Forestation at the right time with the right species can generate persistent carbon benefits in China.

Previous evaluations on the biophysical potential of forest carbon sink have focused on forestation area distribution and the associated carbon stock for equilibrium-state forests after centuries-long growth. These approaches, however, have limited relevance for climate policies because they ignore the near-term and mid-term decadal carbon uptake dynamics and suitable forest species for forestation. This study developed a forestation roadmap to support China's "carbon neutrality" objective in 2060 by addressing three key questions of forestation: where, with what forest species, and when to afforest. The results yielded a high-confidence potential forestation map for China at a resolution of 1 km with the identified optimal native forest type or species. Our analysis revealed an additional 78 Mha suitable for forestation up to the 2060s, a 43% increase on the current forest area. Selecting forest species for maximal carbon stock in addition to maximizing local environmental suitability enabled almost a doubling in forest carbon sink potential. Progressive forestation of this area can fix a considerable amount of CO2 and compensate for the carbon sink decline in existing forests. Altogether, the entire forest ecosystem can support a persistent biophysical carbon sink potential of 0.4 Pg C y-1 by 2060 and 0.2 Pg C y-1 by 2100, offsetting 7 to 14% of the current national fossil CO2 emissions. Our research provides an example of building a forestation roadmap toward a sustained forest carbon sink, which creates a critical time window for the emission cuts required by the goal of carbon neutrality.

A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks.

MOTIVATION: A large number of studies have shown that circular RNA (circRNA) affects biological processes by competitively binding miRNA, providing a new perspective for the diagnosis, and treatment of human diseases. Therefore, exploring the potential circRNA-miRNA interactions (CMIs) is an important and urgent task at present. Although some computational methods have been tried, their performance is limited by the incompleteness of feature extraction in sparse networks and the low computational efficiency of lengthy data. RESULTS: In this paper, we proposed JSNDCMI, which combines the multi-structure feature extraction framework and Denoising Autoencoder (DAE) to meet the challenge of CMI prediction in sparse networks. In detail, JSNDCMI integrates functional similarity and local topological structure similarity in the CMI network through the multi-structure feature extraction framework, then forces the neural network to learn the robust representation of features through DAE and finally uses the Gradient Boosting Decision Tree classifier to predict the potential CMIs. JSNDCMI produces the best performance in the 5-fold cross-validation of all data sets. In the case study, seven of the top 10 CMIs with the highest score were verified in PubMed. AVAILABILITY: The data and source code can be found at https://github.com/1axin/JSNDCMI.

Clonal spread of blaNDM-1-carrying Salmonella enterica serovar Typhimurium clone ST34 and wide spread of IncHI2/ST3-blaNDM-5 plasmid in China.

OBJECTIVES: To characterize blaNDM-carrying Salmonella recovered from a pig slaughterhouse. METHODS: In this study, 46 environment samples were collected from a slaughterhouse in China, and screened for carbapenem-resistant Enterobacterales. WGS, antimicrobial susceptibility testing and conjugation experiments were carried out to identify the isolates' resistance phenotypes and genetic characteristics. The phylogenetic relatedness of the Salmonella isolates obtained in this study and Salmonella (ST34 and ST29) in GenBank was determined. RESULTS: Two ST34 Salmonella Typhimurium and one ST29 Salmonella Stanley, recovered from three environmental samples (6.52%), were positive for blaNDM-1 and blaNDM-5, respectively. The two ST34 S. Typhimurium strains exhibited a close relationship (10-36 SNPs) with two human-derived blaNDM-1-bearing isolates from China (Hong Kong and Guangxi Province) and two blaNDM-negative ST34 Salmonella strains from the UK. The blaNDM-1 genes were located on IncHI2/ST3 plasmids. The capture of blaNDM-1 by the IncHI2/ST3 plasmid seems to be due to homologous recombination mediated by circular structures, as the genetic arrangements of the blaNDM-1 gene contain two IS26 elements of the same orientation. The blaNDM-5 gene was also carried by the IncHI2/ST3 plasmid, which shares highly similar structures with other blaNDM-5-bearing IncHI2/ST3 plasmids from other sources (fish, chicken, duck, human). CONCLUSIONS: This is the first report of a blaNDM-5-carrying IncHI2/ST3 plasmid in Salmonella. The clonal spread of NDM-1-producing ST34 S. Typhimurium across human and animal-associated environments, and the widespread dissemination of epidemic blaNDM-5-carrying IncHI2/ST3 plasmids among Enterobacteriaceae in China indicate the potential of further dissemination of blaNDM among Salmonella, which poses a threat to public health.

