Caffeine is the most widely consumed psychoactive substance in the world. It is readily available in coffee and other foods and beverages, and is used to mitigate sleepiness, enhance performance, and treat apnea in premature infants. This review systematically explores evidence from epidemiological studies and randomized controlled trials as to whether coffee and caffeine have deleterious effects on sleep. Caffeine typically prolonged sleep latency, reduced total sleep time and sleep efficiency, and worsened perceived sleep quality. Slow-wave sleep and electroencephalographic (EEG) slow-wave activity were typically reduced, whereas stage-1, wakefulness, and arousals were increased. Dose- and timing-response relationships were established. The sleep of older adults may be more sensitive to caffeine compared to younger adults. Pronounced individual differences are also present in young people, and genetic studies isolated functional polymorphisms of genes implicated in adenosine neurotransmission and metabolism contributing to individual sensitivity to sleep disruption by caffeine. Most studies were conducted in male adults of Western countries, which limits the generalizability of the findings. Given the importance of good sleep for general health and functioning, longitudinal investigations aimed at establishing possible causal relationships among coffee- and caffeine-induced changes in sleep quality and health development are warranted.

Background Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. Objective This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. Methods A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. Results Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non–rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. Conclusions We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.

The relatively new method of photoelectron spectroscopy has been used to measure the first and inner ionization potentials of benzene and four fluorine-substituted benzenes. Correlations between the higher levels in the fluorobenzenes are attempted using simple Hückel molecular orbital (HMO) theory and the assumption that the second level in benzene is ir.

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Rat parvalbumin (PV) and oncomodulin (OM) display considerable sequence similarity and structural similarity, but differ in the affinity and selectivity of metal binding to their CD site, a Ca" /Mgz+-mixed site in PV and a Ca2+-specific site in OM. In an attempt to identify the structural basis for these differences, mutations were introduced in the previously generated [W102]PV mutant, which contains a unique tryptophan as a conformational-sensitive fluorescent probe inside the hydrophobic core. In the present report, we substituted selected amino acid residues in the CD site of PV by those present at identical positions in OM.