Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion.

Recent work has identified dozens of non-coding loci for Alzheimer's disease (AD) risk, but their mechanisms and AD transcriptional regulatory circuitry are poorly understood. Here, we profile epigenomic and transcriptomic landscapes of 850,000 nuclei from prefrontal cortexes of 92 individuals with and without AD to build a map of the brain regulome, including epigenomic profiles, transcriptional regulators, co-accessibility modules, and peak-to-gene links in a cell-type-specific manner. We develop methods for multimodal integration and detecting regulatory modules using peak-to-gene linking. We show AD risk loci are enriched in microglial enhancers and for specific TFs including SPI1, ELF2, and RUNX1. We detect 9,628 cell-type-specific ATAC-QTL loci, which we integrate alongside peak-to-gene links to prioritize AD variant regulatory circuits. We report differential accessibility of regulatory modules in late AD in glia and in early AD in neurons. Strikingly, late-stage AD brains show global epigenome dysregulation indicative of epigenome erosion and cell identity loss.

Molecular Choreography of Acute Exercise.

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians.

Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007. Growth parameters (i.e. height, velocity, and timing of growth spurt) were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 787 participants with height measurements spanning the whole period of growth. Heritability estimates suggested that genetic factors could explain 25% to 71% of the variance of pubertal growth traits. We performed a GWAS of growth parameters, testing their associations with 5 077 595 imputed or directly genotyped variants. Six variants associated with height at peak velocity (P < 5 × 10-8, adjusted for sex, birth year and principal components). Implicated genes include NUDT3, previously associated with adult height, and PACSIN1. Two novel variants associated with duration of growth spurt (P < 5 × 10-8) in LOC105375344, an uncharacterized gene with unknown function. We finally examined the association of growth parameters with a polygenic score for height derived from 9557 single nucleotide polymorphisms (SNPs) identified in the GIANT meta-analysis for which genotypic data were available for the American Indian study population. Height polygenic score was correlated with the magnitude and velocity of height growth that occurred before and at the peak of the adolescent growth spurt, indicating overlapping genetic architecture, with no influence on the timing of adolescent growth.

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years.

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual α peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of α oscillations and the relative balance of excitatory/inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection time points. Post hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

Linear and Nonlinear Behaviors of the Photoreceptor Coupled Network.

Photoreceptors are electrically coupled to one another, and the spatiotemporal properties of electrical synapses in a two-dimensional retinal network are still not well studied, because of the limitation of the single electrode or pair recording techniques which do not allow simultaneously measuring responses of multiple photoreceptors at various locations in the retina. A multiple electrode recording system is needed. In this study, we investigate the network properties of the two-dimensional rod coupled array of the salamander retina (both sexes were used) by using the newly available multiple patch electrode system that allows simultaneous recordings from up to eight cells and to determine the electrical connectivity among multiple rods. We found direct evidence that voltage signal spread in the rod-rod coupling network in the absence of I h (mediated by HCN channels) is passive and follows the linear cable equation. Under physiological conditions, I h shapes the network signal by progressively shortening the response time-to-peak of distant rods, compensating the time loss of signal traveling from distant rods to bipolar cell somas and facilitating synchronization of rod output signals. Under voltage-clamp conditions, current flow within the coupled rods follows Ohm's law, supporting the idea that nonlinear behaviors of the rod network are dependent on membrane voltage. Rod-rod coupling is largely symmetrical in the 2D array, and voltage-clamp blocking the next neighboring rod largely suppresses rod signal spread into the second neighboring rod, suggesting that indirect coupling pathways play a minor role in rod-rod coupling.

Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling.

