Mapping In Vivo RNA Structures and Interactions.

RNA folds to form diverse secondary and tertiary structures and often interacts with other biomolecules to function in cells. The technologies developed to map in vivo RNA structures and interactions can be broadly classified into four categories.

Revealing lncRNA Structures and Interactions by Sequencing-Based Approaches.

Long noncoding RNAs (lncRNAs) have emerged as significant players in almost every level of gene function and regulation. Thus, characterizing the structures and interactions of lncRNAs is essential for understanding their mechanistic roles in cells. Through a combination of (bio)chemical approaches and automated capillary and high-throughput sequencing (HTS), the complexity and diversity of RNA structures and interactions has been revealed in the transcriptomes of multiple species. These methods have uncovered important biological insights into the mechanistic and functional roles of lncRNA in gene expression and RNA metabolism, as well as in development and disease. In this review, we summarize the latest sequencing strategies to reveal RNA structure, RNA-RNA, RNA-DNA, and RNA-protein interactions, and highlight the recent applications of these approaches to map functional lncRNAs. We discuss the advantages and limitations of these strategies, and provide recommendations to further advance methodologies capable of mapping RNA structure and interactions in order to discover new biology of lncRNAs and decipher their molecular mechanisms and implication in diseases.

Comprehensive insights into the metabolism characteristics of small RNA Qrr4 in Vibrio alginolyticus.

Vibrio alginolyticus is an important foodborne pathogen that can infect both humans and marine animals and cause massive economic losses in aquaculture. Small noncoding RNAs (sRNAs) are emerging posttranscriptional regulators that affect bacterial physiology and pathological processes. In the present work, a new cell density-dependent sRNA, Qrr4, was characterized in V. alginolyticus based on a previously reported RNA-seq analysis and bioinformatics approach. The effects of Qrr4 actions on the physiology, virulence, and metabolism of V. alginolyticus were comprehensively investigated based on molecular biology and metabolomics approaches. The results showed that qrr4 deletion markedly inhibited growth, motility and extracellular protease activities. Additionally, nontargeted metabolism and lipidomics analyses revealed that qrr4 deletion induced significant disturbance of multiple metabolic pathways. The key metabolic remodelling that occurred in response to qrr4 deletion was found to involve phospholipid, nucleotide, carbohydrate and amino acid metabolic pathways, providing novel clues about a potential mechanism via which mutation of qrr4 could interfere with cellular energy homeostasis, modulate membrane phospholipid composition and inhibit nucleic acid and protein syntheses to regulate the motility, growth and virulence characteristics of V. alginolyticus. Overall, this study provides a comprehensive understanding of the regulatory roles of the new cell density-dependent sRNA Qrr4 in V. alginolyticus. KEY POINTS: • A novel cell density-dependent sRNA, Qrr4, was cloned in V. alginolyticus. •Qrr4 regulated growth and virulence factors of V. alginolyticus. • Phospholipid, nucleotide and energy metabolisms were modulated obviously by Qrr4.

Enhanced transcriptome-wide RNA G-quadruplex sequencing for low RNA input samples with rG4-seq 2.0.

BACKGROUND: RNA G-quadruplexes (rG4s) are non-canonical structural motifs that have diverse functional and regulatory roles, for instance in transcription termination, alternative splicing, mRNA localization and stabilization, and translational process. We recently developed the RNA G-quadruplex structure sequencing (rG4-seq) technique and described rG4s in both eukaryotic and prokaryotic transcriptomes. However, rG4-seq suffers from a complicated gel purification step and limited PCR product yield, thus requiring a high amount of RNA input, which limits its applicability in more physiologically or clinically relevant studies often characterized by the limited availability of biological material and low RNA abundance. Here, we redesign and enhance the workflow of rG4-seq to address this issue. RESULTS: We developed rG4-seq 2.0 by introducing a new ssDNA adapter containing deoxyuridine during library preparation to enhance library quality with no gel purification step, less PCR amplification cycles and higher yield of PCR products. We demonstrate that rG4-seq 2.0 produces high-quality cDNA libraries that support reliable and reproducible rG4 identification at varying RNA inputs, including RNA mounts as low as 10 ng. rG4-seq 2.0 also improved the rG4-seq calling outcome and nucleotide bias in rG4 detection persistent in rG4-seq 1.0. We further provide in vitro mapping of rG4 in the HEK293T cell line, and recommendations for assessing RNA input and sequencing depth for individual rG4 studies based on transcript abundance. CONCLUSIONS: rG4-seq 2.0 can improve the identification and study of rG4s in low abundance transcripts, and our findings can provide insights to optimize cDNA library preparation in other related methods.

