Prmt5 deficient mouse B cells display RNA processing complexity and slower colorectal tumor progression.

Protein arginine methyltransferase 5 (Prmt5) is essential for normal B-cell development; however, the roles of Prmt5 in tumor-infiltrating B cells in tumor therapy have not been well elucidated. Here, we revealed that CD19-cre-Prmt5fl/fl (Prmt5cko) mice showed smaller tumor weights and volumes in the colorectal cancer mouse model; B cells expressed higher levels of Ccl22 and Il12a, which attracted T cells to the tumor site. Furthermore, we used direct RNA sequencing to comprehensively profile RNA processes in Prmt5 deletion B cells to explore underline mechanisms. We found significantly differentially expressed isoforms, mRNA splicing, poly(A) tail lengths, and m6A modification changes between the Prmt5cko and control groups. Cd74 isoform expressions might be regulated by mRNA splicing; the expression of two novel Cd74 isoforms was decreased, while one isoform was elevated in the Prmt5cko group, but the Cd74 gene expression showed no changes. We observed Ccl22, Ighg1, and Il12a expression was significantly increased in the Prmt5cko group, whereas Jak3 and Stat5b expression was decreased. Ccl22 and Ighg1 expression might be associated with poly(A) tail length, Jak3, Stat5b, and Il12a expression might be modulated by m6A modification. Our study demonstrated that Prmt5 regulates B-cell function through different mechanisms and supported the development of Prmt5-targeted antitumor treatments.

Metabolomic and transcriptomic analyses highlight metabolic regulatory networks of Salvia miltiorrhiza in response to replant disease.

BACKGROUND: Salvia miltiorrhiza, a well-known traditional Chinese medicine, frequently suffers from replant diseases that adversely affect its quality and yield. To elucidate S. miltiorrhiza's metabolic adaptations to replant disease, we analyzed its metabolome and transcriptome, comparing normal and replant diseased plants for the first time. RESULTS: We identified 1,269 metabolites, 257 of which were differentially accumulated metabolites, and identified 217 differentially expressed genes. Integrated transcriptomic and metabolomic analyses revealed a significant up-regulation and co-expression of metabolites and genes associated with plant hormone signal transduction and flavonoid biosynthesis pathways in replant diseases. Within plant hormone signal transduction pathway, plants afflicted with replant disease markedly accumulated indole-3-acetic acid and abscisic acid, correlating with high expression of their biosynthesis-related genes (SmAmidase, SmALDH, SmNCED, and SmAAOX3). Simultaneously, changes in hormone concentrations activated plant hormone signal transduction pathways. Moreover, under replant disease, metabolites in the local flavonoid metabolite biosynthetic pathway were significantly accumulated, consistent with the up-regulated gene (SmHTC1 and SmHTC2). The qRT-PCR analysis largely aligned with the transcriptomic results, confirming the trends in gene expression. Moreover, we identified 10 transcription factors co-expressed with differentially accumulated metabolites. CONCLUSIONS: Overall, we revealed the key genes and metabolites of S. miltiorrhiza under replant disease, establishing a robust foundation for future inquiries into the molecular responses to combat replant stress.

Gray matter atrophy is constrained by normal structural brain network architecture in depression.

BACKGROUND: There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression. METHODS: In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis. RESULTS: In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset. CONCLUSIONS: These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

PRMT5 Deficiency Enforces the Transcriptional and Epigenetic Programs of Klrg1+CD8+ Terminal Effector T Cells and Promotes Cancer Development.

Protein arginine methyltransferase 5 (PRMT5) participates in the symmetric dimethylation of arginine residues of proteins and contributes to a wide range of biological processes. However, how PRMT5 affects the transcriptional and epigenetic programs involved in the establishment and maintenance of T cell subset differentiation and roles in antitumor immunity is still incompletely understood. In this study, using single-cell RNA and chromatin immunoprecipitation sequencing, we found that mouse T cell-specific deletion of PRMT5 had greater effects on CD8+ than CD4+ T cell development, enforcing CD8+ T cell differentiation into Klrg1+ terminal effector cells. Mechanistically, T cell deficiency of PRMT5 activated Prdm1 by decreasing H4R3me2s and H3R8me2s deposition on its loci, which promoted the differentiation of Klrg1+CD8+ T cells. Furthermore, effector CD8+ T cells that transited to memory precursor cells were decreased in PRMT5-deficient T cells, thus causing dramatic CD8+ T cell death. In addition, in a mouse lung cancer cell line-transplanted tumor mouse model, the percentage of CD8+ T cells from T cell-specific deletion of PRMT5 mice was dramatically lost, but CD8+Foxp3+ and CD8+PDL1+ regulatory T cells were increased compared with the control group, thus accelerating tumor progression. We further verified these results in a mouse colon cancer cell line-transplanted tumor mouse model. Our study validated the importance of targeting PRMT5 in tumor treatment, because PRMT5 deficiency enforced Klrg1+ terminal CD8+ T cell development and eliminated antitumor activity.