Radix Tetrastigma Hemsleyani Flavone represses cutaneous squamous cell carcinoma via Janus kinase/signal transducer and activator of transcription 3 pathway inactivation.

Cutaneous squamous cell carcinoma (CSCC) is the second most common malignant skin tumor and significantly affects patients' quality of life and health. The Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT3) pathway activation is involved in CSCC development. Radix Tetrastigma hemsleyani flavone (RTHF) is an active Radix Tetrastigma extract (RTE), which was recently reported to have promising inhibitory effects on CSCC. However, the underlying functional mechanisms of this inhibition remain unknown. In the present study, A431 cells or SCL-1 cells were incubated with 1, 5, and 10 mg/mL RTHF for 48 h, respectively. A significantly increased wound closure rate, decreased number of migrated and invaded cells, decreased colony number, and elevated apoptotic rate were observed after treatment with 1, 5, and 10 mg/mL RTHF. Furthermore, after incubation with RTHF, p-JAK1/JAK1, p-JAK2/JAK2, and p-STAT3/STAT3 levels were drastically reduced. An A431 xenograft model was constructed, followed by oral administration of 15, 30, or 60 mg/kg RTHF for 21 consecutive days. A significantly lower increase in tumor volume and reduced tumor weight were observed in all RTHF-treated groups. In addition, JAK/STAT3 signaling was drastically repressed in tumor tissues. Collectively, RTHF inhibited CSCC progression, which may be associated with JAK/STAT3 pathway inactivation.

The predictive efficacy of programmed cell death in immunotherapy of melanoma: A comprehensive analysis of gene expression data for programmed cell death biomarker and therapeutic target discovery.

In this study, genes linked to prognosis in skin cutaneous melanoma (SKCM) involved in programmed cell death (PCD) were identified and confirmed and prognostic models based on these genes were constructed. Acquisition and analysis of clinical data and RNA sequencing information from The Cancer Genome Atlas-SKCM (TCGA-SKCM) and Sangerbox databases, gene expression data for 477 tumor samples and 2 normal samples were successfully gathered. The patients were separated into two clusters based on consensus clustering of PCD-related genes, with Cluster A having greater tumor purity, ESTIMATE score, immune score, and matrix score, and Cluster B having a significantly distinct pattern of immune cell infiltration. The use of gene set enrichment analysis and weighted correlation network analysis showed significant associations between certain genes and factors such as tumor mutation burden, age, stage, grade, and tumor subtype. Finally, based on the 12 genes selected by Least Absolute Shrinkage and Selection Operator regression analysis (STAT3, IRF2, SLC7A11, ZEB1, LIPT1, PML, GCH1, GYS1, ABCC1, XBP1, TFAP2C, NOX4), a prognostic model of PGD-related genes was constructed. The effectiveness of the model's prognostic value was confirmed through survival analysis, time-dependent receiver operating characteristic curve, single-factor Cox regression analysis, and nomogram. We also verified the relationship between the GCH1 and MKI67 expression by wet experiment. This model has high prediction accuracy in SKCM patients and can provide a reference for clinical treatment.

The role of PKP1 in tumor progression in melanoma: Analysis of a cell adhesion-related model.

