Integrated evaluation of the biological response of the earthworm Eisenia fetida using two glyphosate exposure strategies: soil enriched and soils collected from crops in Southeastern Mexico

Under laboratory conditions, the toxicological effects of pesticides tend to be less variable and realistic than under field conditions, limiting their usefulness in environmental risk assessment. In the current study, the earthworm Eisenia fetida was selected as a bioindicator for assessing glyphosate toxic effects in two different trials to solve this dilemma. In Trial 1, the worms were exposed for 7 and 14 days to concentrations of a commercial glyphosate formulation (1 to 500 mg a.i. kg-1) currently used in the field. In Trial 2, the worms were kept in nine soils collected from different plots with crops for 14 days of exposure. In both experiments, glutathione S-transferase (GST), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and acetylcholinesterase (AChE) activities and contents of lipid peroxidation (LPO) were evaluated. In T1, the glyphosate formulation produced a 40% inhibition of AChE activity and a significant increase in GST, SOD, CAT, and GPx activities and LPO contents in E. fetida on day 7. In T2, higher concentrations of glyphosate were detected in the soils of soybean, papaya, and corn (0.92, 0.87, and 0.85 mg kg-1), which induced a positive correlation between the levels of glyphosate residues with GST, SOD, CAT, GPx, and LPO and a negative correlation with AChE. These findings indicate that crop soils polluted with glyphosate elicited higher oxidative stress than under laboratory conditions, confirmed by IBRv2, PCA, and AHC analyses.

Bioinformatics analysis of a disease-specific lncRNA-miRNA-mRNA regulatory network in recurrent spontaneous abortion (RSA)

BACKGROUND

This study investigated the molecular mechanisms of long non-coding RNAs (lncRNAs) in RSA using the lncRNA-miRNA-mRNA regulatory network.

METHODS

The present study obtained expression datasets of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) from blood samples of individuals with unexplained recurrent spontaneous abortion (RSA) and healthy controls. Differentially expressed lncRNAs (DELs), mRNAs (DEMs), and miRNAs (DEmiRs) were identified. A regulatory network comprising lncRNA, miRNA, and mRNA was constructed, and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEM. Also, a protein-protein interaction (PPI) network was made and key genes were identified.

RESULTS

A total of 57 DELs, 212 DEmiRs, and 301 DEMs regarding RSA were identified. Later analysis revealed a lncRNA-miRNA-mRNA network comprising nine lncRNAs, 14 miRNAs, and 65 mRNAs. Then, the ceRNA network genes were subjected to functional enrichment and pathway analysis, which showed their association with various processes, such as cortisol and thyroid hormone synthesis and secretion, human cytomegalovirus infection, and parathyroid hormone synthesis. In addition, ten hub genes (ITGB3, GNAI2, GNAS, SRC, PLEC, CDC42, RHOA, RAC1, CTNND1, and FN1) were identified based on the PPI network results.

CONCLUSION

In summary, the outcomes of our study provided some data regarding the alteration genes involved in RSA pathogenic mechanism via the lncRNA-miRNA-mRNA network and reveal the possibility of identifying new lncRNAs and miRNAs as promising molecular biomarkers.

Alterations of gut microbiota and its correlation with the liver metabolome in the process of ameliorating Parkinson's disease with Buyang Huanwu decoction

ETHNOPHARMACOLOGICAL RELEVANCE

Buyang Huanwu decoction (BHD), a famous traditional Chinese medicine (TCM) formula, was first recorded in Qing Dynasty physician Qingren Wang's Yi Lin Gai Cuo. BHD has been widely utilized in the treatment of patients with neurological disorders, including Parkinson's disease (PD). However, the underlying mechanism has not been fully elucidated. In particular, little is known about the role of gut microbiota.

AIM OF THE STUDY

We aimed to reveal the alterations and functions of gut microbiota and its correlation with the liver metabolome in the process of improving PD with BHD.

MATERIALS AND METHODS

The cecal contents were collected from PD mice treated with or without BHD. 16S rRNA gene sequencing was performed on an Illumina MiSeq-PE250 platform, and the ecological structure, dominant taxa, co-occurrence patterns, and function prediction of the gut microbial community were analyzed by multivariate statistical methods. The correlation between differential microbial communities in the gut and differentially accumulated metabolites in the liver was analyzed using Spearman's correlation analysis.

RESULTS

The abundance of Butyricimonas, Christensenellaceae, Coprococcus, Peptococcaceae, Odoribacteraceae, and Roseburia was altered significantly in the model group, which was by BHD. Ten genera, namely Dorea, unclassified_Lachnospiraceae, Oscillospira, unidentified_Ruminococcaceae, unclassified_Clostridiales, unidentified_Clostridiales, Bacteroides, unclassified_Prevotellaceae, unidentified_Rikenellaceae, and unidentified_S24-7, were identified as key bacterial communities. According to the function prediction of differential genera, the mRNA surveillance pathway might be a target of BHD. Integrated analysis of gut microbiota and the liver metabolome revealed that several gut microbiota genera such as Parabacteroides, Ochrobactrum, Acinetobacter, Clostridium, and Halomonas, were positively or negatively correlated with some nervous system-related metabolites, such as L-carnitine, L-pyroglutamic acid, oleic acid, and taurine.