Prmt5 deficiency inhibits CD4+ T-cell Klf2/S1pr1 expression and ameliorates EAE disease.

BACKGROUND: Protein arginine methyltransferase 5 (Prmt5) is the main type II methyltransferase, catalyzes protein arginine residue symmetric dimethylation, and modulates normal cellular physiology and disease progression. Prmt5 inhibition or deletion in CD4+ T cells has been reported to ameliorate experimental autoimmune encephalomyelitis (EAE), but the detailed molecular mechanisms have not yet been elucidated. METHODS: EAE was induced by administration of myelin oligodendrocyte glycoprotein (MOG35-55) in T cells Prmt5 conditional knockout (CD4-cre-Prmt5fl/fl, Prmt5cko) and Prmt5fl/fl (WT) mice. Flow cytometry, single-cell RNA sequencing, ATAC sequencing and chromatin immunoprecipitation assay (ChIP) approaches were used to explore the detail mechanisms. RESULTS: We find that Prmt5cko mice are resistant to EAE; infiltrating inflammatory CD4+ T cells in the central nervous system (CNS) are greatly reduced. However, in Prmt5cko mice, T cells in the spleen show much more proliferation and activation properties, the total number of CD4+ T cells in the spleen is not reduced, and the percentage of Rora+ CD4+ T cells is elevated. Also, CD4+ T cells express lower levels of S1pr1 and Klf2 than WT mice, which may influence pathogenic CD4+ T-cell egress from the spleen and migration to the CNS. Moreover, the single-cell ATAC sequence and ChIP assay reveal that the transcription factor Klf2 is enriched at the S1pr1 promoter and that Klf2 motif activity is reduced in Prmt5cko mice. CONCLUSIONS: Our study delineates the undiscovered role of Prmt5 in T-cell biology in which Prmt5 may inhibit Klf2-S1pr1 pathway to ameliorate EAE disease. Controlling T-cell Prmt5 expression may be helpful for the treatment of autoimmune diseases.

Resolving heterogeneity in depression using individualized structural covariance network analysis.

BACKGROUND: Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis. METHODS: T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges. RESULTS: As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms. CONCLUSIONS: In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis.

BACKGROUND: As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown. METHODS: To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis. RESULTS: Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus. CONCLUSIONS: Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.

Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance network analysis.

BACKGROUND: Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders. METHODS: Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed. RESULTS: Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network. CONCLUSIONS: These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

Altered time-varying local spontaneous brain activity pattern in patients with high myopia: a dynamic amplitude of low-frequency fluctuations study.

PURPOSE: To investigate the abnormal time-varying local spontaneous brain activity in patients with high myopia (HM) on the basis of the dynamic amplitude of low-frequency fluctuations (dALFF) approach. METHODS: Age and gender matching were performed based on resting-state functional magnetic resonance imaging data from 86 HM patients and 87 healthy controls (HCs). Local spontaneous brain activities were evaluated using the time-varying dALFF method. Support vector machine combined with the radial basis function kernel was used for pattern classification analysis. RESULTS: Inter-group comparison between HCs and HM patients has demonstrated that dALFF variability in the left inferior frontal gyrus (orbital part), left lingual gyrus, right anterior cingulate and paracingulate gyri, and right calcarine fissure and surrounding cortex was decreased in HM patients, while increased in the left thalamus, left paracentral lobule, and left inferior parietal (except supramarginal and angular gyri). Pattern classification between HM patients and HCs displayed a classification accuracy of 85.5%. CONCLUSION: In this study, the findings mentioned above have suggested the association between local brain activities of HM patients and abnormal variability in brain regions performing visual sensorimotor and attentional control functions. Several useful information has been provided to elucidate the mechanism-related alterations of the myopic nervous system. In addition, the significant role of abnormal dALFF variability has been highlighted to achieve an in-depth comprehension of the pathological alterations and neuroimaging mechanisms in the field of HM.