A Transformer-Based Capsule Network for 3D Part-Whole Relationship Learning.

Learning the relationship between the part and whole of an object, such as humans recognizing objects, is a challenging task. In this paper, we specifically design a novel neural network to explore the local-to-global cognition of 3D models and the aggregation of structural contextual features in 3D space, inspired by the recent success of Transformer in natural language processing (NLP) and impressive strides in image analysis tasks such as image classification and object detection. We build a 3D shape Transformer based on local shape representation, which provides relation learning between local patches on 3D mesh models. Similar to token (word) states in NLP, we propose local shape tokens to encode local geometric information. On this basis, we design a shape-Transformer-based capsule routing algorithm. By applying an iterative capsule routing algorithm, local shape information can be further aggregated into high-level capsules containing deeper contextual information so as to realize the cognition from the local to the whole. We performed classification tasks on the deformable 3D object data sets SHREC10 and SHREC15 and the large data set ModelNet40, and obtained profound results, which shows that our model has excellent performance in complex 3D model recognition and big data feature learning.

Hepatic portal venous gas: A case report and analysis of 131 patients using PUBMED and MEDLINE database.

OBJECTIVE: Hepatic portal pneumatosis has a high mortality rate, and whether surgical intervention is necessary remains controversial. This experiment retrospectively analyzed the etiology, treatment methods and prognosis of adult patients with hepatoportal pneumocele to provide a theoretical basis for the treatment of this disease. METHODS: We analyzed the clinical symptoms and post-treatment of a 43-year-old male patient with HPVG admitted to hospital. We retrieved adult non-iatrogenic HPVG cases with complete clinical data in PUBMED,  and MEDLINE and other databases were retrieved for analysis, and summarized the pathogenesis, clinical symptoms, pathogenesis, pathogenesis and prognosis of different treatment schemes were summarized. RESULTS: The main etiology of HPVG are intestinal ischemia (27%), severe enteritis/intestinal perforation/intestinal fistula (16%), intestinal obstruction (7%), abdominal infection (7%), gastric diseases (11%), appendicitis and its complications (5%), acute hemorrhage or necrotizing pancreatitis (5%), Crohn's disease and its complications (4%), trauma (traffic accidents, falls) (2%), diverticulitis and perforation (6%), nephrogenic diseases (4%), spontaneous pneumohepatic portal vein (2%), other reasons (4%). And after analysis, we found that the survival rate of patients treated by surgery was 40.5% and the mortality rate was 19.1%, the difference between the two was significant. CONCLUSIONS: Etiology should be actively explored and surgical treatment is necessary.

Metabolic changes in primary, secondary, and lipid metabolism in tobacco leaf in response to topping.

As an important cultivation practice used for flue-cured tobacco, topping affects diverse biological processes in the later stages of development and growth. Some studies have focused on using tobacco genes to reflect the physiological changes caused by topping. However, the complex metabolic shifts in the leaf resulting from topping have not yet been investigated in detail. In this study, a comprehensive metabolic profile of primary, secondary, and lipid metabolism in flue-cured tobacco leaf was generated with use of a multiple platform consisting of gas chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and liquid chromatography-mass spectrometry/ultraviolet spectroscopy. A total of 367 metabolites were identified and determined. Both principal component analysis and the number of significantly different metabolites indicated that topping had the greatest influence on the upper leaves. During the early stage of topping, great lipid level variations in the upper leaves were observed, and antioxidant defense metabolites were accumulated. This indicated that the topping activated lipid turnover and the antioxidant defense system. At the mature stage, lower levels of senescence-related metabolites and higher levels of secondary metabolites were found in the topped mature leaves. This implied that topping delayed leaf senescence and promoted secondary metabolite accumulation. This study provides a global view of the metabolic perturbation in response to topping. Graphical abstract Metabolic alterations in tobacco leaf in response to topping using a multiplatform metabolomics.

A Nonparametric Model for Multi-Manifold Clustering with Mixture of Gaussians and Graph Consistency.

Multi-manifold clustering is among the most fundamental tasks in signal processing and machine learning. Although the existing multi-manifold clustering methods are quite powerful, learning the cluster number automatically from data is still a challenge. In this paper, a novel unsupervised generative clustering approach within the Bayesian nonparametric framework has been proposed. Specifically, our manifold method automatically selects the cluster number with a Dirichlet Process (DP) prior. Then, a DP-based mixture model with constrained Mixture of Gaussians (MoG) is constructed to handle the manifold data. Finally, we integrate our model with the k-nearest neighbor graph to capture the manifold geometric information. An efficient optimization algorithm has also been derived to do the model inference and optimization. Experimental results on synthetic datasets and real-world benchmark datasets exhibit the effectiveness of this new DP-based manifold method.

