Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration

Aberrant Dynamic Functional Network Connectivity and Graph Properties in Major Depressive Disorder

Major depressive disorder (MDD) is a complex mood disorder characterized by persistent and overwhelming depression. Previous studies have identified abnormalities in large scale functional brain networks in MDD, yet most of them were based on static functional connectivity. In contrast, here we explored disrupted topological organization of dynamic functional network connectivity (dFNC) in MDD based on graph theory. One hundred and eighty-two MDD patients and 218 healthy controls were included in this study, all Chinese Han people. By applying group information guided independent component analysis (GIG-ICA) to resting-state functional magnetic resonance imaging (fMRI) data, the dFNCs of each subject were estimated using a sliding window method and k-means clustering. Network properties including global efficiency, local efficiency, node strength and harmonic centrality, were calculated for each subject. Five dynamic functional states were identified, three of which demonstrated significant group differences in their percentage of state occurrence. Interestingly, MDD patients spent much more time in a weakly-connected State 2, which includes regions previously associated with self-focused thinking, a representative feature of depression. In addition, the FNCs in MDD were connected differently in different states, especially among prefrontal, sensorimotor, and cerebellum networks. MDD patients exhibited significantly reduced harmonic centrality primarily involving parietal lobule, lingual gyrus and thalamus. Moreover, three dFNCs with disrupted node properties were commonly identified in different states, and also correlated with depressive symptom severity and cognitive performance. This study is the first attempt to investigate the dynamic functional abnormalities in MDD in a Chinese population using a relatively large sample size, which provides new evidence on aberrant time-varying brain activity and its network disruptions in MDD, which might underscore the impaired cognitive functions in this mental disorder

Changes in Soil Bacterial Community and Function in Winter Following Long-Term Nitrogen (N) Deposition in Wetland Soil in Sanjiang Plain, China

N deposition is a key factor affecting the composition and function of soil microbial communities in wetland ecosystems. Previous studies mainly focused on the effects of N deposition in the soil during the growing season (summer and autumn). Here, we focused on the response of the soil microbial community structure and function in winter. Soil from the Sanjiang Plain wetland, China, that had been treated for the past 11 years by using artificial N deposition at three levels (no intervention in N0, N deposition with 4 g N m−2 yr−1 in N1, and with 8 g N m−2 yr−1 in N2). Soil characteristics were determined and the bacterial composition and function was characterized using high-throughput sequence technology. The N deposition significantly reduced the soil bacterial diversity detected in winter compared with the control N0, and it significantly changed the composition of the bacterial community. At the phylum level, the high N deposition (N2) increased the relative abundance of Acidobacteria and decreased that of Myxococcota and Gemmatimonadota compared with N0. In soil from N2, the relative abundance of the general Candidatus_Solibacter and Bryobacter was significantly increased compared with N0. Soil pH, soil organic carbon (SOC), and total nitrogen (TN) were the key factors affecting the soil bacterial diversity and composition in winter. Soil pH was correlated with soil carbon cycling, probably due to its significant correlation with aerobic_chemoheterotrophy. The results show that a long-term N deposition reduces soil nutrients in winter wetlands and decreases soil bacterial diversity, resulting in a negative impact on the Sanjiang plain wetland. This study contributes to a better understanding of the winter responses of soil microbial community composition and function to the N deposition in temperate wetland ecosystems

The complete mitochondrial genome of Cladobotryum mycophilum (Hypocreales: Sordariomycetes)

Cladobotryum mycophilum is the causal agent of cobweb disease in many important mushroom crops. In this study, we report the complete mitochondrial genome of C. mycophilum for the first time. The genome is 78,729 bp long and comprises 52 protein-coding genes (PCGs), 2 ribosomal RNA genes (rRNA), and 26 transfer RNA (tRNA) genes. The nucleotide composition of C. mycophilum mitochondrial genome is as follows: A (38.06%), T (34.68%), C (12.19%), and G (15.07%). Phylogenetic analysis revealed that C. mycophilum had a close relationship with Cladobotryum varium from Hypocreaceae. This study provided a basis for studies of the mitochondrial evolution of Hypocreaceae