Development and validation of a nomogram for predicting metabolic-associated fatty liver disease in the Chinese physical examination population.

AIM: We aim to develop and validate a nomogram including readily available clinical and laboratory indicators to predict the risk of metabolic-associated fatty liver disease (MAFLD) in the Chinese physical examination population. METHODS: The annual physical examination data of Chinese adults from 2016 to 2020 were retrospectively analyzed. We extracted the clinical data of 138 664 subjects and randomized participants to the development and validation groups (7:3). Significant predictors associated with MAFLD were identified by using univariate and random forest analyses, and a nomogram was constructed to predict the risk of MAFLD based on a Lasso logistic model. Receiver operating characteristic curve analysis, calibration curves, and decision curve analysis were used to verify the discrimination, calibration, and clinical practicability of the nomogram, respectively. RESULTS: Ten variables were selected to establish the nomogram for predicting MAFLD risk: sex, age, waist circumference (WC), uric acid (UA), body mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting plasma glucose (FPG), triglycerides (TG), and alanine aminotransferase (ALT). The nomogram built on the nonoverfitting multivariable model showed good prediction of discrimination (AUC 0.914, 95% CI: 0.911-0.917), calibration, and clinical utility. CONCLUSIONS: This nomogram can be used as a quick screening tool to assess MAFLD risk and identify individuals at high risk of MAFLD, thus contributing to the improved management of MAFLD.

Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China.

BACKGROUND: The aggregation of lifestyle behaviours and their association with metabolic-associated fatty liver disease (MAFLD) remain unclear. We identified lifestyle patterns and investigated their association with the risk of developing MAFLD in a sample of Chinese adults who underwent annual physical examinations. METHODS: Annual physical examination data of Chinese adults from January 2016 to December 2020 were used in this study. We created a scoring system for lifestyle items combining a statistical method (multivariate analysis of variance) and clinical expertise (Delphi method). Subsequently, principal component analysis and two-step cluster analysis were implemented to derive the lifestyle patterns of men and women. Binary logistic regression analysis was used to explore the prevalence risk of MAFLD among lifestyle patterns stratified by sex. RESULTS: A total of 196,515 subjects were included in the analysis. Based on the defined lifestyle scoring system, nine and four lifestyle patterns were identified for men and women, respectively, which included "healthy or unhealthy" patterns and mixed patterns containing a combination of healthy and risky lifestyle behaviours. This study showed that subjects with an unhealthy or mixed pattern had a significantly higher risk of developing MAFLD than subjects with a relatively healthy pattern, especially among men. CONCLUSIONS: Clusters of unfavourable behaviours are more prominent in men than in women. Lifestyle patterns, as important factors influencing the development of MAFLD, show significant sex differences in the risk of MAFLD. There is a strong need for future research to develop targeted MAFLD interventions based on the identified behavioural clusters by sex stratification.

Construction and validation of a risk prediction model for delayed discharge in elderly patients with hip fracture.

BACKGROUND: Because of their poor physical state, elderly hip fracture patients commonly require prolonged hospitalization, resulting in a drop in bed circulation rate and an increased financial burden. There are currently few predictive models for delayed hospital discharge for hip fractures. This research aimed to develop the optimal model for delayed hospital discharge for hip fractures in order to support clinical decision-making. METHODS: This case-control research consisted of 1259 patients who were continuously hospitalized in the orthopedic unit of an acute hospital in Tianjin due to a fragility hip fracture between January and December 2021. Delayed discharge was defined as a hospital stay of more than 11 days. The prediction model was constructed through the use of a Cox proportional hazards regression model. Furthermore, the constructed prediction model was transformed into a nomogram. The model's performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). the STROBE checklist was used as the reporting guideline. RESULTS: The risk prediction model developed contained the Charlson Comorbidity Index (CCI), preoperative waiting time, anemia, hypoalbuminemia, and lower limbs arteriosclerosis. The AUC for the risk of delayed discharge was in the training set was 0.820 (95% CI,0.79 ~ 0.85) and 0.817 in the testing sets. The calibration revealed that the forecasted cumulative risk and observed probability of delayed discharge were quite similar. Using the risk prediction model, a higher net benefit was observed than when considered all patients were at high risk, demonstrating good clinical usefulness. CONCLUSION: Our prediction models could support policymakers in developing strategies for the optimal management of hip fracture patients, with a particular emphasis on individuals at high risk of prolonged LOS.