Recognizing binding sites of DNA-binding proteins is a key factor for elucidating transcriptional regulation in organisms. ChIP-exo enables researchers to delineate genome-wide binding landscapes of DNA-binding proteins with near single base-pair resolution. However, the peak calling step hinders ChIP-exo application since the published algorithms tend to generate false-positive and false-negative predictions. Here, we report the development of DEOCSU (DEep-learning Optimized ChIP-exo peak calling SUite), a novel machine learning-based ChIP-exo peak calling suite. DEOCSU entails the deep convolutional neural network model which was trained with curated ChIP-exo peak data to distinguish the visualized data of bona fide peaks from false ones. Performance validation of the trained deep-learning model indicated its high accuracy, high precision and high recall of over 95%. Applying the new suite to both in-house and publicly available ChIP-exo datasets obtained from bacteria, eukaryotes and archaea revealed an accurate prediction of peaks containing canonical motifs, highlighting the versatility and efficiency of DEOCSU. Furthermore, DEOCSU can be executed on a cloud computing platform or the local environment. With visualization software included in the suite, adjustable options such as the threshold of peak probability, and iterable updating of the pre-trained model, DEOCSU can be optimized for users' specific needs.

Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.

BACKGROUND: Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as inflammations, infections, responses to exposures or interactions with microbial communities. However, biological interpretation of global metabolomics data remains a daunting task. Recent years have seen growing applications of pathway enrichment analysis based on putative annotations of liquid chromatography coupled with mass spectrometry (LC-MS) peaks for functional interpretation of LC-MS-based global metabolomics data. However, due to intricate peak-metabolite and metabolite-pathway relationships, considerable variations are observed among results obtained using different approaches. There is an urgent need to benchmark these approaches to inform the best practices. RESULTS: We have conducted a benchmark study of common peak annotation approaches and pathway enrichment methods in current metabolomics studies. Representative approaches, including three peak annotation methods and four enrichment methods, were selected and benchmarked under different scenarios. Based on the results, we have provided a set of recommendations regarding peak annotation, ranking metrics and feature selection. The overall better performance was obtained for the mummichog approach. We have observed that a ~30% annotation rate is sufficient to achieve high recall (~90% based on mummichog), and using semi-annotated data improves functional interpretation. Based on the current platforms and enrichment methods, we further propose an identifiability index to indicate the possibility of a pathway being reliably identified. Finally, we evaluated all methods using 11 COVID-19 and 8 inflammatory bowel diseases (IBD) global metabolomics datasets.

SmartGate is a spatial metabolomics tool for resolving tissue structures.

Imaging mass spectrometry (IMS) is one of the powerful tools in spatial metabolomics for obtaining metabolite data and probing the internal microenvironment of organisms. It has dramatically advanced the understanding of the structure of biological tissues and the drug treatment of diseases. However, the complexity of IMS data hinders the further acquisition of biomarkers and the study of certain specific activities of organisms. To this end, we introduce an artificial intelligence tool, SmartGate, to enable automatic peak selection and spatial structure identification in an iterative manner. SmartGate selects discriminative m/z features from the previous iteration by differential analysis and employs a graph attention autoencoder model to perform spatial clustering for tissue segmentation using the selected features. We applied SmartGate to diverse IMS data at multicellular or subcellular spatial resolutions and compared it with four competing methods to demonstrate its effectiveness. SmartGate can significantly improve the accuracy of spatial segmentation and identify biomarker metabolites based on tissue structure-guided differential analysis. For multiple consecutive IMS data, SmartGate can effectively identify structures with spatial heterogeneity by introducing three-dimensional spatial neighbor information.

The emergence of the EEG dominant rhythm across the first year of life.

The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.

Cross-α/ß polymorphism of PSMα3 fibrils.

The formation of ordered cross-ß amyloid protein aggregates is associated with a variety of human disorders. While conventional infrared methods serve as sensitive reporters of the presence of these amyloids, the recently discovered amyloid secondary structure of cross-α fibrils presents new questions and challenges. Herein, we report results using Fourier transform infrared spectroscopy and two-dimensional infrared spectroscopy to monitor the aggregation of one such cross-α-forming peptide, phenol soluble modulin alpha 3 (PSMα3). Phenol soluble modulins (PSMs) are involved in the formation and stabilization of Staphylococcus aureus biofilms, making sensitive methods of detecting and characterizing these fibrils a pressing need. Our experimental data coupled with spectroscopic simulations reveals the simultaneous presence of cross-α and cross-ß polymorphs within samples of PSMα3 fibrils. We also report a new spectroscopic feature indicative of cross-α fibrils.

Intensity and retention time prediction improves the rescoring of protein-nucleic acid cross-links.

