Subjective sleep more predictive of global cognitive function than objective sleep in older adults: A specification curve analysis.

OBJECTIVES: Sleep is associated with cognitive function in older adults. In the current study, we examined this relationship from subjective and objective perspectives, and determined the robustness and dimensional specificity of the associations using a comprehensive modelling approach. METHODS: Multiple dimensions of subjective (sleep quality and daytime sleepiness) and objective sleep (sleep stages, sleep parameters, sleep spindles, and slow oscillations), as well as subjectively reported and objectively measured cognitive function were collected from 55 older adults. Specification curve analysis was used to examine the robustness of correlations for the effects of sleep on cognitive function. RESULTS: Robust associations were found between sleep and objectively measured cognitive function, but not with subjective cognitive complaints. In addition, subjective sleep showed robust and consistent associations with global cognitive function, whereas objective sleep showed a more domain-specific association with episodic memory. Specifically, subjective sleep quality and daytime sleepiness correlated with global cognitive function, and objective sleep parameters correlated with episodic memory. CONCLUSIONS: Overall, associations between sleep and cognitive function in older adults depend on how they are measured and which specific dimensions of sleep and domains of cognitive function are considered. It highlights the importance of focusing on specific associations to ameliorate the detrimental effects of sleep disturbance on cognitive function in later life.

The influence of cognitive activity on subsequent daytime nap: A deep neural network model based on sleep spindles.

OBJECTIVES: Understanding the influence of cognitive activity on subsequent sleep has both theoretical and applied implications. This study aims to investigate the effect of pre-sleep cognitive activity, in the context of avoiding emotional interference, on macro-sleep and sleep spindles. METHODS: In a within-subjects design, participants' sleep electroencephalography was collected in both the with and without pre-sleep cognitive activity conditions. Subsequent macro-sleep (i.e., sleep stage distribution and sleep parameters) and spindle characteristics (i.e., density, amplitude, duration, and frequency) were analyzed. In addition, a novel machine learning framework (i.e., deep neural network, DNN) was used to discriminate between cognitive activity and control conditions. RESULTS: There were no significant differences in macro-sleep and sleep spindles between the cognitive activity and control conditions. Spindles-based DNN models achieved over 96% accuracy in differentiating between the two conditions, with fast spindles performing better than full-range and slow spindles. CONCLUSIONS: These results suggest a weak but positive effect of pre-sleep cognitive activity on subsequent sleep. It sheds light on a possible low-cost and easily accessible sleep intervention strategy for clinical and educational purposes.

Relationship between self-reported sleep and cognitive function: a specification curve analysis.

The relationship between self-reported sleep and cognitive function is complex; it is unclear whether self-reported sleep is a robust correlate of people's cognitive function. We address this gap by using a comprehensive large-scale dataset (N = 1054) coupled with a novel modeling approach, specification curve analysis (SCA), to test the association between self-reported sleep and cognitive function. The results of the SCA showed robust correlations between self-reported sleep and cognitive function, with poorer sleep associated with worse cognitive function. Furthermore, the correlations between sleep components and cognitive function were heterogeneous, with differences emerging across cognitive measures and domains. Specifically, daytime dysfunction was associated with the strongest effect on subjective cognitive function, whereas sleep duration and sleep efficiency had the strongest effect on objective cognitive function. Therefore, the relationship between self-reported sleep and cognition depends largely on what and how cognitive function is measured. Our findings guide measurement and domain selection for future research on the role of sleep in cognitive function.

Luminance stepped decreasing ratio of the tunnel entrance enhanced lighting based on visual performance.

To achieve a safe and comfortable entrance enhanced lighting environment of tunnels, visual performance experiments under the dynamic and static luminance environments were carried out to investigate the influence of the luminance variation forms and stepped decreasing ratio k' of the tunnel entrance enhanced lighting on the driver's comprehensive visual performance. The application effect was further verified by real vehicle experiments and field luminance measurements. The results of the dynamic and static experiments show that compared with the continuous and smooth decrease of the luminance according to the International Commission on Illumination (CIE), when facing the stepped decrease of luminance, drivers tend to withstand greater visual operation stress and a more tense psychological state. After the stepped decrease of the luminance, the driver's average and instantaneous reaction both slow down, while the amplitude of the slowdown decreases with the increase of k' and increases with the increase of the luminance level. The results of the real vehicle experiments show that increasing k' of Threshold Zones 1 and 2 and Transition Zones 1 and 2 to 0.7, 0.6, 0.5, and 0.5, respectively, can effectively relieve driver's psychological tension and enhance the visual performance. For practical engineering applications, it should be combined with daylight reduction facilities, thus avoiding the increase of energy consumption of the tunnel entrance enhance lighting.

Crown Nanopores in Graphene for CO2 Capture and Filtration.

With growing concerns about global warming, it has become urgent and critical to capture carbon from various emission sources (such as power plants) and even directly from air. Recent advances in materials research permit the design of various efficient approaches for capturing CO2 with high selectivity over other gases. Here, we show that crown nanopores (resembling crown ethers) embedded in graphene can efficaciously allow CO2 to pass and block other flue gas components (such as N2 and O2). We carried out extensive density functional theory-based calculations as well as classical and ab initio molecular dynamics simulations to reveal the energetics and dynamics of gas transport through crown nanopores. Our results highlight that the designed crown nanopores in graphene possess not only an excellent selectivity for CO2 separation/capture but also fast transport (flow) rates, which are ideal for the treatment of flue gas in power plants.