Nicotine addiction and overweight affect intrinsic neural activity and neurotransmitter activity: A fMRI study of interaction effects.

BACKGROUND: Nicotine addiction and overweight often co-exist, but the neurobiological mechanism of their co-morbidity remains to be clarified. In this study, we explore how nicotine addiction and overweight affect intrinsic neural activity and neurotransmitter activity. METHODS: This study included 54 overweight people and 54 age-, sex-, and handedness-matched normal-weight individuals, who were further divided into four groups based on nicotine addiction. We used a two-way factorial design to compare intrinsic neural activity (calculated by the fALFF method) in four groups based on resting-state functional magnetic resonance images (rs-fMRI). Furthermore, the correlation between fALFF values and PET- and SPECT-derived maps to examine specific neurotransmitter system changes underlying nicotine addiction and overweight. RESULTS: Nicotine addiction and overweight affect intrinsic neural activity by themselves. In combination, they showed antagonistic effects in the interactive brain regions (left insula and right precuneus). Cross-modal correlations displayed that intrinsic neural activity changes in the interactive brain regions were related to the noradrenaline system (NAT). CONCLUSION: Due to the existence of interaction, nicotine partially restored the changes of spontaneous activity in the interactive brain regions of overweight people. Therefore, when studying one factor alone, the other should be used as a control variable. Besides, this work links the noradrenaline system with intrinsic neural activity in overweight nicotine addicts. By examining the interactions between nicotine addiction and overweight from neuroimaging and molecular perspectives, this study provides some ideas for the treatment of both co-morbidities.

Abnormal voxel-wise whole-brain functional connectivity in first-episode, drug-naïve adolescents with major depression disorder.

Major depression disorder (MDD) is one of the most common psychiatric disorders. Previous studies have demonstrated structural and functional abnormalities in adult depression. However, the neurobiology of adolescent depression has not been fully understood. The aim of this study was to investigate the intrinsic dysconnectivity pattern of voxel-level whole-brain functional networks in first-episode, drug-naïve adolescents with MDD. Resting-state functional magnetic resonance imaging data were acquired from 66 depressed adolescents and 47 matched healthy controls. Voxel-wise degree centrality (DC) analysis was performed to identify voxels that showed altered whole-brain functional connectivity (FC) with other voxels. We further conducted seed-based FC analysis to investigate in more detail the connectivity patterns of the identified DC changes. The relationship between altered DC and clinical variables in depressed adolescents was also analyzed. Compared with controls, depressed adolescents showed lower DC in the bilateral hippocampus, left superior temporal gyrus and right insula. Seed-based analysis revealed that depressed adolescents, relative to controls, showed hypoconnectivity between the hippocampus to the medial prefrontal regions and right precuneus. Furthermore, the DC values in the bilateral hippocampus were correlated with the Hamilton Depression Rating Scale score and duration of disease (all P < 0.05, false discovery rate corrected). Our study indicates abnormal intrinsic dysconnectivity patterns of whole-brain functional networks in drug-naïve, first-episode adolescents with MDD, and abnormal DC in the hippocampus may affect the association of prefrontal-hippocampus circuit. These findings may provide new insights into the pathophysiology of adolescent-onset MDD.

Integrated Analysis of lncRNA-mRNA Regulatory Networks Related to Lipid Metabolism in High-Oleic-Acid Rapeseed.

A high oleic acid content is considered an essential characteristic in the breeding of high-quality rapeseed in China. Long-chain non-coding RNA (lncRNA) molecules play an important role in the plant's growth and its response to stress. To better understand the role of lncRNAs in regulating plant reproductive development, we analyzed whole-transcriptome and physiological data to characterize the dynamic changes in lncRNA expression during the four representative times of seed development of high- and low-oleic-acid rapeseed in three regions. We identified 21 and 14 lncRNA and mRNA modules, respectively. These modules were divided into three types related to region, development stages, and material. Next, we analyzed the key modules related to the oil content and the oleic acid, linoleic acid, and linolenic acid contents with physiological data and constructed the key functional network analysis on this basis. Genes related to lipid metabolism, such as 3-ketoacyl-CoA synthase 16 (KCS16) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), were present in the co-expression network, suggesting that the effect of these genes on lipid metabolism might be embodied by the expression of these lncRNAs. Our results provide a fresh insight into region-, development-stage-, and material-biased changes in lncRNA expression in the seeds of Brassica napus. Some of these lncRNAs may participate in the regulatory network of lipid accumulation and metabolism, together with regulated genes. These results may help elucidate the regulatory system of lncRNAs in the lipid metabolism of high-oleic-acid rapeseed seeds.