Diversity Analysis of the Rice False Smut Pathogen Ustilaginoidea virens in Southwest China

Rice false smut caused by Ustilaginoidea virens is a destructive disease in rice cropping areas of the world. The present study is focused on the morphology, pathogenicity, mating-type loci distribution, and genetic characterization of different isolates of U. virens. A total of 221 strains of U. virens were collected from 13 rice-growing regions in southwest China. The morphological features of these strains exhibited high diversity, and the pathogenicity of the smut fungus showed significant differentiation. There was no correlation between pathogenicity and sporulation. Mating-type locus (MAT) analysis revealed that all 221 isolates comprised heterothallic and homothallic forms, wherein 204 (92.31%) and 17 (7.69%) isolates belonged to heterothallic and homothallic mating types, respectively. Among 204 strains of heterothallic mating types, 62 (28.05%) contained MAT1-1-1 idiomorphs, and 142 isolates (64.25%) had the MAT1-2-1 idiomorph. Interestingly, strains isolated from the same fungus ball had different mating types. The genetic structure of the isolates was analyzed using simple sequence repeats (SSRs) and single-nucleotide polymorphisms (SNPs). All isolates were clustered into five genetic groups. The values of Nei’s gene diversity (H) and Shannon’s information index (I) indicated that all strains as a group had higher genetic diversity than strains from a single geographical population. The pairwise population fixation index (FST) values also indicated significant genetic differentiation among all compared geographical populations. The analysis of molecular variation (AMOVA) indicated greater genetic variation within individual populations and less genetic variation among populations. The results showed that most of the strains were not clustered according to their geographical origin, showing the rich genetic diversity and the complex and diverse genetic background of U. virens in southwest China. These results should help to better understand the biological and genetic diversity of U. virens in southwest China and provide a theoretical basis for building effective management strategies

Characterization of the complete mitochondrial genome of Corynespora cassiicola (Pleosporales: Dothideomycetes), with its phylogenetic analysis

Corynespora cassiicola is a well-known plant pathogen with a broad host range and diverse lifestyles. In this study, we presented the complete mitochondrial genome (mitogenome) of C. cassiicola for the first time. It has a total length of 40,752 bp, which encodes 17 protein-coding genes (PCGs), 2 ribosomal RNA genes (rRNA), and 27 transfer RNA (tRNA) genes. The nucleotide composition of the mitogenome is: A (36.24%), T (34.62%), G (15.74%), and C (13.39%). Phylogenetic analysis revealed that C. cassiicola has a close relationship with Didymella pinodes from Didymellaceae

A New Strategy to Minimize Humidity Influences for Acoustic Wave Ultraviolet Sensor Using ZnO Nanowires Wrapped with Hydrophobic Silica Nanoparticles

Surface acoustic wave (SAW) technology has been widely developed for ultraviolet (UV) detection due to its advantages of miniaturization, portability, potential to be integrated with microelectronics, and passive/wireless capabilities. To enhance UV sensitivities, nanowires (NWs) such as ZnO are often applied to enhance SAW based UV detection, due to their highly porous and interconnected 3D network structures and good UV sensitivity. However, ZnO NWs are normally hydrophilic, and thus changes of environmental parameters such as humidity will significantly influence the detection precision and sensitivity of the SAW based UV sensors. To solve this issue, in this work, we proposed a new strategy using ZnO NWs wrapped with hydrophobic silica nanoparticles as the effective sensing layer. Analysis of distribution and chemical bonds of these hydrophobic silica nanoparticles showed that numerous C-F bonds (which are hydrophobic) were found on the surface of sensitive layer, which effectively block the adsorption of water molecules onto the ZnO NWs. This new sensing layer design endows the ZnO NWs based UV sensor with a minimized humidity interference within the relatively humidity range between 10 and 70. The sensor showed a UV sensitivity of 9.53 ppm (mW/cm2)-1, with a high linearity (R2 value is 0.99904), small hysteresis (less than 1.65) and a good repeatability. This work solves the long-term dilemma for ZnO NWs based sensors which are often sensitive to humidity changes