HBB contributes to individualized aconitine-induced cardiotoxicity in mice via interfering with ABHD5/AMPK/HDAC4 axis.

The root of Aconitum carmichaelii Debx. (Fuzi) is an herbal medicine used in China that exerts significant efficacy in rescuing patients from severe diseases. A key toxic compound in Fuzi, aconitine (AC), could trigger unpredictable cardiotoxicities with high-individualization, thus hinders safe application of Fuzi. In this study we investigated the individual differences of AC-induced cardiotoxicities, the biomarkers and underlying mechanisms. Diversity Outbred (DO) mice were used as a genetically heterogeneous model for mimicking individualization clinically. The mice were orally administered AC (0.3, 0.6, 0.9 mg· kg-1 ·d-1) for 7 d. We found that AC-triggered cardiotoxicities in DO mice shared similar characteristics to those observed in clinic patients. Most importantly, significant individual differences were found in DO mice (variation coefficients: 34.08%-53.17%). RNA-sequencing in AC-tolerant and AC-sensitive mice revealed that hemoglobin subunit beta (HBB), a toxic-responsive protein in blood with 89% homology to human, was specifically enriched in AC-sensitive mice. Moreover, we found that HBB overexpression could significantly exacerbate AC-induced cardiotoxicity while HBB knockdown markedly attenuated cell death of cardiomyocytes. We revealed that AC could trigger hemolysis, and specifically bind to HBB in cell-free hemoglobin (cf-Hb), which could excessively promote NO scavenge and decrease cardioprotective S-nitrosylation. Meanwhile, AC bound to HBB enhanced the binding of HBB to ABHD5 and AMPK, which correspondingly decreased HDAC-NT generation and led to cardiomyocytes death. This study not only demonstrates HBB achievement a novel target of AC in blood, but provides the first clue for HBB as a novel biomarker in determining the individual differences of Fuzi-triggered cardiotoxicity.

Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC). METHODS: A total of 215 tumours (129 for training and 31 for internal validation, centre 1; 55 for external validation, centre 2) were included. MIBC was confirmed by pathological examination. VI-RADS scores were provided by two groups of radiologists (readers 1 and readers 2) independently. A deep convolutional neural network was constructed in the training set, and validation was conducted on the internal and external validation sets. ROC analysis was performed to evaluate the performance for MIBC diagnosis. RESULTS: The AUCs of the DL model, readers 1, and readers 2 were as follows: in the internal validation set, 0.963, 0.843, and 0.852, respectively; in the external validation set, 0.861, 0.808, and 0.876, respectively. The accuracy of the DL model in the tumours scored VI-RADS 2 or 3 was higher than that of radiologists in the external validation set: for readers 1, 0.886 vs. 0.600, p = 0.006; for readers 2, 0.879 vs. 0.636, p = 0.021. The average processing time (38 s and 43 s in two validation sets) of the DL method was much shorter than the readers, with a reduction of over 100 s in both validation sets. CONCLUSIONS: Compared to radiologists using VI-RADS, the DL method had a better diagnostic performance, shorter processing time, and robust generalisability, indicating good potential for diagnosing MIBC. KEY POINTS: • The DL model shows robust performance for MIBC diagnosis in both internal and external validation. • The diagnostic performance of the DL model in the tumours scored VI-RADS 2 or 3 is better than that obtained by radiologists using VI-RADS. • The DL method shows potential in the preoperative assessment of MIBC.

Correlation between hypothalamic-pituitary-adrenal axis gene polymorphisms and posttraumatic stress disorder symptoms.