Tissue-Specific Transcriptome and Metabolome Analysis Reveals the Response Mechanism of Brassica napus to Waterlogging Stress.

During the growth period of rapeseed, if there is continuous rainfall, it will easily lead to waterlogging stress, which will seriously affect the growth of rapeseed. Currently, the mechanisms of rapeseed resistance to waterlogging stress are largely unknown. In this study, the rapeseed (Brassica napus) inbred lines G230 and G218 were identified as waterlogging-tolerant rapeseed and waterlogging-sensitive rapeseed, respectively, through a potted waterlogging stress simulation and field waterlogging stress experiments. After six days of waterlogging stress at the seedling stage, the degree of leaf aging and root damage of the waterlogging-tolerant rapeseed G230 were lower than those of the waterlogging-sensitive rapeseed G218. A physiological analysis showed that waterlogging stress significantly increased the contents of malondialdehyde, soluble sugar, and hydrogen peroxide in rape leaves and roots. The transcriptomic and metabolomic analysis showed that the differential genes and the differential metabolites of waterlogging-tolerant rapeseed G230 were mainly enriched in the metabolic pathways, biosynthesis of secondary metabolites, flavonoid biosynthesis, and vitamin B6 metabolism. Compared to G218, the expression levels of some genes associated with flavonoid biosynthesis and vitamin B metabolism were higher in G230, such as CHI, DRF, LDOX, PDX1.1, and PDX2. Furthermore, some metabolites involved in flavonoid biosynthesis and vitamin B6 metabolism, such as naringenin and epiafzelechin, were significantly up-regulated in leaves of G230, while pyridoxine phosphate was only significantly down-regulated in roots and leaves of G218. Furthermore, foliar spraying of vitamin B6 can effectively improve the tolerance to waterlogging of G218 in the short term. These results indicate that flavonoid biosynthesis and vitamin B6 metabolism pathways play a key role in the waterlogging tolerance and hypoxia stress resistance of Brassica napus and provide new insights for improving the waterlogging tolerance and cultivating waterlogging-tolerant rapeseed varieties.

Dual trajectory of sleep and frail in elderly people. / è€å¹´äººç¡çœ ä¸Žè¡°å¼±åŒè½¨è¿¹.

The high incidence of dual sleep and frail disorders in the elderly people, often occurring together, seriously affects the physical and mental health of the older people, effective research on the dynamics of dual sleep and frail disorders is important for improving the quality of life for the older people and responding to global ageing trend. While trajectory studies provide a unique practical scientific perspective to grasp the dynamics of development, dual trajectories unite dual barriers provide an opportunity to study the dynamic dependence of both sleep and frailty simultaneously sleep trajectories and frailty trajectories in older people are interrelated and interacted through deeper mechanisms. Therefore, it is necessary for the study not only focus on the ongoing development of health problems, but also needs to consider multiple aspects and propose targeted intervention program.

Abnormal dynamic functional connectivity in first-episode, drug-naïve adolescents with major depressive disorder.

Previous neuroimaging studies have identified disrupted large-scale functional brain networks in major depressive disorder (MDD); however, most of them focused on adult patients and were based on static functional connectivity (FC). Thus, we aimed to investigate the patterns of change in dynamic FC in depressed adolescents. Resting-state functional magnetic resonance imaging data were acquired from 60 first-episode, drug-naïve adolescents with MDD and 60 matched healthy controls (HCs). Then, the dynamic FC properties were analyzed using a sliding windows approach, k-means clustering, and graph theory methods. The intrinsic brain FC were clustered into two configuration states-a more frequent and relatively sparsely connected State 1 and a less frequent and more strongly interconnected State 2. Compared with HCs, depressed adolescents had higher reoccurrence fraction and dwell time in State 1, and lower reoccurrence fraction and dwell time in State 2, and higher total number of transitions between the two states. Depressed adolescents showed decreased FC within the default mode network (DMN) and between the DMN and other networks in State 1. Additionally, the MDD group showed higher variances in the global and local efficiency. Furthermore, the duration of illness was positively correlated with the number of state transitions, and the 17-item Hamilton Depression Rating Scale score was positively correlated with the mean dwell time in State 1. This study demonstrated abnormal dynamic FC in depressed adolescents, which provided new insights into the pathophysiological mechanisms of adolescent-onset depression.