CONCLUSIONS

Gut microbiota might be a target of BHD in the process of ameliorating PD. Our findings provide novel insight into the mechanisms underlying the effects of BHD on PD and contribute to the development of TCM.

Liver proteomics analysis reveals the differentiation of lipid mechanism and antioxidant enzyme activity during chicken embryonic development

Chicken embryo development is a dynamic process. However, no detailed information is available about the protein abundance changes associated with the lipid mechanism and antioxidant enzyme activity during the egg embryo development. Thus, in the present study, an TMT-based proteomic approach was used to quantify protein abundance changes at different stages of chicken embryonic development. A total of 289 significantly differentially abundant hepatic proteins were quantified, of which 180 were upregulated and 109 were downregulated in the comparison of Day 20 with Day 12 in chicken embryos. Pathway analysis showed that metabolic pathways were the most highly enriched pathways, followed by arachidonic acid metabolism and steroid biosynthesis. Integration of proteomic-based studies profiling of three incubation stages revealed that the two compare groups (Day 12 vs Day 20 and Day 16 vs Day 20) shared some key differentially abundant proteins (DAPs), including LBFABP, FABP5, CYP4V2, PDCD4, LAL, APOA1, APOA4, SAA, FABP2, ACBSG2, FABP2, CYP51A1, and FBXO9. The STRING database and GO analysis results showed that there was close connectivity between APOA4, LBFABP, SERPINC1, APOA1, FGB, FGA, ANGPTL3 and these proteins were involved in the oxidation-reduction process, lipid transport, iron ion, heme, and lipid binding. Importantly, APOA4, FABP2, and CYP51A1 might be key factors to control fat deposition and antioxidant enzyme activity during chicken embryonic development. These findings will facilitate a better understanding of antioxidant and lipid mechanisms in chicken embryo and these DAPs can be further investigated as candidate markers to predict lipid deposition and the activity of antioxidant enzymes.

Identifying Key Genes to the Early Diagnosis of Inflammatory Bowel Disease by Integrating Analysis at the Blood and Tissue Levels

Background

Inflammatory bowel disease (IBD) encompasses Crohn's disease (CD) and ulcerative colitis (UC), is challenging to diagnose, and frequently relapses, significantly affecting patients' quality of life. Despite extensive efforts, the pathogenesis of IBD remains unclear.

Methods

In this study, we integrated bioinformatics analysis and animal disease model to investigate IBD from two dimensions to identify potential diagnostic biomarkers and explore the pathogenesis of distinct conditions at tissue-specific levels.

Results

Firstly, we identified dysferlin (DYSF) and C-X-C motif chemokine ligand 2 (CXCL2) as crucial biomarkers for IBD, with 11 and 13 putative biomarkers for CD and UC, respectively, identified by peripheral blood testing only. CXCL8 and S100 calcium-binding protein A8 (S100A8) were determined to be critical hub genes and validated by real-time polymerase chain reaction (RT-PCR). Secondly, in CD, the differentially expressed genes (DEGs) were mainly associated with immunity based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, while the metabolism of multiple substances and substance transport activity were dominant in UC. Thirdly, essential genes in the pathological progression of CD and UC were identified through protein-protein interaction networks and molecular complex detection (MCODE) analysis. Finally, pathological examination and quantitative analysis of IBD models confirmed the above results.

Conclusions

Our findings could contribute to understanding the molecular mechanism of IBD, hold clinical significance for early diagnosis and prevention, and provide effective targets for treating IBD.

18-Month efficacy and safety analysis of monthly subcutaneous buprenorphine injection for opioid use disorder: Integrated analysis of phase 3 studies

BACKGROUND

Few studies investigate the natural history of patients on long-term treatment for opioid use disorder (OUD). We evaluated the long-term efficacy, safety, and tolerability experience of monthly extended-release buprenorphine (BUP-XR) in participants seeking treatment for OUD, via integrated analysis of phase 3 studies.

METHODS

Study 1 was a 24-week randomized, double-blind, placebo-controlled trial of participants receiving monthly injections of BUP-XR (300 mg × 2, 100 mg × 4 [n = 203] or 300 mg × 6 [n = 201]) or placebo (n = 100). Study 2 was a 48-week, open-label trial enrolling 257 participants who completed study 1 and 412 de novo participants, to receive 6 and 12 BUP-XR injections, respectively. Study 3 was a 24-week, open-label extension enrolling 208 participants who completed study 2 for 6 additional injections. We assessed opioid abstinence as the proportion of urine opioid negative participants by visit and the percentage of each participant's negative opioid assessments during the first 6 months.