BACKGROUND: The hypothalamic-pituitary-adrenal (HPA) axis is the main neuroendocrine system that controls stress responses, including fear learning. To further understand the correlation between the HPA axis and stress- and fear-related symptoms in humans, the current study investigated the relationship between HPA axis gene polymorphisms and a stress- and fear-related disorder, posttraumatic stress disorder (PTSD). This is the first study that systematically investigates the correlations between HPA axis genes and distinct PTSD symptom clusters. METHODS: Participants included 1132 Chinese earthquake survivors (772 women and 360 men). PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5), and the severity (total symptoms) and symptom clusters were calculated according to the hybrid seven-factor model of DSM-5 PTSD. We genotyped eight single nucleotide polymorphisms (SNPs) of three HPA axis genes, including FKBP5, CRHR1 and CRHR2. RESULTS: The main effects of the CRHR2 SNP rs2267715 were associated with PTSD severity (P = 0.0035) and all PTSD symptom clusters except dysphoric arousal (P ranging from 0.0011 to 0.048). In women, a gene-environment interaction (G × E) effect of FKBP5 (rs3800373 × trauma exposure) was correlated with PTSD severity (P = 0.038), externalizing behaviors, anxious arousal and dysphoric arousal symptoms (P ranging from 0.014 to 0.028); the G × E effect of CRHR1 (rs4458044 × trauma exposure) was associated with anxious arousal symptoms (P = 0.016). In men, a gene-gene interaction (G × G) effect of FKBP5-CRHR1 (rs9470080 × rs4458044) was associated with PTSD severity (P = 0.0091), intrusion, negative affect, externalizing behaviors and anxious arousal (P ranging 0.012-0.049). CONCLUSION: Our results systematically revealed that the main effects and G × E and G × G effects of some genetic polymorphisms of HPA axis genes are involved in the severity and distinct symptom clusters of PTSD.

A machine learning-driven study indicates emodin improves cardiac hypertrophy by modulation of mitochondrial SIRT3 signaling.

Cardiac hypertrophy (CH) is an enormous risk factor in the process of heart failure development, however, there is still lack of effective treatment for CH. Mitochondrial protection is an effective way against CH. Rheum palmatum L. (rhubarb) has been used to treat chronic heart diseases such as heart failure, especially to inhibit cardiac compensatory enlargement. The aim of this study was to explore the pharmacodynamic component of rhubarb and reveal its pharmacological effects and targets in the treatment of CH. Based on network pharmacology and machine learning approach, ingredients of rhubarb and targets for CH were extracted and surflex docking was conducted for obtaining the optimal ingredient-target combination(s) and emodin-SIRT3 was identified for further functional analysis. Transverse aortic constriction or isoproterenol induced CH mice and phenylephrine injured cardiomyocytes were used to verify the mitochondria protection effect and CH improvement of emodin in vivo and in vitro by modulation of mitochondrial SIRT3 signaling. The results showed that emodin could block agonist-induced and pressure overload-mediated CH. Emodin prevented mitochondrial dysfunction and its underlying mechanism was attributed to the activation of SIRT3, but the effect was not obvious with the presence of SIRT3 inhibitors (3-TYP)/SIRT3 siRNA. Furthermore, PGC-1ɑ was involved in the process of emodin regulating SIRT3 signaling pathway as an upstream target. Our findings clarified the main material basis and mechanism of rhubarb in the treatment of CH. Emodin, as the major ingredient of rhubarb, has therapeutic potential for CH through mitochondrial protection due to the modulation of SIRT3 signaling.

FKBP5 Genotype Linked to Combined PTSD-Depression Symptom in Chinese Earthquake Survivors.

BACKGROUND: Post-traumatic stress disorder (PTSD) and depression are common mental disorders in individuals experiencing traumatic events. To date, few studies have studied the relationship between genetic basis and phenotypic heterogeneity of traumatized individuals. The present study examined the effects of four FKBP5 SNPs (rs1360780, rs3800373, rs9296158, and rs9470080) in four postdisaster groups (low symptom, predominantly depressive, predominantly PTSD, and combined PTSD-depression symptom groups) as identified by latent profile analysis. METHODS: A total of 1,140 adults who experienced the 2008 Wenchuan earthquake participated in our study. Earthquake-related trauma, PTSD, and depressive symptoms were measured using standard psychometric instruments. The four FKBP5 SNPs were genotyped using a custom-by-design 2 × 48-Plex SNP scan™ Kit. RESULTS: After adjusting for covariates, the main and gene-environment interaction effects of rs9470080 were all significant when the combined PTSD-depression group was compared with the low symptoms, predominantly depression and predominantly PTSD groups. rs9470080 TT genotype carriers had a higher risk of developing high co-occurring PTSD and depression symptoms than the C allele carriers. However, when trauma exposure was severe, the TT genotype carriers and C allele carriers did not differ in the risk of developing high co-occurring PTSD and depressive symptoms. The other three SNPs demonstrated no significant effects. Moreover, the rs3800373-rs9296158-rs1360780-rs9470080 haplotype A-G-C-T was found significantly associated with combined PTSD-depression symptoms. CONCLUSION: Our findings support the genetic basis of phenotypic heterogeneity in people exposed to trauma. Furthermore, the results reveal the possibility that the variants of FKBP5 gene may be associated with depression-PTSD comorbidity.