Saccharomyces boulardii, a yeast probiotic, inhibits gut motility through upregulating intestinal serotonin transporter and modulating gut microbiota.

Saccharomyces boulardii (Sb) is a widely used fungal probiotic in treating various digestive diseases, including irritable bowel syndrome (IBS). However, the specific mechanisms of Sb relieving IBS remain unclear. The abnormal serotonin transporter (SERT) / 5-hydroxytryptamine (5-HT) system could cause disordered gastrointestinal sensation and motility, which closely related to IBS pathogenesis. The aim of this study was to explore the effects and mechanisms of Sb on regulating gut motility. Sb supernatant (SbS) was administered to intestinal epithelial cells and mice. SbS upregulated SERT expression via enhancing heparin-binding epidermal growth factor (HB-EGF) release to activate epidermal growth factor receptor (EGFR). EGFR kinase inhibitor treatment or HB-EGF siRNA transfection in cells blocked SbS upregulating SERT. Consistently, SbS-treated mice presented inhibited gut motility, and EGFR activation and SERT upregulation were found. Moreover, 16 S rDNA sequence presented an evident decrease in Firmicutes / Bacteroidetes ratio in SbS group. In genus level, SbS reduced Escherichia_Shigella, Alistipes, Clostridium XlVa, and Saccharibacteria_genera_incertae_sedis, meanwhile, increased Parasutterella. The abundance of Saccharibacteria_genera_incertae_sedis positively correlated with defecation parameters and intestinal 5-HT content. Fecal microbiota transplantation showed that SbS could modulate gut microbiota to influence gut motility. Interestingly, elimination of gut microbiota with antibiotic cocktail did not entirely block SbS regulating gut motility. Furthermore, SbS administration to IBS-D mice significantly upregulated SERT and inhibited gut motility. In conclusion, SbS could upregulate SERT by EGFR activation, and modulate gut microbiota to inhibit gut motility. This finding would provide more evidence for the application of this yeast probiotic in IBS and other diarrheal disorders.

Lactobacillus rhamnosus GG colonization in early life regulates gut-brain axis and relieves anxiety-like behavior in adulthood.

Evidence reveals that gut dysbiosis is involved in bidirectional interactions in gut-brain axis and participates in the progress of multiple disorders like anxiety. Gut microbes in early life are crucial for establishment of host health. We aimed to investigate whether early life probiotics Lactobacillus rhamnosus GG (LGG) colonization could relieve anxiety in adulthood through regulation of gut-brain axis. Live or fixed LGG was gavaged to C57BL/6 female mice from day 18 of pregnancy until natural birth, and newborn mice from day 1 to day 5 respectively. In this study, we found that live LGG could be effectively colonized in the intestine of offspring. LGG colonization increased intestinal villus length and colonic crypt depth, accompanied with barrier function protection before weaning. Microbiota composition by 16S rRNA sequencing showed that some beneficial bacteria, such as Akkermansia and Bifidobacteria, were abundant in LGG colonization group. The protective effect of LGG on gut microbiota persisted from weaning to adulthood. Intriguingly, behavioral results assessed by elevated plus mazed test and open field test demonstrated relief of anxiety-like behavior in adult LGG-colonized offspring. Mechanically, LGG colonization activated epithelial growth factor receptor (EGFR) and enhanced serotonin transporter (SERT) expression and modulated serotonergic system in the intestine, and increased brain-derived neurotrophic factor and γ-aminobutyric acid receptor levels in the hippocampus and amygdala. Blocking EGFR blunted LGG-induced the increased SERT and zonula occludens-1 expression. Collectively, early life LGG colonization could protect intestinal barrier of offspring and modulate gut-brain axis in association with relief of anxiety-like behavior in adulthood.