constituent ratio of any genus between the Non-VAP and VAP group within 1 day after intubation. After 1 to 3 days, the constituent ratios of Klebsiella sp., Acinetobacter sp., and Streptococcus sp. in the VAP group were higher than those in the Non-VAP group, and the ratios of Serratia sp. and Achromobacter sp. were lower. After 3 to 5 days, the ratios of Klebsiella sp., Acinetobacter sp., Serratia sp., and Achromobacter sp. were lower than those in the Non-VAP group. The richness and Shannon-Wiener index of the Non-VAP group were higher than those of the VAP group from 1 to 3 days after intubation, while no differences were found within 1 day and from 3 to 5 days. We conclude that during the first three days of intubation, the microflora diversity in the lower respiratory tract was reduced due to VAP, and the greater constituent ratios of Klebsiella sp., Acinetobacter sp., and Streptococcus sp. in the sputum may be indicators of VAP.

SUMMARYHumans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance (UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation (TSD) and (ii) chronic sleep restriction (CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over nonindividualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions. IN TROD UCTI ONInsufficient sleep impairs alertness and neurobehavioural performance. Results from Van Dongen et al. (2004) and Rupp et al. (2012) showed that substantial interindividual variability exists with regard to response to sleep loss. More importantly, both studies also showed that this response was trait-like. Van Dongen et al. (2004) evaluated the same 21 individuals under three separate total sleep deprivation (TSD) challenges of 36 h each and observed that the neurobehavioural deficits resulting from sleep loss were stable within individuals across the three challenges. Rupp et al. (2012) showed that an individual's neurobehavioural response to 64 h of TSD was correlated positively with that individual's response to chronic sleep restriction (CSR) [seven consecutive days of 3 h nightly time in bed (TIB)]. In both studies, they quantified individual response to sleep loss by averaging neurobehavioural performance [i.e. psychomotor vigilance task (PVT) data] over the last 12-24 h of the sleep-loss condition, and used the intraclass correlation coefficient (ICC) to assess the extent to which an individual's vulnerability rank among a group of individuals was preserved across sleep-loss conditions. Large ICC values observed in the two studies suggest a high degree of trait preservation. In other words, performance on the last day of a particular sleep-loss challenge can predict accurately the relative rank of an individual for a subsequent sleep-loss challenge. However, such analyses provide little or no information regarding the temporal dynamics of an individual's performance, which is critical in operational settings.In the past, many biomathematical m...