Analysis of polymorphisms of genes associated with folate-mediated one-carbon metabolism and neural tube defects in Chinese Han Population.

BACKGROUND: The polymorphism of genes involved in folate-mediated one-carbon metabolism may be a risk factor for neural tube defects (NTDs). In the present study, we aimed to investigate the single nucleotide polymorphisms (SNPs) of the genes BHMT, CUBN, FTCD, GAMT, GART, SARDH, SHMT1, and MUT, and their effect on NTDs in the Chinese Han population. METHODS: A total of 270 NTDs cases and 192 controls were enrolled in this study. The SNPs were analyzed with the next-generation sequencing method. The folate levels of brain tissues from 113 available NTDs cases and 123 available controls were measured. RESULTS: Next-generation sequencing identified 818 single nucleotide variants, including 214 SNPs used for further analysis. Statistical analysis showed that two independent SNP loci, rs2797840 and rs2073817 in SARDH, may be associated with the susceptibility of NTDs. Specifically, the minor allele G of rs2797840 was significantly associated with NTDs risk in spina bifida subgroup (p value = 0.0348). For subjects whose folate content was measured, the protective allele G of rs2797840 was significantly associated with increased folate content of brain. rs2797840 is within several ENCODE regulatory regions, indicating this SNPs may influence expression of SARDH. CONCLUSION: The SNPs rs2797840 and rs2073817 in SARDH may serve as an indicator for the occurrence of NTDs in the Chinese Han population, and rs2797840 may also be an indicator for folate content of brain.

rSNPBase: a database for curated regulatory SNPs.

In recent years, human regulatory SNPs (rSNPs) have been widely studied. Here, we present database rSNPBase, freely available at http://rsnp.psych.ac.cn/, to provide curated rSNPs that analyses the regulatory features of all SNPs in the human genome with reference to experimentally supported regulatory elements. In contrast with previous SNP functional annotation databases, rSNPBase is characterized by several unique features. (i) To improve reliability, all SNPs in rSNPBase are annotated with reference to experimentally supported regulatory elements. (ii) rSNPBase focuses on rSNPs involved in a wide range of regulation types, including proximal and distal transcriptional regulation and post-transcriptional regulation, and identifies their potentially regulated genes. (iii) Linkage disequilibrium (LD) correlations between SNPs were analysed so that the regulatory feature is annotated to SNP-set rather than a single SNP. (iv) rSNPBase provides the spatio-temporal labels and experimental eQTL labels for SNPs. In summary, rSNPBase provides more reliable, comprehensive and user-friendly regulatory annotations on rSNPs and will assist researchers in selecting candidate SNPs for further genetic studies and in exploring causal SNPs for in-depth molecular mechanisms of complex phenotypes.

ADHDgene: a genetic database for attention deficit hyperactivity disorder.

With a worldwide prevalence of ~5%, attention deficit hyperactivity disorder (ADHD) has become one of the most common psychiatric disorders. The polygenetic nature of ADHD indicates that multiple genes jointly contribute to the development of this complex disease. Studies aiming to explore genetic susceptibility of ADHD have been increasing in recent years. There is a growing need to integrate the genetic data from various genetic studies to provide a comprehensive data set and uniform access for convenience of in-depth data mining. So far, there has been no such effort for ADHD. To address the genetic complexity of ADHD, we developed the ADHDgene database by integrating ADHD-related genetic factors by profound literature reading. Based on the data from the literature, extended functional analysis, including linkage disequilibrium analysis, pathway-based analysis and gene mapping were performed to provide new insights into genetic causes of ADHD. Moreover, powerful search tools and a graphical browser were developed to facilitate the navigation of the data and data connections. As the first genetic database for ADHD, ADHDgene aims to provide researchers with a central genetic resource and analysis platform for ADHD and is freely available at http://adhd.psych.ac.cn/.