The incidence rate of melanoma varies across regions, with Europe, the United States, and Australia having 10-25, 20-30, and 50-60 cases per 1 00 000 people. In China, patients with melanoma exhibit different clinical manifestations, pathogenesis, and outcomes. Current treatments include surgery, adjuvant therapy, and immune checkpoint inhibitors. Nonetheless, complications may arise during treatment. Melanoma development is heavily reliant on cell adhesion molecules (CAMs), and studying these molecules could provide new research directions for metastasis and progression. CAMs include the integrin, immunoglobulin, selectin, and cadherin families, and they affect multiple processes, such as maintenance, morphogenesis, and migration of adherens junction. In this study, a cell adhesion-related risk prognostic signature was constructed using bioinformatics methods, and survival analysis was performed. Plakophilin 1 (PKP1) was observed to be crucial to the immune microenvironment and has significant effects on melanoma cell proliferation, migration, invasion, and the cell cycle. This signature demonstrates high reliability and has potential for clinical applications.

Fabrication of planar monolayer microreactor array for visual statistical analysis and droplet-based digital quantitative analysis in situ.

Planar monolayer microreactor arrays (PMMRAs) make droplet-based numerical measurements and statistical analysis cheap and easy. However, PMMRAs are typically produced in complex microfluidic devices and, moreover, still requires stringent control to reduce droplet loss during heating. In this paper, a simple, reliable, and flexible method for fabricating PMMRAs in a 96-well plate is described in detail by using simple materials and low-cost equipment. The partitioned droplets spontaneously assemble into PMMRAs in the plates, and this distribution is maintained even after incubation. This is advantageous for in situ analysis based on an individual droplet in droplet digital loop-mediated isothermal amplification (ddLAMP) and does not require the transfer of positive droplets. Precise and reproducible quantification of classical swine fever virus (CSFV) extracts was executed in these PMMRAs to verify its availability. Our results demonstrate that the proposed approach not only provides a flexible and controllable execution scheme for droplet-based nucleic acid quantification in resource-limited laboratories but also opens new perspectives for numerous analytical and biochemical applications using droplets as versatile plastic microreactors.

Quantitative analysis of respiratory viruses based on lab-on-a-chip platform.

The quantitative analysis of respiratory viruses is of great importance for rapid diagnosis, precision medicine, and prognosis. Several current quantitative analysis systems have been proposed and commercialized. Although they have been proven in trials, quantitative analyzes based on real samples are still complex, time-consuming, and expensive. Therefore, they are not able to directly quantify real samples. In this work, we presented a lab-on-a-chip platform combined with an automated control system to achieve quantitative analysis from samples to results. We developed a multilayer integrated chip to rapidly extract and quantify RNA of coronavirus disease 2019 (COVID-19) pseudovirus from large-volume nasal swab samples. The dependence of the magnetic bead size and the interfacial effect was studied for the first time, and the conditions of immiscible filtration assisted by surface tension (IFAST) method for nucleic acid extraction were optimized to increase the nucleic acid recovery rate up to 85%. Inside the chip, a pneumatic valve was developed for automatic opening and closing of the liquid channel. The integrated chip platform and automatic control system presented here are advantageous for use in resource-limited settings (RLS). In addition, our method can be extended to other respiratory viruses and other sample types.

Comparative study of first-principles approaches for effective Coulomb interaction strength Ueff between localized f-electrons: Lanthanide metals as an example.

As correlation strength has a key influence on the simulation of strongly correlated materials, many approaches have been proposed to obtain the parameter using first-principles calculations. However, a comparison of the different Coulomb strengths obtained using these approaches and an investigation of the mechanisms behind them are still needed. Taking lanthanide metals as an example, we research the factors that affect the effective Coulomb interaction strength, Ueff, by local screened Coulomb correction (LSCC), linear response (LR), and constrained random-phase approximation (cRPA) in the Vienna Ab initio Simulation Package. The Ueff LSCC value increases from 4.75 to 7.78 eV, Ueff LR is almost stable at about 6.0 eV (except for Eu, Er, and Yb), and Ueff cRPA shows a two-stage decreasing trend in both light and heavy lanthanides. To investigate these differences, we establish a scheme to analyze the coexistence and competition between the orbital localization and the screening effect. We find that LSCC and cRPA are dominated by the orbital localization and the screening effect, respectively, whereas LR shows the balance of the competition between the two factors. Additionally, the performance of these approaches is influenced by different starting points from the Perdew-Burke-Ernzerhof (PBE) and PBE + U, especially for cRPA. Our results provide useful knowledge for understanding the Ueff of lanthanide materials, and similar analyses can also be used in the research of other correlation strength simulation approaches.