In protein-RNA cross-linking mass spectrometry, UV or chemical cross-linking introduces stable bonds between amino acids and nucleic acids in protein-RNA complexes that are then analyzed and detected in mass spectra. This analytical tool delivers valuable information about RNA-protein interactions and RNA docking sites in proteins, both in vitro and in vivo. The identification of cross-linked peptides with oligonucleotides of different length leads to a combinatorial increase in search space. We demonstrate that the peptide retention time prediction tasks can be transferred to the task of cross-linked peptide retention time prediction using a simple amino acid composition encoding, yielding improved identification rates when the prediction error is included in rescoring. For the more challenging task of including fragment intensity prediction of cross-linked peptides in the rescoring, we obtain, on average, a similar improvement. Further improvement in the encoding and fine-tuning of retention time and intensity prediction models might lead to further gains, and merit further research.

Multiplet-Assisted Peak Alignment for 1H NMR-Based Metabolomics.

NMR-based metabolomics aims at recovering biological information by comparing spectral data from samples of biological interest and appropriate controls. Any statistical analysis performed on the data matrix relies on the proper peak alignment to produce meaningful results. Through the last decades, several peak alignment algorithms have been proposed, as well as alternatives like spectral binning or strategies for annotation and quantification, the latter depending on reference databases. Most of the alignment algorithms, mainly based on segmentation of the spectra, present limitations for regions with peak overlap or cases of frequency order exchange. Here, we present our multiplet-assisted peak alignment algorithm, a new methodology that consists of aligning peaks by matching multiplet profiles of f1 traces from J-resolved spectra. A correspondence matrix with the linked f1 traces is built, and multivariate data analysis can be performed on it to obtain useful information from the data, overcoming the issues of peak overlap and frequency crossovers. Statistical total correlation spectroscopy can be applied on the matrix as well, toward a better identification of molecules of interest. The results can be queried on one-dimensional (1D) 1H databases or can be directly coupled to our previously published Chemical Shift Multiplet Database.

Genome-wide profiling of histone (H3) lysine 4 (K4) tri-methylation (me3) under drought, heat, and combined stresses in switchgrass.

BACKGROUND: Switchgrass (Panicum virgatum L.) is a warm-season perennial (C4) grass identified as an important biofuel crop in the United States. It is well adapted to the marginal environment where heat and moisture stresses predominantly affect crop growth. However, the underlying molecular mechanisms associated with heat and drought stress tolerance still need to be fully understood in switchgrass. The methylation of H3K4 is often associated with transcriptional activation of genes, including stress-responsive. Therefore, this study aimed to analyze genome-wide histone H3K4-tri-methylation in switchgrass under heat, drought, and combined stress. RESULTS: In total, ~ 1.3 million H3K4me3 peaks were identified in this study using SICER. Among them, 7,342; 6,510; and 8,536 peaks responded under drought (DT), drought and heat (DTHT), and heat (HT) stresses, respectively. Most DT and DTHT peaks spanned 0 to + 2000 bases from the transcription start site [TSS]. By comparing differentially marked peaks with RNA-Seq data, we identified peaks associated with genes: 155 DT-responsive peaks with 118 DT-responsive genes, 121 DTHT-responsive peaks with 110 DTHT-responsive genes, and 175 HT-responsive peaks with 136 HT-responsive genes. We have identified various transcription factors involved in DT, DTHT, and HT stresses. Gene Ontology analysis using the AgriGO revealed that most genes belonged to biological processes. Most annotated peaks belonged to metabolite interconversion, RNA metabolism, transporter, protein modifying, defense/immunity, membrane traffic protein, transmembrane signal receptor, and transcriptional regulator protein families. Further, we identified significant peaks associated with TFs, hormones, signaling, fatty acid and carbohydrate metabolism, and secondary metabolites. qRT-PCR analysis revealed the relative expressions of six abiotic stress-responsive genes (transketolase, chromatin remodeling factor-CDH3, fatty-acid desaturase A, transmembrane protein 14C, beta-amylase 1, and integrase-type DNA binding protein genes) that were significantly (P < 0.05) marked during drought, heat, and combined stresses by comparing stress-induced against un-stressed and input controls. CONCLUSION: Our study provides a comprehensive and reproducible epigenomic analysis of drought, heat, and combined stress responses in switchgrass. Significant enrichment of H3K4me3 peaks downstream of the TSS of protein-coding genes was observed. In addition, the cost-effective experimental design, modified ChIP-Seq approach, and analyses presented here can serve as a prototype for other non-model plant species for conducting stress studies.