Mild adsorption of carbon nitride (C3N3) nanosheet on a cellular membrane reveals its suitable biocompatibility.

Recently, the novel hole-containing carbon nitride C3N3 nanomaterial was successfully synthesized, featuring outstanding and unique mechanical and electrical properties. However, to fully exploit this nanomaterial in biomedical applications, information regarding its biocompatibility is necessary. Herein, by using all-atom molecular dynamics simulations, we evaluate the interactions between a C3N3 nanosheet and a critical cellular component, that is, a lipid membrane bilayer. Our results indicate that the C3N3 nanosheet is able to interact with the lipid bilayer surface without affecting the membrane's structural integrity. Moreover, our results showed that the C3N3 nanosheet is adsorbed on the surface of the lipid bilayer without inflicting any structural damage to the membrane, regardless of the conditions of the system (that is, with and without restrains in the C3N3 nanosheet). Also, we found that both energy contributions, namely vdW and Coulomb energies, conjointly mediated the C3N3 adsorption process. In comparison and as expected, pristine graphene significantly disturbed the membrane structure. Perpendicularly-oriented-sheet simulations described the significance of the surface charges of the C3N3 nanosheet in prohibiting its insertion into the membrane. Detailed analysis indicated that the electrostatic attraction between the pores in the C3N3 structure and the lipid head amino groups stabilized the interaction restricting the insertion of the C3N3 structure deeper into the membrane. Our results suggested the importance of the negatively charged C3N3 pores when interacting with lipid membranes. Our findings shed light on the potential compatibility of C3N3 with biomembranes and its underlying molecular mechanism, which might provide a useful foundation for the future exploration of this 2D nanomaterial in biomedical applications.

Testing the competition-colonization trade-off and its correlations with functional trait variations among subtropical tree species.

The competition-colonization trade-off, by which species can partition spatial niches, is a potentially important mechanism allowing the maintenance of species diversity in plant communities. We examined whether there was evidence for this trade-off among tree species in a subtropical forest and how it correlated with eight functional traits. We developed and estimated a metric for colonization ability that incorporates both fecundity and seed dispersal based on seed trap data and the sizes and distributions of adult trees. Competitive ability was estimated as survival probability under high crowding conditions based on neighborhood models. Although we found no significant relationship between colonization and competitive abilities, there was a significant negative correlation between long distance dispersal ability and competitive ability at the 5 cm size class. Colonizers had traits associated with faster growth, such as large leaves and low leaf lamina density, whereas competitors had traits associated with higher survival, such as dense wood. Our results imply that any trade-off between competition and colonization may be more determined by dispersal ability than by fecundity, suggesting that seed dispersal is an important contributor to diversity maintenance. Future work should test how competitive ability covaries with the components of colonization ability, as we did here.

Changing rainfall frequency affects soil organic carbon concentrations by altering non-labile soil organic carbon concentrations in a tropical monsoon forest.

Soil stores a substantial proportion of carbon (C), making it the greatest terrestrial C pool and pivotal to stabilizing the global climate system. Rainfall amounts and regimes have been changing in many places, but effects of precipitation changes on soil organic C (SOC) stabilization are not completely understood. Considerable attention has been focused on the consequences of changes in rainfall amounts, with rainfall regimes having been less studied. This study was conducted in a tropical climax forest to clarify the effects of rainfall changes on SOC fractions, with permanganate oxidation and density fractionations employed to divide the labile and non-labile SOC fractions. Two rainfall manipulation treatments, i.e., increased rainfall frequency with the total rainfall amount unchanged (IRF) and decreased rainfall amount by 50% with rainfall frequency unaltered (DRA), were conducted for two years, with ambient rainfall (AR) as the control. As a result, the IRF treatment increased the SOC concentration that mainly originated from increases in the non-labile SOC content. Relative to the AR control, the DRA treatment did not change the total SOC concentration although the labile SOC concentration increased. This typically is due to a small proportion of the labile fraction to the total SOC content. Our results suggest that this water-rich mature forest is resistant to rainfall amount changes to a great extent (e.g., decrease of 50% as in the present study) from the SOC stabilization perspective, while changes in rainfall frequency could exert more notable effects.

Forest dynamics and its driving forces of sub-tropical forest in South China.

Tree mortality and recruitment are key factors influencing forest dynamics, but the driving mechanisms of these processes remain unclear. To better understand these driving mechanisms, we studied forest dynamics over a 5-year period in a 20-ha sub-tropical forest in the Dinghushan Nature Reserve, South China. The goal was to identify determinants of tree mortality/recruitment at the local scale using neighborhood analyses on some locally dominant tree species. Results show that the study plot was more dynamic than some temperate and tropical forests in a comparison to large, long-term forest dynamics plots. Over the 5-year period, mortality rates ranged from 1.67 to 12.33% per year while recruitment rates ranged from 0 to 20.26% per year. Tree size had the most consistent effect on mortality across species. Recruitment into the ≥1-cm size class consistently occurred where local con-specific density was high. This suggests that recruitment may be limited by seed dispersal. Hetero-specific individuals also influenced recruitment significantly for some species. Canopy species had low recruitment into the ≥1-cm size class over the 5-year period. In conclusion, tree mortality and recruitment for sixteen species in this plot was likely limited by seed dispersal and density-dependence.

Separating the effects of environment and space on tree species distribution: from population to community.

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.