Single-minded homolog 2 as a potential prognostic signature and assessment of its correlation with immune cell infiltration in pancreatic cancer.

Single-minded homolog 2 (SIM2) has been identified as a potential contributor to the development of solid tumors. Despite this, there is a lack of comprehensive research regarding its biological role and underlying mechanism within pancreatic cancer (PC), as well as its prognostic impact. This study systematically evaluated the expression level and clinical significance of SIM2 in patients with PC using various databases, including The Cancer Genome Atlas, KM Plotter, and gene expression profiling interactive analysis. To investigate the relationship between SIM2 expression and immune cell infiltration, we conducted ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) analyses. Single-minded homolog 2 was up-regulated in patients with PC. Pancreatic cancer patients with higher SIM2 expression had poorer overall survival rates. Gene set enrichment analysis results suggested that SIM2 may have a significant impact on the progression of PC and the regulation of immune responses. According to the ssGSEA algorithm, SIM2 has a negative correlation with the levels of infiltrating TFH, mast cells, and pDC. Our study demonstrated that SIM2 serves as a biomarker, and is associated with both prognosis and immune infiltration in PC. This provides a solid foundation for future investigations into the precise role of SIM2 in the carcinogenesis and progression of PC.

Engineering of formate dehydrogenase for improving conversion potential of carbon dioxide to formate.

Formate dehydrogenase (FDH) is a D-2-hydroxy acid dehydrogenase, which can reversibly reduce CO2 to formate and thus act as non-photosynthetic CO2 reductase. In order to increase catalytic efficiency of formate dehydrogenase for CO2 reduction, two mutants V328I/F285W and V354G/F285W were obtained of which reduction activity was about two times more than the parent CbFDHM2, and the formate production from CO2 catalyzed by mutants were 2.9 and 2.7-fold higher than that of the parent CbFDHM2. The mutants had greater potential in CO2 reduction. The optimal temperature for V328I/F285W and V354G/F285W was 55 °C, and they showed increasement of relative activity under 45 °C to 55 °C compared with parent. The optimal pH for the mutants was 9.0, and they showed excellent stability in pH 4.0-11.5. The kcat/Km values of mutants were 1.75 times higher than that of the parent. Then the molecular basis for its improvement of biochemical characteristics were preliminarily elucidated by computer-aided methods. All of these results further established a solid foundation for molecular modification of formate dehydrogenase and CO2 reduction.

LncRNA GAS8-AS1 is a Novel Prognostic and Diagnostic Biomarker for Pancreatic Cancer.

BACKGROUND: LncRNA GAS8-AS1 inhibits thyroid carcinoma, but its function in other malignancies is unknown. The present study aimed to investigate the involvement of GAS8-AS1 in pancreatic cancer (PC). METHODS: The present study included 68 PC patients (38 males and 30 females, 42-66 years, 52.1 ± 4.5) and 62 healthy volunteers (28 males and 24 females, 43-67 years, 52.3 ± 4.9). Real-time quantitative PCR, transient cell transfection, and in vitro cell migration and invasion assays were applied for the research. RESULTS: The study showed that plasma GAS8-AS1 was lower in PC patients than in healthy controls. Downregulation of plasma GAS8-AS1 distinguished early-stage PC patients from healthy controls. Patients with low GAS8-AS1 plasma levels showed a significantly lower 5-year overall survival rate. Plasma miR-1179 levels were also significantly lower in PC patients than in healthy controls and were positively correlated with plasma GAS8-AS1 levels in PC patients but not healthy controls. GAS8-AS1 overexpression upregulated miR-1179, and MiR-1179 overexpression increased GAS8-AS1 level. Overexpression of both GAS8-AS1 and miR-1179 inhibited PC cell migration and invasion. CONCLUSION: GAS8-AS1 may promote PC by positively interacting with miR-1179.