The effect of age on alpha rhythms in the human brain derived from source localized resting-state electroencephalography.

With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.

Ant impacts on global patterns of bird elevational diversity.

Using data on bird species elevational distributions from the world's mountain ranges, bird diets, and the distribution of the ant genus Oecophylla, we report that global patterns in bird elevational diversity show signals of competition with ants. Oecophylla is an abundant and effective predator of invertebrates, preying on the same species that invertivorous birds feed on. In mountain ranges with Oecophylla present in the foothills, the maximum species richness of invertivorous birds (but not other trophic guilds) occurs, on average, at 960 m, ca. 450 m higher than in mountain ranges without Oecophylla, resulting in a mid-elevation peak in bird species richness. Where Oecophylla is absent, bird species richness for all guilds generally show monotonic declines with increasing elevation. We argue that Oecophylla reduces prey density for invertivorous birds and that low prey abundance reduces invertivorous bird density, which in turn is correlated with lower bird species richness. These findngs suggest that competition between distantly related taxa can set range limits, leading to emergent diversity patterns over large scales.

Long-term PM2.5 exposure and peak expiratory flow in middle-aged and older people in China: A quasi-experimental study.

China's Clean Air Act (CCAA) has been demonstrated to reduce the public health burden of ambient air pollution. Few studies have assessed the health effects of CCAA on lung function. We aimed to investigate the effects of CCAA and PM2.5 exposures on peak expiratory flow (PEF) in middle-aged and older people in China. Three waves (2011, 2013, and 2015) of the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. We performed a difference-in-difference (DID) model and mixed effect method to assess the association between CCAA, PM2.5, and PEF. To increase the reliability, multiple environmental factors were considered, and spline function was utilized to fit the spatial autocorrelations. We found that the risk of decreased PEF in the policy intervention group was reduced by 46% (95% CI: 23%~62%). The estimate showed a 10µg/m3 increase in PM2.5 would increase the risk of decreased PEF by 10% (95% CI: 3%~18%). The results of the mixed effect model showed a 10 µg/m3 increase in PM2.5 concentration was associated with a 2.23% (95% CI: 1.35%~3.06%) decrease in the PEF. These results contributed to the limited epidemiology evidence on demonstrating the effect of PM2.5 on lung function.

Longitudinal decline in peak V̇o2 with aging in a healthy population is associated with a reduction in peripheral oxygen utilization but not in cardiac output.

Aging is associated with a significant decline in aerobic capacity assessed by maximal exercise oxygen consumption (V̇o2max). The relative contributions of the specific V̇o2 components driving this decline, namely cardiac output (CO) and arteriovenous oxygen difference (A - V)O2, remain unclear. We examined this issue by analyzing data from 99 community-dwelling participants (baseline age: 21-96 yr old; average follow-up: 12.6 yr old) from the Baltimore Longitudinal Study of Aging, free of clinical cardiovascular disease. V̇o2peak, a surrogate of V̇o2max, was used to assess aerobic capacity during upright cycle ergometry. Peak exercise left ventricular volumes, heart rate, and CO were estimated using repeated gated cardiac blood pool scans. The Fick equation was used to calculate (A - V)O2diff,peak from COpeak and V̇o2peak. In unadjusted models, V̇o2peak, (A - V)O2diff,peak, and COpeak declined longitudinally over time at steady rates with advancing age. In multiple linear regression models adjusting for baseline values and peak workload, however, steeper declines in V̇o2peak and (A - V)O2diff,peak were observed with advanced entry age but not in COpeak. The association between the declines in V̇o2peak and (A - V)O2diff,peak was stronger among those ≥50 yr old compared with their younger counterparts, but the difference between the two age groups did not reach statistical significance. These findings suggest that age-associated impairment of peripheral oxygen utilization during maximal exercise poses a stronger limitation on peak V̇o2 than that of CO. Future studies examining interventions targeting the structure and function of peripheral muscles and their vasculature to mitigate age-associated declines in (A - V)O2diff are warranted.NEW & NOTEWORTHY The age-associated decline in aerobic exercise performance over an average of 13 yr in community-dwelling healthy individuals is more closely associated with decreased peripheral oxygen utilization rather than decreased cardiac output. This association was more evident in older than younger individuals. These findings suggest that future studies with larger samples examine whether these associations vary across the age range and whether the decline in cardiac output plays a greater role earlier in life. In addition, studies focused on determinants of peripheral oxygen uptake by exercising muscle may guide the selection of preventive strategies designed to maintain physical fitness with advancing age.