Epistasis in neurotransmitter receptors linked to posttraumatic stress disorder and major depressive disorder comorbidity in traumatized Chinese.

Background: Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) comorbidity occurs through exposure to trauma with genetic susceptibility. Neuropeptide-Y (NPY) and dopamine are neurotransmitters associated with anxiety and stress-related psychiatry through receptors. We attempted to explore the genetic association between two neurotransmitter receptor systems and the PTSD-MDD comorbidity. Methods: Four groups were identified using latent profile analysis (LPA) to examine the patterns of PTSD and MDD comorbidity among survivors exposed to earthquake-related trauma: low symptoms, predominantly depression, predominantly PTSD, and PTSD-MDD comorbidity. NPY2R (rs4425326), NPY5R (rs11724320), DRD2 (rs1079597), and DRD3 (rs6280) were genotyped from 1,140 Chinese participants exposed to earthquake-related trauma. Main, gene-environment interaction (G × E), and gene-gene interaction (G × G) effects for low symptoms, predominantly depression, and predominantly PTSD were tested using a multinomial logistic model with PTSD-MDD comorbidity as a reference. Results: The results demonstrated that compared to PTSD-MDD comorbidity, epistasis (G × G) NPY2R-DRD2 (rs4425326 × rs1079597) affects low symptoms (ß = -0.66, OR = 0.52 [95% CI: 0.32-0.84], p = 0.008, pperm = 0.008) and predominantly PTSD (ß = -0.56, OR = 0.57 [95% CI: 0.34-0.97], p = 0.037, pperm = 0.039), while NPY2R-DRD3 (rs4425326 × rs6280) impacts low symptoms (ß = 0.82, OR = 2.27 [95% CI: 1.26-4.10], p = 0.006, pperm = 0.005) and predominantly depression (ß = 1.08, R = 2.95 [95% CI: 1.55-5.62], p = 0.001, pperm = 0.001). The two G × G effects are independent. Conclusion: NPY and dopamine receptor genes are related to the genetic etiology of PTSD-MDD comorbidity, whose specific mechanisms can be studied at multiple levels.

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

Interactions between genetic variants and environmental risk factors are associated with the severity of pelvic organ prolapse.

OBJECTIVE: Both environmental and genetic risk factors contribute to pelvic organ prolapse (POP). No genome-wide study has investigated the gene-environment (G × E) interactions. In this study, we aim to identify single nucleotide polymorphisms (SNPs) that may interact with the potential environmental factors, maximum birth weight, and age in Chinese women. METHODS: We recruited 576 women for phase 1 and 264 women for phase 2 with stages III and IV prolapse from six geographic regions of China. Genomic DNAs from blood samples were genotyped using Affymetrix Axiom Genome-Wide CHB1 Array of 640,674 SNPs for phase 1 and Illumina Infinium Asian Screening Array of 743,722 SNPs for phase 2. Meta-analysis was used to combine the two results. Interactions of genetic variants with maximum birth weight and age on POP severity were identified. RESULTS: In phase 1, 502,283 SNPs in 523 women passed quality control and 450 women had complete POP-quantification measurements. In phase 2, 463,351 SNPs in 257 women passed quality control with complete POP-quantification measurements. Three SNPs rs76662748 ( WDR59 , Pmeta = 2.146 × 10 -8 ), rs149541061 ( 3p26.1 , Pmeta = 9.273 × 10 -9 ), and rs34503674 ( DOCK9 , Pmeta = 1.778 × 10 -9 ) respectively interacted with maximum birth weight, and two SNPs rs74065743 ( LINC01343 , Pmeta = 4.386 × 10 -8 ) and rs322376 ( NEURL1B - DUSP1 , Pmeta = 2.263 × 10 -8 ), respectively, interacted with age. The magnitude of disease severity associated with maximum birth weight and age differed according to genetic variants. CONCLUSIONS: This study provided preliminary evidence that interactions between genetic variants and environmental risk factors are associated with POP severity, suggesting the potential use of combining epidemiologic exposure data with selected genotyping for risk assessment and patient stratification.