The Variation Analysis of DNA Methylation in Wheat Carrying Gametocidal Chromosome 3C from Aegilops triuncialis.

Gametocidal (Gc) chromosomes can ensure their preferential transmission by killing the gametes without themselves through causing chromosome breakage and therefore have been exploited as an effective tool for genetic breeding. However, to date very little is known about the molecular mechanism of Gc action. In this study, we used methylation-sensitive amplified polymorphism (MSAP) technique to assess the extent and pattern of cytosine methylation alterations at the whole genome level between two lines of wheat Gc addition line and their common wheat parent. The results indicated that the overall levels of cytosine methylation of two studied Gc addition lines (CS-3C and CS-3C3C, 48.68% and 48.65%, respectively) were significantly increased when compared to common wheat CS (41.31%) and no matter fully methylated or hemimethylated rates enhanced in Gc addition lines. A set of 30 isolated fragments that showed different DNA methylation or demethylation patterns between the three lines were sequenced and the results indicated that 8 fragments showed significant homology to known sequences, of which three were homologous to MITE transposon (Miniature inverted-repeat transposable elements), LTR-retrotransposon WIS-1p and retrotransposon Gypsy, respectively. Overall, our results showed that DNA methylation could play a role in the Gc action.

Metabolic Profiling with Gas Chromatography-Mass Spectrometry and Capillary Electrophoresis-Mass Spectrometry Reveals the Carbon-Nitrogen Status of Tobacco Leaves Across Different Planting Areas.

The interaction between carbon (C) and nitrogen (N) metabolism can reflect plant growth status and environmental factors. Little is known regarding the connections between C-N metabolism and growing regions under field conditions. To comprehensively investigate the relationship in mature tobacco leaves, we established metabolomics approaches based on gas chromatography-mass spectrometry (GC-MS) and capillary electrophoresis-time-of-flight-mass spectrometry (CE-TOF-MS). Approximately 240 polar metabolites were determined. Multivariate statistical analysis revealed that the growing region greatly influenced the metabolic profiles of tobacco leaves. A metabolic correlation network and related pathway maps were used to reveal the global overview of the alteration of C-N metabolism across three typical regions. In Yunnan, sugars and tricarboxylic acid (TCA) cycle intermediates were closely correlated with amino acid pools. Henan tobacco leaves showed positive correlation between the pentose phosphate pathway (PPP) intermediates and C-rich secondary metabolism. In Guizhou, the proline and asparagine had significant links with TCA cycle intermediates and urea cycle, and antioxidant accumulation was observed in response to drought. These results demonstrate that combined analytical approaches have great potential to detect polar metabolites and provide information on C-N metabolism related to planting regional characteristics.

A Novel Strategy for Large-Scale Metabolomics Study by Calibrating Gross and Systematic Errors in Gas Chromatography-Mass Spectrometry.

Metabolomics is increasingly applied to discover and validate metabolite biomarkers and illuminate biological variations. Combination of multiple analytical batches in large-scale and long-term metabolomics is commonly utilized to generate robust metabolomics data, but gross and systematic errors are often observed. The appropriate calibration methods are required before statistical analyses. Here, we develop a novel correction strategy for large-scale and long-term metabolomics study, which could integrate metabolomics data from multiple batches and different instruments by calibrating gross and systematic errors. The gross error calibration method applied various statistical and fitting models of the feature ratios between two adjacent quality control (QC) samples to screen and calibrate outlier variables. Virtual QC of each sample was produced by a linear fitting model of the feature intensities between two neighboring QCs to obtain a correction factor and remove the systematic bias. The suggested method was applied to handle metabolic profiling data of 1197 plant samples in nine batches analyzed by two gas chromatography-mass spectrometry instruments. The method was evaluated by the relative standard deviations of all the detected peaks, the average Pearson correlation coefficients, and Euclidean distance of QCs and non-QC replicates. The results showed the established approach outperforms the commonly used internal standard correction and total intensity signal correction methods, it could be used to integrate the metabolomics data from multiple analytical batches and instruments, and it allows the frequency of QC to one injection of every 20 real samples. The suggested method makes a large amount of metabolomics analysis practicable.