Effects of pre-pregnancy BMI and gestational weight gain on adverse pregnancy outcomes and complications of GDM.

To investigate the effects of pre-pregnancy BMI and gestational weight gain on adverse pregnancy outcomes and complications of gestational diabetes mellitus. 3966 pregnant women were enrolled in this study. Multivariate logistic regression analysis was conducted to estimate the relative risk between pre-pregnancy BMI, gestational weight gain, and adverse pregnancy outcome. Pre-pregnancy BMI was found to be a risk factor for preeclampsia (OR = 1.159), gestational diabetes mellitus (OR = 1.191), gestational hypertension (OR = 1.221), and macrosomia (OR = 1.165). Gestational weight gain was a risk factor for preeclampsia (OR = 1.783), placental abruption (OR = 2.209), and macrosomia (OR = 1.506). Total weight gain during pregnancy cannot be used as a predictor of GDM. Pre-pregnancy BMI is a risk factor for gestational diabetes mellitus complicated with preeclampsia, preterm delivery, gestational hypertension, and macrosomia. Impact statementWhat is already known on this subject? Obesity during pregnancy includes pre-pregnancy obesity and excessive weight gain during pregnancy. Obese pregnant women have a higher risk of pregnancy complications.What do the results of this study add? We focus on the effects of pre-pregnancy BMI on pregnancy outcomes, classified by Asian criteria. Our findings suggest for the first time that excessive weight gain during pregnancy is a risk factor for placental abruption and we specifically point out that total weight gain during pregnancy cannot be used as a predictor of GDM.What are the implications of these findings for clinical practice and/or further research? This study is helpful to monitor the risk of adverse pregnancy outcomes in the Asian population and suggest the risk of pregnancy complications, such as gestational diabetes mellitus and placental abruption.

[Dynamics analysis of knee joint during sit-stand movement].

Sit-stand movement is one of the most common movement behaviors of the human body. The knee joint is the main bearing joint of this movement. Thus, the dynamic analysis of knee joint during this movement has deeply positive influences. According to the principle of moment balance, the dynamics of the knee joint during the movement were analyzed. Furthermore, combined with the data obtained from optical motion capture and six-dimensional ground reaction force test, the curve of knee joint torque was calculated. To verify the accuracy of the analysis of dynamic, the human body model was established, the polynomial equations of angle and angular velocity were fitted according to the experimental data, and the knee joint simulation of the movement was carried out. The result revealed that in terms of range and trend, the theoretical data and simulation data were consistent. The relationship between knee joint torque and ground reaction force was revealed based on the variation law of knee joint torque. During the sit-stand movement, the knee joint torque and the ground reaction force were directly proportional to each other, and the ratio was 5 to 6. In the standing process, the acceleration first increased and then decreased and finally increased in reverse, and the maximum knee torque occurred at an angle of about 140°. In the sitting process, the torque was maximized in the initial stage. The results of the dynamics analysis of knee joint during sit-stand movement are beneficial to the optimal design and force feedback control of seated rehabilitation aids, and can provide theoretical guidance for knee rehabilitation training.

Study on the differences of gene expression between pear and apple wild cultivation materials based on RNA-seq technique.