Development and Evaluation of a Flexible PVDF-Based Balloon Sensor for Detecting Mechanical Forces at Key Esophageal Nodes in Esophageal Motility Disorders.

Prevailing methods for esophageal motility assessments, such as perfusion manometry and probe-based function imaging, frequently overlook the intricate stress fields acting on the liquid-filled balloons at the forefront of the probing device within the esophageal lumen. To bridge this knowledge gap, we innovatively devised an infusible flexible balloon catheter, equipped with a quartet of PVDF piezoelectric sensors. This design, working in concert with a bespoke local key-node analytical algorithm and a sensor array state analysis model, seeks to shed new light on the dynamic mechanical characteristics at pivotal esophageal locales. To further this endeavor, we pioneered a singular closed balloon system and a complementary signal acquisition and processing system that employs a homogeneously distributed PVDF piezoelectric sensor array for the real-time monitoring of dynamic mechanical nuances in the esophageal segment. An advanced analytical model was established to scrutinize the coupled physical fields under varying degrees of balloon inflation, thereby facilitating a thorough dynamic stress examination of local esophageal nodes. Our rigorous execution of static, dynamic, and simulated swallowing experiments robustly substantiated the viability of our design, the logical coherence of our esophageal key-point stress analytical algorithm, and the potential clinical utility of a flexible esophageal key-node stress detection balloon probe outfitted with a PVDF array. This study offers a fresh lens through which esophageal motility testing can be viewed and improved upon.

Machine learning and experimental screening of chromatin regulator signatures and potential drugs in hepatitis B related hepatocellular carcinoma.

Many evidences have confirmed that chromatin regulator factors (CRs) are involved in the progression of cancer, but its potential mechanism of affecting hepatitis B related hepatocellular carcinoma still needs to be studied. Our study detected the CRs that affect hepatitis B related hepatocellular carcinoma (HBV-HCC) through machine learning analysis, conducted the analysis of immune cells, constructed the relevant risk model and immune function infiltration, and predicted the potential therapeutic drugs. We found that these CRs were significantly related to the immune cells of Macrophages, B cells, CD8+T cells, etc., and PBK, AURKA, TOP2A and AURKB were the potential risk CRs of HBV-HCC. The expression levels of these four CRs increased in HepG2.2.15 cells and the liver of HBV-HCC patients, consistent with the predicted risk model. Subsequently, ten potential drugs closely related to the risk CRs were finally obtained, experimental research on resveratrol has shown that it can inhibit the proliferation of HepG2.2.15 cells and potentially inhibit the occurrence and development of HBV-HCC. Our study provides novel insights into the function of CRs in HBV-HCC and certain ideas for more accurate targeted therapy.Communicated by Ramaswamy H. Sarma.

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning.

BACKGROUND AND OBJECTIVES: Radiomics and deep learning are two popular technologies used to develop computer-aided detection and diagnosis schemes for analysing medical images. This study aimed to compare the effectiveness of radiomics, single-task deep learning (DL) and multi-task DL methods in predicting muscle-invasive bladder cancer (MIBC) status based on T2-weighted imaging (T2WI). METHODS: A total of 121 tumours (93 for training, from Centre 1; 28 for testing, from Centre 2) were included. MIBC was confirmed with pathological examination. A radiomics model, a single-task model, and a multi-task model based on T2WI were constructed in the training cohort with five-fold cross-validation, and validation was conducted in the external test cohort. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of each model. DeLong's test and a permutation test were used to compare the performance of the models. RESULTS: The area under the ROC curve (AUC) values of the radiomics, single-task and multi-task models in the training cohort were: 0.920, 0.933 and 0.932, respectively; and were 0.844, 0.884 and 0.932, respectively, in the test cohort. The multi-task model achieved better performance in the test cohort than did the other models. No statistically significant differences in AUC values and Kappa coefficients were observed between pairwise models, in either the training or test cohorts. According to the Grad-CAM feature visualization results, the multi-task model focused more on the diseased tissue area in some samples of the test cohort compared with the single-task model. CONCLUSIONS: The T2WI-based radiomics, single-task, and multi-task models all exhibited good diagnostic performance in preoperatively predicting MIBC, in which the multi-task model had the best diagnostic performance. Compared with the radiomics method, our multi-task DL method had the advantage of saving time and effort. Compared with the single-task DL method, our multi-task DL method had the advantage of being more lesion-focused and more reliable for clinical reference.

