Relationship between Brazilian airline pilot errors and time of day

Flight safety is one of the most important and frequently discussed issues in aviation. Recent accident inquiries have raised questions as to how the work of flight crews is organized and the extent to which these conditions may have been contributing factors to accidents. Fatigue is based on physiologic limitations, which are reflected in performance deficits. The purpose of the present study was to provide an analysis of the periods of the day in which pilots working for a commercial airline presented major errors. Errors made by 515 captains and 472 copilots were analyzed using data from flight operation quality assurance systems. To analyze the times of day (shifts) during which incidents occurred, we divided the light-dark cycle (24:00) in four periods: morning, afternoon, night, and early morning. The differences of risk during the day were reported as the ratio of morning to afternoon, morning to night and morning to early morning error rates. For the purposes of this research, level 3 events alone were taken into account, since these were the most serious in which company operational limits were exceeded or when established procedures were not followed. According to airline flight schedules, 35% of flights take place in the morning period, 32% in the afternoon, 26% at night, and 7% in the early morning. Data showed that the risk of errors increased by almost 50% in the early morning relative to the morning period (ratio of 1:1.46). For the period of the afternoon, the ratio was 1:1.04 and for the night a ratio of 1:1.05 was found. These results showed that the period of the early morning represented a greater risk of attention problems and fatigue.

Sleep, ageing and night work

Studies have shown that the frequency or worsening of sleep disorders tends to increase with age and that the ability to perform circadian adjustments tends to decrease in individuals who work the night shift. This condition can cause consequences such as excessive sleepiness, which are often a factor in accidents that occur at work. The present study investigated the effects of age on the daytime and nighttime sleep patterns using polysomnography (PSG) of long-haul bus drivers working fixed night or day shifts. A total of 124 drivers, free of sleep disorders and grouped according to age (<45 years, N = 85, and ≥45 years, N = 39) and PSG timing (daytime (D) PSG, N = 60; nighttime (N) PSG, N = 64) participated in the study. We observed a significant effect of bedtime (D vs N) and found that the length of daytime sleep was shorter [D: <45 years (336.10 ± 73.75 min) vs N: <45 years (398 ± 78.79 min) and D: ≥45 years (346.57 ± 43.17 min) vs N: ≥45 years (386.44 ± 52.92 min); P ≤ 0.05]. Daytime sleep was less efficient compared to nighttime sleep [D: <45 years (78.86 ± 13.30%) vs N: <45 years (86.45 ± 9.77%) and D: ≥45 years (79.89 ± 9.45%) and N: ≥45 years (83.13 ± 9.13%); P ≤ 0.05]. An effect of age was observed for rapid eye movement sleep [D: <45 years (18.05 ± 6.12%) vs D: ≥45 years (15.48 ± 7.11%) and N: <45 years (23.88 ± 6.75%) vs N: ≥45 years (20.77 ± 5.64%); P ≤ 0.05], which was greater in younger drivers. These findings are inconsistent with the notion that older night workers are more adversely affected than younger night workers by the challenge of attempting to rest during the day.

A link between sleep loss, glucose metabolism and adipokines

The present review evaluates the role of sleep and its alteration in triggering problems of glucose metabolism and the possible involvement of adipokines in this process. A reduction in the amount of time spent sleeping has become an endemic condition in modern society, and a search of the current literature has found important associations between sleep loss and alterations of nutritional and metabolic contexts. Studies suggest that sleep loss is associated with problems in glucose metabolism and a higher risk for the development of insulin resistance and type 2 diabetes mellitus. The mechanism involved may be associated with the decreased efficacy of regulation of the hypothalamus-pituitary-adrenal axis by negative feedback mechanisms in sleep-deprivation conditions. In addition, changes in the circadian pattern of growth hormone (GH) secretion might also contribute to the alterations in glucose regulation observed during sleep loss. On the other hand, sleep deprivation stress affects adipokines - increasing tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and decreasing leptin and adiponectin -, thus establishing a possible association between sleep-debt, adipokines and glucose metabolism. Thus, a modified release of adipokines resulting from sleep deprivation could lead to a chronic sub-inflammatory state that could play a central role in the development of insulin resistance and type 2 diabetes mellitus. Further studies are necessary to investigate the role of sleep loss in adipokine release and its relationship with glucose metabolism.

The expression of melanopsin and clock genes in Xenopus laevis melanophores and their modulation by melatonin

Vertebrates have a central clock and also several peripheral clocks. Light responses might result from the integration of light signals by these clocks. The dermal melanophores of Xenopus laevis have a photoreceptor molecule denominated melanopsin (OPN4x). The mechanisms of the circadian clock involve positive and negative feedback. We hypothesize that these dermal melanophores also present peripheral clock characteristics. Using quantitative PCR, we analyzed the pattern of temporal expression of Opn4x and the clock genes Per1, Per2, Bmal1, and Clock in these cells, subjected to a 14-h light:10-h dark (14L:10D) regime or constant darkness (DD). Also, in view of the physiological role of melatonin in the dermal melanophores of X. laevis, we determined whether melatonin modulates the expression of these clock genes. These genes show a time-dependent expression pattern when these cells are exposed to 14L:10D, which differs from the pattern observed under DD. Cells kept in DD for 5 days exhibited overall increased mRNA expression for Opn4x and Clock, and a lower expression for Per1, Per2, and Bmal1. When the cells were kept in DD for 5 days and treated with melatonin for 1 h, 24 h before extraction, the mRNA levels tended to decrease for Opn4x and Clock, did not change for Bmal1, and increased for Per1 and Per2 at different Zeitgeber times (ZT). Although these data are limited to one-day data collection, and therefore preliminary, we suggest that the dermal melanophores of X. laevis might have some characteristics of a peripheral clock, and that melatonin modulates, to a certain extent, melanopsin and clock gene expression.

Long-term correlation of the electrocorticogram as a bioindicator of brain exposure to ionizing radiation

Understanding the effects of radiation and its possible influence on the nervous system are of great clinical interest. However, there have been few electrophysiological studies on brain activity after exposure to ionizing radiation (IR). A new methodological approach regarding the assessment of the possible effects of IR on brain activity is the use of linear and nonlinear mathematical methods in the analysis of complex time series, such as brain oscillations measured using the electrocorticogram (ECoG). The objective of this study was to use linear and nonlinear mathematical methods as biomarkers of gamma radiation regarding cortical electrical activity. Adult Wistar rats were divided into 3 groups: 1 control and 2 irradiated groups, evaluated at 24 h (IR24) and 90 days (IR90) after exposure to 18 Gy of gamma radiation from a cobalt-60 radiotherapy source. The ECoG was analyzed using power spectrum methods for the calculation of the power of delta, theta, alpha and beta rhythms and by means of the α-exponent of the detrended fluctuation analysis (DFA). Using both mathematical methods it was possible to identify changes in the ECoG, and to identify significant changes in the pattern of the recording at 24 h after irradiation. Some of these changes were persistent at 90 days after exposure to IR. In particular, the theta wave using the two methods showed higher sensitivity than other waves, suggesting that it is a possible biomarker of exposure to IR.