BACKGROUND: Pears and apples are both perennial deciduous trees of the Rosaceae family, and both are important economic fruit trees worldwide. The emergence of many varieties in the market has been mostly domesticated from wild to cultivated and regulated by the differential expression of genes. However, the molecular process and pathways underlying this phenomenon remain unclear. Four typical wild and cultivar pear and apple trees at three developmental stages were used in our study to investigate the molecular process at the transcriptome level. RESULT: Physiological observations indicated the obvious differences of size, weight, sugar acid content and peel color in wild and cultivar fruit among each developmental stage. Using next-generation sequencing based RNA-seq expression profiling technology, we produced a transcriptome in procession of a large fraction of annotated pear and apple genes, and provided a molecular basis underlying the phenomenon of wild and cultivar fruit tree differences. 5921 and 5744 differential expression genes were identified in pear and apple at three developmental stages respectively. We performed temporal and spatial differential gene expression profiling in developing fruits. Several key pathways such as signal transduction, photosynthesis, translation and many metabolisms were identified as involved in the differentiation of wild and cultivar fruits. CONCLUSION: In this study, we reported on the next-generation sequencing study of the temporal and spatial mRNA expression profiling of pear and apple fruit trees. Also, we demonstrated that the integrated analysis of pear and apple transcriptome, which strongly revealed the consistent process of domestication in Rosaceae fruit trees. The results will be great influence to the improvement of cultivar species and the utilization of wild resources.

Atomic force microscopy for revealing micro/nanoscale mechanics in tumor metastasis: from single cells to microenvironmental cues.

Mechanics are intrinsic properties which appears throughout the formation, development, and aging processes of biological systems. Mechanics have been shown to play important roles in regulating the development and metastasis of tumors, and understanding tumor mechanics has emerged as a promising way to reveal the underlying mechanisms guiding tumor behaviors. In particular, tumors are highly complex diseases associated with multifaceted factors, including alterations in cancerous cells, tissues, and organs as well as microenvironmental cues, indicating that investigating tumor mechanics on multiple levels is significantly helpful for comprehensively understanding the effects of mechanics on tumor progression. Recently, diverse techniques have been developed for probing the mechanics of tumors, among which atomic force microscopy (AFM) has appeared as an excellent platform enabling simultaneously characterizing the structures and mechanical properties of living biological systems ranging from individual molecules and cells to tissue samples with unprecedented spatiotemporal resolution, offering novel possibilities for understanding tumor physics and contributing much to the studies of cancer. In this review, we survey the recent progress that has been achieved with the use of AFM for revealing micro/nanoscale mechanics in tumor development and metastasis. Challenges and future progress are also discussed.

Clinicopathological features and risk factors analysis of lymph node metastasis and long-term prognosis in patients with synchronous multiple gastric cancer.

BACKGROUND: As a common malignancy, gastric cancer (GC) remains an important threat to human's health. The incidence of synchronous multiple gastric cancer (SMGC) has increased obviously with technical advances of endoscopic and pathological examinations. Several studies have investigated the relationship between SMGC and solitary gastric cancer (SGC). However, little is known about the relationship between early and advanced SMGCs, and the independent risk factors of lymph node metastasis and prognosis in SMGC patients remain unclear. METHODS: We retrospectively collected 57 patients diagnosed as SMGC and underwent radical gastrectomies from December 2011 to September 2019. Epidemiological data and clinicopathological characteristics of all patients were recorded. Postoperative follow-up was performed by telephone or outpatient service. Chi-squared test or Fisher's exact test was adopted in analysis of categorical data. Continuous data were analyzed by using unpaired t test. Univariate and multivariate analyses were performed to investigate the independent risk factors of lymph node metastasis and tumor recurrence of SMGC. RESULTS: There were 45 males and 12 females. The average age was 62.1 years old. There were 20 patients with early SMGC and 37 patients with advanced SMGC. Most of patients (91.2%) had two malignant lesions. Tumor recurrence occurred in 8 patients, among which 7 patients died from recurrence. The rates of total gastrectomy, tumor size ≥ 2 cm, poorly differentiated type, lymph node metastasis, ulcer and nerve invasion, and preoperative CEA level were significantly higher in advanced SMGC patients compared to those with early SMGC. Lymphovascular cancer plug and preoperative CA125 were the independent risk factors of lymph node metastasis in patients with SMGC. Lymph node metastasis, nerve invasion, and preoperative AFP might be the risk factors of tumor recurrence of SMGC, but need further validation. CONCLUSIONS: In patients with SMGC, the presence of tumor size ≥ 2 cm, poorly differentiated type, lymph node metastasis, ulcer, nerve invasion, and relatively high preoperative CEA level might indicate the advanced SMGC. More attention should be paid to lymph node metastasis in SMGC patients with lymphovascular cancer plug and high preoperative CA125. Lymph node metastasis, nerve invasion, and preoperative AFP might be associated with recurrence of SMGC, needing further validation.