i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study.

Genome-wide association study (GWAS) is nowadays widely used to identify genes involved in human complex disease. The standard GWAS analysis examines SNPs/genes independently and identifies only a number of the most significant SNPs. It ignores the combined effect of weaker SNPs/genes, which leads to difficulties to explore biological function and mechanism from a systems point of view. Although gene set enrichment analysis (GSEA) has been introduced to GWAS to overcome these limitations by identifying the correlation between pathways/gene sets and traits, the heavy dependence on genotype data, which is not easily available for most published GWAS investigations, has led to limited application of it. In order to perform GSEA on a simple list of GWAS SNP P-values, we implemented GSEA by using SNP label permutation. We further improved GSEA (i-GSEA) by focusing on pathways/gene sets with high proportion of significant genes. To provide researchers an open platform to analyze GWAS data, we developed the i-GSEA4GWAS (improved GSEA for GWAS) web server. i-GSEA4GWAS implements the i-GSEA approach and aims to provide new insights in complex disease studies. i-GSEA4GWAS is freely available at http://gsea4gwas.psych.ac.cn/.

Common genetic variation and the control of HIV-1 in humans.

To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.

Identification of miRNA-mediated gene regulatory networks in L-methionine exposure counteracts cocaine-conditioned place preference in mice.

Background and Aims: Methionine has been proven to inhibit addictive behaviors of cocaine dependence. This study aimed to identify the potential mechanisms of MET relating to its inhibitory effects on cocaine induced cellular and behavioral changes. Methods: MRNA and miRNA high-throughput sequencing of the prefrontal cortex in a mouse model of cocaine conditioned place preference (CPP) combined with L-methionine was performed. Differentially expressed miRNAs (DE-miRNAs) and differentially expressed genes (DEGs) regulated by cocaine and inhibited by L-methionine were identified. DEGs were mapped to STRING database to construct a protein-protein interaction (PPI) network. Then, the identified DEGs were subjected to the DAVID webserver for functional annotation. Finally, miRNA-mRNA regulatory network and miRNA-mRNA-TF regulatory networks were established to screen key DE-miRNAs and coregulation network in Cytoscape. Results: Sequencing data analysis showed that L-methionine reversely regulated genes and miRNAs affected by cocaine. Pathways associated with drug addiction only enriched in CS-down with MC-up genes targeted by DE-miRNAs including GABAergic synapse, Glutamatergic synapse, Circadian entrainment, Axon guidance and Calcium signaling pathway. Drug addiction associated network was formed of 22 DEGs including calcium channel (Cacna1c, Cacna1e, Cacna1g and Cacng8), ephrin receptor genes (Ephb6 and Epha8) and ryanodine receptor genes (Ryr1 and Ryr2). Calcium channel gene network were identified as a core gene network modulated by L-methionine in response to cocaine dependence. Moreover, it was predicted that Grin1 and Fosb presented in TF-miRNA-mRNA coregulation network with a high degree of interaction as hub genes and interacted calcium channels. Conclusion: These identified key genes, miRNA and coregulation network demonstrated the efficacy of L-methionine in counteracting the effects of cocaine CPP. To a certain degree, it may provide some hints to better understand the underlying mechanism on L-methionine in response to cocaine abuse.

The main effect and gene-environment interaction effect of the ADCYAP1R1 polymorphism rs2267735 on the course of posttraumatic stress disorder symptoms-A longitudinal analysis.