The contribution of high-LET track to DNA damage formation and cell death for Monoenergy and SOBP carbon ion irradiation.

Carbon ion radiotherapy (CIRT) is a heavy ion charge particle therapy with 29 years of prominent use. Despite advantages like high relative biological effectiveness (RBE), improved quality of life, and reduced treatment time, challenges persist, especially regarding heavy nuclear fragments. Our research addresses these challenges in horizontal irradiation, aiming to comprehend Monoenergetic and Spread-Out Bragg peak (SOBP) carbon ion beam trajectories using cell survival analysis and visualizing biological effects through DNA damage (γ-H2AX). This reveals repair-related protein foci near the Bragg peak. CR-39, a plastic nuclear track detector, was explored to understand high-linear energy transfer (LET) tracks and radiation quality near the Bragg peak. Findings unveil high-LET DNA damage signatures through aligned γ-H2AX foci, correlating with LET values in SOBP. CR-39 visualized high-LET particle exposure, indicating comet-type etch-pits at the Bragg peak and suggesting carbon ion fragmentation. Unexpectedly, dot-type etch-pits in irradiated and post-Bragg peak regions indicated high-LET neutron production. This investigation highlights the intricate interplay of carbon ion beams, stressing the importance of understanding LET variations, DNA damage patterns, and undesired secondary exposure.

CdSe Quantum Dots Enable High Thermoelectric Performance in Solution-Processed Polycrystalline SnSe.

Here, a high peak ZT of ≈2.0 is reported in solution-processed polycrystalline Ge and Cd codoped SnSe. Microstructural characterization reveals that CdSe quantum dots are successfully introduced by solution process method. Ultraviolet photoelectron spectroscopy evinces that CdSe quantum dots enhance the density of states in the electronic structure of SnSe, which leads to a large Seebeck coefficient. It is found that Ge and Cd codoping simultaneously optimizes carrier concentration and improves electrical conductivity. The enhanced Seebeck coefficient and optimization of carrier concentration lead to marked increase in power factor. CdSe quantum dots combined with strong lattice strain give rise to strong phonon scattering, leading to an ultralow lattice thermal conductivity. Consequently, high thermoelectric performance is realized in solution-processed polycrystalline SnSe by designing quantum dot structures and introducing lattice strain. This work provides a new route for designing prospective thermoelectric materials by microstructural manipulation in solution chemistry.

Suppressed Droplet Splashing on Positively Skewed Surfaces for High-Efficiency Evaporation Cooling.

Two types of functional surfaces with the same roughness but completely different surface topographies are prepared, namely positively skewed surfaces filled with micropillar arrays (Sa ≈4.4 µm, Ssk >0) and negatively skewed surfaces filled with microcavity arrays (Sa ≈4.4 µm, Ssk <0), demonstrating promoting droplet splashing. Remarkably, the critical Weber number for generating satellite droplets on the negatively skewed surfaces is significantly lower than that on the positively skewed surfaces, indicating that the negatively skewed surface with microcavity arrays is more likely to promote droplet splashing. It is mainly attributed to the fact that air on the negatively skewed surface can make the liquid film take on a Cassie-Baxter state on the surface so that the stabilizing capillary force of the liquid film exceeds the destabilizing stress of the air film. Moreover, the surface topography promoting droplet spreading and the mechanical properties of three-phase moving contact lines are analyzed from the perspective of microscopic interface mechanics. Finally, it is demonstrated the designed positively skewed surfaces can be employed for large-area heat dissipation by means of high-efficiency evaporation.