Association between air pollutants and atrial fibrillation in general population: A systematic review and meta-analysis.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia with several risk factors. Recent studies have suggested that the exposure to air pollutants may increase the prevalence of AF, we evaluated those studies systematically to better elucidate the correlation between exposure to air pollution and AF. METHOD: We conducted a systematic review of publications using PubMed, Embase, the Cochrane library and Web of Science to explore the association between air pollutants and AF within the general population. The chosen studies were published until 7 July 2020. According to different study designs, we divided the outcomes into "short-term-exposure group" and "long-term-exposure group" for each pollutant. We used I2 statistics and Q-test to examine statistical heterogeneity, and sensitivity analysis to exclude the heterogeneous study. Fixed or random-effect model was used to combine the effects. Final result was presented as the OR and 95% CI of AF prevalence for every 10 µg/m3 increase in the concentration of PM2.5 and PM10;10 ppb increase in the concentration of SO2 ,NO2 ,O3; and 1 ppm increase in the CO concentration. RESULTS: Our analysis contain 18 studies. Underlying short-term exposure effect, for each increment of 10 µg/m3 in the PM2.5 concentration, the combined OR of AF prevalence was 1.01(1.00-1.02), for PM10 was 1.03(1.01-1.05). For a 10 ppb increment in the concentration of SO2, NO2, and O3 was 1.05(1.01-1.09), 1.03(1.01-1.04), and 1.01(0.97-1.06), respectively, for a 1 ppm increase of CO concentration was 1.02(0.99-1.06). Underlying long-term-exposure effect for each increment of 10 µg/m3 in the PM2.5 concentration; the combined OR of AF prevalence was 1.07(1.04-1.10) and that for PM10 was 1.03(1.03-1.04) For a 10 ppb increment in the NO2 concentration was 1.02(1.00-1.04). CONCLUSION: Our meta-analysis indicated that all air pollutants exposure had an adverse effect on AF prevalence in general population.

Traits mediate drought effects on wood carbon fluxes.

CO2 fluxes from wood decomposition represent an important source of carbon from forest ecosystems to the atmosphere, which are determined by both wood traits and climate influencing the metabolic rates of decomposers. Previous studies have quantified the effects of moisture and temperature on wood decomposition, but these effects were not separated from the potential influence of wood traits. Indeed, it is not well understood how traits and climate interact to influence wood CO2 fluxes. Here, we examined the responses of CO2 fluxes from dead wood with different traits (angiosperm and gymnosperm) to 0%, 35%, and 70% rainfall reduction across seasonal temperature gradients. Our results showed that drought significantly decreased wood CO2 fluxes, but its effects varied with both taxonomical group and drought intensity. Drought-induced reduction in wood CO2 fluxes was larger in angiosperms than gymnosperms for the 35% rainfall reduction treatment, but there was no significant difference between these groups for the 70% reduction treatment. This is because wood nitrogen density and carbon quality were significantly higher in angiosperms than gymnosperms, yielding a higher moisture sensitivity of wood decomposition. These findings were demonstrated by a significant positive interaction effect between wood nitrogen and moisture on CO2 fluxes in a structural equation model. Additionally, we ascertained that a constant temperature sensitivity of CO2 fluxes was independent of wood traits and consistent with previous estimates for extracellular enzyme kinetics. Our results highlight the key role of wood traits in regulating drought responses of wood carbon fluxes. Given that both climate and forest management might extensively modify taxonomic compositions in the future, it is critical for carbon cycle models to account for such interactions between wood traits and climate in driving dynamics of wood decomposition.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.