Background: Many studies have been performed to investigate the association between the ADCYAP1R1 polymorphism rs2267735 and posttraumatic stress disorder (PTSD), but the results have been inconsistent, and the way in which this gene affects the course of PTSD has not been widely investigated. Thus, a longitudinal study of the course (development trajectory) of PTSD is needed. Methods: In this study, we performed a longitudinal analysis of rs2267735 in 1017 young, trauma-exposed Chinese people (549 females and 468 males, ranging from 7 to 11 years old). At four time points after trauma exposure (2.5, 3.5, 4.5, and 5.5 years), we measured PTSD symptoms with the University of California, Los Angeles PTSD Reaction Index (PTSD-RI) for DSM-IV (Child Version). We employed a latent growth model (LGM) for the longitudinal data to test the association between rs2267735 (main and gene-environment interaction effects) and the course of PTSD symptoms. Results: The results of LGM showed that the gene-environment interaction (rs2267735 × trauma exposure) effects were associated with PTSD symptoms in girls at 2.5 years (ß = -0.291 and P = 0.013 for LGM intercept). The gene-environment interaction (rs2267735 × trauma exposure) effect was also correlated with PTSD symptoms in girls at 3.5 and 4.5 years (ß = -0.264 and P = 0.005; ß = -0.217 and P = 0.013). Conclusion: Our study revealed that the gene-environment interaction of the ADCYAP1R1 polymorphism rs2267735 is associated with PTSD symptoms in girls at 2.5 years and that the effects may be stable over time and not related to the PTSD symptom recovery rate. This is the first study to detect the how the ADCYAP1R1 gene affects the course of PTSD after trauma exposure in a longitudinal view.

Artificial Intelligence Uncovers Natural MMP Inhibitor Crocin as a Potential Treatment of Thoracic Aortic Aneurysm and Dissection.

Thoracic aortic aneurysm and dissection (TAAD) is a lethal cardiovascular condition without effective pharmaceutical therapy. Identifying novel drugs that target the key pathogenetic components is an urgent need. Bioinformatics analysis of pathological studies indicated "extracellular matrix organization" as the most significant functional pathway related to TAAD, in which matrix metallopeptidase (MMP) 2 and MMP9 ranked above other proteases. MMP1-14 were designated as the prototype molecules for docking against PubChem Compound Database using Surflex-Dock, and nine natural compounds were identified. Using a generic MMP activity assay and an aminopropionitrile (BAPN)-induced TAAD mouse model, we identified crocin as an effective MMP inhibitor, suppressing the occurrence and rupture of TAAD. Biolayer interferometry and AI/bioinformatics analyses indicated that crocin may inhibit MMP2 activity by direct binding. Possible binding sites were investigated. Overall, the integration of artificial intelligence and functional experiments identified crocin as an MMP inhibitor with strong therapeutic potential.

Systematic evaluation of genome-wide methylated DNA enrichment using a CpG island array.

BACKGROUND: Recent progress in high-throughput technologies has greatly contributed to the development of DNA methylation profiling. Although there are several reports that describe methylome detection of whole genome bisulfite sequencing, the high cost and heavy demand on bioinformatics analysis prevents its extensive application. Thus, current strategies for the study of mammalian DNA methylomes is still based primarily on genome-wide methylated DNA enrichment combined with DNA microarray detection or sequencing. Methylated DNA enrichment is a key step in a microarray based genome-wide methylation profiling study, and even for future high-throughput sequencing based methylome analysis. RESULTS: In order to evaluate the sensitivity and accuracy of methylated DNA enrichment, we investigated and optimized a number of important parameters to improve the performance of several enrichment assays, including differential methylation hybridization (DMH), microarray-based methylation assessment of single samples (MMASS), and methylated DNA immunoprecipitation (MeDIP). With advantages and disadvantages unique to each approach, we found that assays based on methylation-sensitive enzyme digestion and those based on immunoprecipitation detected different methylated DNA fragments, indicating that they are complementary in their relative ability to detect methylation differences. CONCLUSIONS: Our study provides the first comprehensive evaluation for widely used methodologies for methylated DNA enrichment, and could be helpful for developing a cost effective approach for DNA methylation profiling.