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How odor cues help to optimize learning during sleep in a real life-setting.

ABSTRACT: Effortless learning during sleep is everybody's dream. Several studies found that presenting odor cues during learning and selectively during slow wave sleep increases learning success. The current study extends previous research in three aspects to test for optimization and practical applicability of this cueing effect: We (1) performed a field study of vocabulary-learning in a regular school setting, (2) stimulated with odor cues during the whole night without sleep monitoring, and (3) applied the odor additionally as retrieval cue in a subsequent test. We found an odor cueing effect with comparable effect sizes (d between 0.6 and 1.2) as studies with sleep monitoring and selective cueing. Further, we observed some (non-significant) indication for a further performance benefit with additional cueing during the recall test. Our results replicate previous findings and provide important extensions: First, the odor effect also works outside the lab. Second, continuous cueing at night produces similar effect sizes as a study with selective cueing in specific sleep stages. Whether odor cueing during memory recall further increases memory performance hast to be shown in future studies. Overall, our results extend the knowledge on odor cueing effects and provide a realistic practical perspective on it.

SUBMITTER: Neumann F

PROVIDER: S-EPMC6985213 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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How odor cues help to optimize learning during sleep in a real life-setting.

Neumann Franziska F Oberhauser Vitus V Kornmeier Jürgen J

Scientific reports 20200127 1

Effortless learning during sleep is everybody's dream. Several studies found that presenting odor cues during learning and selectively during slow wave sleep increases learning success. The current study extends previous research in three aspects to test for optimization and practical applicability of this cueing effect: We (1) performed a field study of vocabulary-learning in a regular school setting, (2) stimulated with odor cues during the whole night without sleep monitoring, and (3) applied ...[more]

PMID: 31988352

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Project description:Aims/hypothesisSuboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. We aimed to test the hypothesis that poor sleep quality would be associated with greater overnight glycaemic variability.MethodsData were collected in the home setting from 20 adults (ten male and ten female participants) with type 1 diabetes who were current insulin pump users. Simultaneous assessments of objective sleep quality (Zmachine Insight+) and continuous glucose monitoring (CGM) were performed over multiple nights (up to 15 nights) in each participant. Due to the real-life nature of this study, the participants kept their usual CGM alerts for out-of-range glucose values. Sleep quality was categorised as 'good' or 'poor' using a composite of objective sleep features (i.e. sleep efficiency, wake after sleep onset and number of awakenings) based on the National Sleep Foundation's consensus criteria. Glycaemic variability was quantified using SD and CV of overnight glucose values based on overnight CGM profiles.ResultsA total of 170 nights were analysed. Overall, 86 (51%) nights were categorised as good sleep quality, and 84 (49%) nights were categorised as poor sleep quality. Using linear mixed-effects models, poor sleep quality was significantly associated with greater glycaemic variability as quantified by SD (coefficient: 0.39 [95% CI 0.10, 0.67], p = 0.009) and CV (coefficient: 4.35 [95% CI 0.8, 7.9], p = 0.02) of overnight glucose values, after accounting for age, sex, BMI and overnight insulin dose. There was large inter- and intra-individual variability in sleep and glycaemic characteristics. Both pooled and individual-level data revealed that the nights with poor sleep quality had larger SDs and CVs, and, conversely, the nights with good sleep quality had smaller SDs and CVs. No associations were found between sleep quality and time spent in the target glucose range, or above or below the target glucose range, where CGM alarms are most likely to occur.Conclusions/interpretationObjectively measured sleep quality is associated with overnight glycaemic variability in adults with type 1 diabetes. These findings highlight an important role of sleep quality in overnight glycaemic control in type 1 diabetes. They also provide a strong incentive to both patients and healthcare providers for considering sleep quality in personalised type 1 diabetes glycaemic management plans. Future studies should investigate the mechanisms linking sleep quality to glycaemic variability.

Project description:BackgroundThe prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting.Methods28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT.TB. We analyzed specimen types' effect on these assays' performance, determined the number of smears for diagnosing PTB, and evaluated the ability of these assays performed alone, or in combination, to diagnose PTB and nontuberculous mycobacteria (NTM) infections.ResultsSputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB+/Xpert+ and 6/7 of AFB+/Xpert- cases as PTB and NTM, respectively. Lastly, when combined with AFB/Xpert sequentially, T-SPOT showed limited roles in patients that were either AFB+ or Xpert+. However, T-SPOTMDC (manufacturer-defined cut-off) showed a high negative predicative value (99.1%) and suboptimal sensitivity (74.4%), and TBAg/PHA (ratio of Mycobacterium tuberculosis-specific antigens to phytohaemagglutinin spot-forming cells, which is a modified method calculating T-SPOT.TB assay results) ≥0.3 demonstrated a high specificity (95.7%) and a relatively low sensitivity (16.3%) in AFB-/Xpert- patients.ConclusionsConcurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOTMDC and TBAg/PHA ratios have a supplementary role for PTB diagnosis in AFB-/Xpert- patients (moderately ruling out PTB and ruling in PTB, respectively). Our findings may also inform policy makers' decisions regarding prevention and control of TB in a high burden setting.

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How odor cues help to optimize learning during sleep in a real life-setting.

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How odor cues help to optimize learning during sleep in a real life-setting.

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