Sample-directed pseudotargeted method for the metabolic profiling analysis of rice seeds based on liquid chromatography with mass spectrometry.

Rice is one of the most important food crops in the world. Metabolite composition in rice seeds varies significantly depending on genetic variety, climatic alternation and agricultural practice. Metabolomics is a powerful tool to reveal the metabolic response of rice to various conditions. In this work, a rice seed sample-directed pseudotargeted metabolomics method was first established and validated based on ultra high performance liquid chromatography with triple quadrupole mass spectrometry in the multiple reaction monitoring mode. A total of 749 and 617 ion pairs in positive and negative modes were achieved, respectively. Among them, about 200 metabolites were identified or tentatively identified. The developed method showed better linearity and repeatability than those of non-targeted metabolomics method. Good intra-day and inter-day precisions, recoveries and wide linear range were also obtained. Furthermore, the method was applied for the investigation of metabolic variation of rice seeds with two wild cultivars and their transgenic lines that were grown in two locations. Principal component analysis indicated that the effects of cultivar and location on metabolic variations were far more than those of gene modification. The nonparametric Mann-Whitney U test revealed that most metabolites were influenced by cultivar, location and gene modifications together.

Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry.

Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.

Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

Bacterial community shift along with the changes in operational conditions in a membrane-aerated biofilm reactor.

Membrane-aerated biofilm reactor (MABR) is a promising wastewater treatment process. Although bacteria inhabiting the MABR biofilm are important in wastewater treatment, the community composition and its correlation with operating conditions were less clear. A laboratory-scale MABR was designed to investigate the shift of bacterial community through a complete operational process by pyrosequencing the bacterial 16S rRNA genes. From around 19,000 sequences, 175 bacterial genera were retrieved, mainly belonging to Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria, Bacteroidetes, and Actinobacteria. A large number of unclassified bacterial sequences were also detected in the biofilm, suggesting a wide variety of uncharacterized species in MABR. Redundancy analysis (RDA) revealed that influent chemical oxygen demand (COD), NH4-N, and NaHCO3 concentrations could exert distinct influences on the composition of the bacterial community. The influent COD and NaHCO3 concentrations stimulated proliferation of denitrification-related species such as Dokdonella, Azospira, Hydrogenophaga, Rhodocyclaceae, and Thauera, while inhibiting the growth of Acidovorax and Sinobacteraceae. Some denitrifying Thermomonas spp. tended to survive in NH4-N-rich environments, while Flavobacterium preferred to inhabit NH4-N-poor or COD-rich environments. Conversely, the influent NH4-N and NaHCO3, to some extent, appeared to be the growth-promoting factors for nitrifying bacteria. Furthermore, the presence of potential aerobic denitrifiers such as Comamonas, Enterobacter, and Aeromonas indicated that MABR could have the capability of simultaneous aerobic and anoxic denitrification particularly during treatment of low-ammonia nitrogen sewage.

Further Study on Chemical Constituents of Parnassia wightiana Wall: Four New Dihydro-ß-agarofuran Sesquiterpene Polyesters.

Four new (1-4), along with six known (5-10) dihydro-ß-agarofuran sesquiterpene polyesters were isolated from the whole plants of Parnassia wightiana. The new compounds were structurally elucidated through spectroscopic analysis including UV (Ultraviolet Spectrum), IR (Infrared Spectrum), ¹H-NMR (¹Hydrogen-Nuclear Magnetic Resonance), ¹³C-NMR (¹³Carbon-Nuclear Magnetic Resonance), DEPT (Distortionless Enhancement by Polarization Transfer), ¹H-¹H COSY (¹H-¹H Correlation Spectroscopy), HSQC (Heteronuclear Single Quantum Coherence), HMBC (Heteronuclear Multiple Bond Correlation), NOESY (Nuclear Overhauser Enhancement Spectroscopy) and HR-MS (High Resolution Mass Specttrum) and their absolute configurations were proposed by comparison of NOESY spectra and specific optical rotations with those of known compounds and biosynthesis grounds. Compound 2 is the first sesquiterpene alkaloid isolated from this plant. New compounds 1-4 exhibited some cytotoxic activities against NB4, MKN-45 and MCF-7 cells at 20 µM and of which 4 showed the highest activity against NB4 and MKN-45 cells with inhibition rates of 85.6% and 30.5%, respectively.

Metabolomics study of cured tobacco using liquid chromatography with mass spectrometry: method development and its application in investigating the chemical differences of tobacco from three growing regions.

Cured tobacco is an important plant material. Component studies are a big challenge for its significantly diverse chemical properties and vastly different concentrations. In this work, liquid chromatography with quadrupole time-of-flight mass spectrometry was used to perform a metabolomics study of cured tobacco owing to its efficient separation and detection of semipolar metabolites. A solvent of methanol/water (8:2, v/v) and 30 min of ultrasound time were found to be optimal to perform extraction. 95, 92, and 93% of metabolite features had within 20% of coefficient of variation for repeatability, intraday and interday precision analysis, respectively, indicating a good stability of the method developed. 113 metabolites were identified in cured tobacco based on accurate mass, retention time, and MS/MS fragments. The developed method was applied to a metabolomics study of cured tobacco from three growing regions. Forty three metabolites were found to be contributed to the classification. It is shown that the developed method can be applied to metabolomics analysis of plant materials.

An in vitro metabolic system of gut flora and the metabolism of ginsenoside Rg3 and cholic acid.

For orally administered drugs, the metabolism of a drug by the gut flora plays an important role in the bioavailability, activation and disposition of the drug in vivo. However, no in vitro system is currently available to evaluate the metabolism of a drug by the gut flora before the drug is absorbed into the body. This paper presents an in vitro metabolic system in an anaerobic environment that could be used to evaluate the metabolism of an endogenous compound, cholic acid, and a xenobiotic compound, ginsenoside Rg3. We showed that the proliferation of the anaerobic bacteria of the gut content of hamsters produced a similar composition of gut flora in a culture medium for yeast to that in vivo. Incubation of ginsenoside Rg3 and cholic acid in the anaerobic in vitro system efficiently produced the metabolites Rh2 and deoxycholic acid, respectively, similar to those seen in the gut content in vivo. In comparison with in vivo analysis, this anaerobic in vitro metabolic system is convenient, reproducible, economic and animal saving, and can easily be applied to assess the transformation and disposition of a drug before it enters into the circulatory system.

Influence of humic acid on the p-tert-Butylphenol removal efficiency by Spirodela polyrhiza-Tas13 association.

Plant-microbe remediation technique is considered as a promising technology in removal of organic pollutants and its remediation efficiency is largely affected by a variety of surrounding environmental factors. Humic acid (HA) is the complex organic substance ubiquitous in environment, which characterized by its surfactant-like micelle microstructure and various reaction activity. In our study, a plant-microbe association with high p-tert-Butylphenol (PTBP) degradation potential constructed by Spirodela polyrhiza and Sphingobium phenoxybenzoativorans Tas13 has been used, and the influence of HA on the PTBP degradation efficiency of S. polyrhiza-Tas13 association was investigated. The result showed that the presence of HA greatly improved PTBP removal efficiency of S. polyrhiza-Tas13. The reason accounted for this may be due to the presence of HA promoted bacterial cell propagation, altered bacterial cell wall permeability, increased catechol 2,3-dioxygenase (C23O) enzyme activity of strain Tas13, rather than increasing the colonization ability of strain Tas13 on to the root surface. This study will greatly facilitate the application of aquatic plant-microbe association in environmental remediation.

The effects of living arrangements and leisure activities on depressive symptoms of Chinese older adults: Evidence from panel data analysis.

BACKGROUND: Livable environment and ways, as the necessary conditions for the elderly to enjoy their old age, have a significant impact on their mental health and happiness. It's crucial to understand how living arrangements affect depressive symptoms in China. Studies on how various leisure activities modify this association are yet limited. METHODS: This study relies on panel data derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), collected during waves spanning 2008/2009, 2011/2012, 2014, and 2018. The primary objective is to examine the relationship between living arrangements, leisure activities, and depressive symptoms of elderly individuals. Linear mixed-effects models were used to analyze the data. RESULTS: A total of 26,342 observations aged 65 and over were included in this paper. Older adults living alone (ß = 0.66, 95 % CI: 0.55, 0.76) or living in institutions (ß = 0.69, 95 % CI: 0.40, 0.98) had more depressive symptoms than those living with family. Leisure activities were negatively associated with depressive symptoms (ß = -0.16, 95 % CI: -0.18, -0.15). Moreover, there was significant interactions between living arrangements and leisure activities. No matter which kind of living arrangements, participating in physical, productive or social activity was associated with a lower risk of depressive symptoms. LIMITATIONS: Study design might introduce bias, and it cannot establish causality between the tested variables. CONCLUSIONS: Older adults living alone or in institutions have more possibility to develop depressive symptoms than those living with family, and such a relationship among Chinese older adults can be moderated by participating in leisure activities.