RESULTS

In total, 916 participants were treated with BUP-XR or placebo. By the end of 18 months, 92.7 % of the de novo cohort and 81.8 % of the study 1 cohort were urine negative for opioids. Among early nonresponders (percentage of abstinence ≤20 %), 73.1 % were urine negative after 18 months. The longer treatment period was well tolerated, with no new safety concerns, and a low incidence of opioid withdrawal signs and symptoms, and hepatic disorder.

CONCLUSIONS

Extending BUP-XR treatment beyond 6 months sustained improvement in opioid abstinence and was well tolerated, supporting clinical benefit up to 18 months.

TRIAL REGISTRATION

NCT02357901 (study 1); NCT02510014 (study 2); NCT02896296 (study 3).

Integrated analysis of comorbidity, pregnant outcomes, and amniotic fluid cytogenetics of fetuses with persistent left superior vena cava

BACKGROUND

Persistent left superior vena cava (PLSVC) is the most common venous system variant. The clinical characteristics and amniotic fluid cytogenetics of fetuses with PLSVC remain to be further explored.

AIM

To develop reliable prenatal diagnostic recommendations through integrated analysis of the clinical characteristics of fetuses with PLSVC.

METHODS

Cases of PLSVC diagnosed using prenatal ultrasonography between September 2019 and November 2022 were retrospectively studied. The clinical characteristics of the pregnant women, ultrasonic imaging information, gestational age at diagnosis, pregnancy outcomes, and amniocentesis results were summarized and analyzed using categorical statistics and the chi-square test or Fisher's exact test.

RESULTS

Of the 97 cases diagnosed by prenatal ultrasound, 49 (50.5%) had isolated PLSVC and 48 (49.5%) had other structural abnormalities. The differences in pregnancy outcomes and amniocentesis conditions between the two groups were statistically significant (P < 0.05). No significant differences were identified between the two groups in terms of advanced maternal age and gestational age (P > 0.05). According to the results of the classification statistics, the most common intracardiac abnormality was a ventricular septal defect and the most common extracardiac abnormality was a single umbilical artery. In the subgroup analysis, the concurrent combination of intra- and extracardiac structural abnormalities was a risk factor for adverse pregnancy outcomes (odds ratio > 1, P < 0.05). Additionally, all abnormal cytogenetic findings on amniocentesis were observed in the comorbidity group. One case was diagnosed with 21-trisomy and six cases was diagnosed with chromosome segment duplication.

CONCLUSION

Examination for other structural abnormalities is strongly recommended when PLSVC is diagnosed. Poorer pregnancy outcomes and increased amniocentesis were observed in PLSVC cases with other structural abnormalities. Amniotic fluid cytogenetics of fetuses is recommended for PLSVC with other structural abnormalities.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Integrated analysis of metabolomic and transcriptomic profiling reveals the effect of Buyang Huanwu decoction on Parkinson's disease in mice

BACKGROUND

Parkinson's disease (PD) is a common, complex, and chronic neurodegenerative disorder involved in multi-system. At present, medicine for PD has many limitations. Buyang Huanwu decoction (BHD), a famous traditional Chinese medicinal (TCM) formulae, is used in the treatment of PD clinically in China. However, the therapeutic mechanism is still unknown.

PURPOSE

We aimed to explore the pharmacological mechanism of BHD alleviating PD through an integrated liver metabolome and brain transcriptome analysis.

METHODS

The mice with PD were induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Behavioral tests and immunohistochemistry were used to evaluate the neuroprotective effects of BHD. The non-targeted metabolomics analysis was conducted to profile differentially accumulated metabolites (DAMs) in the liver using a UHPLC-Q-Exactive MS/MS method. The differentially expressed genes (DEGs) in the brain were investigated by transcriptomic analysis on an Illumina sequencing platform. The correlations of DAMs and DEGs were investigated using an integrated metabolomic and transcriptomic approach.

RESULTS

The results of behavioral tests and immunohistochemistry proved the alleviated effects of BHD on PD symptoms. A total of 14 and 36 DAMs were detected in the groups treated with low- (L group) and high-dose (H group) BHD respectively under the positive ion mode. Compared with the PD model group (M group), three enriched pathways including metabolic pathways, ABC transporters, and biosynthesis of amino acids were common in the L and H group. Transcriptomic analysis proved that BHD could regulate the expression of numerous genes, some of which were targeted by Ben-Ldopa such as Creb5, Gm45623, Ccer2, Cd180, Fosl2, Crip3, and Noxred1. Based on the integrated metabolomic and transcriptomic analysis, 7 metabolite-gene pairs were found in four comparisons, including C vs M, M vs P, M vs L, and M vs H, and 6 enriched pathways containing purine metabolism, glycine/serine/threonine metabolism, phenylalanine metabolism, carbon fixation in photosynthetic organisms, thiamine metabolism, and ABC transporters were overlapped.

CONCLUSIONS

Though the underlying pharmacological mechanism of BHD is still lacking, we provided evidence that BHD could improve dopaminergic neurons in MPTP-induced PD mice by regulating liver metabolism and brain transcriptome. The correlation between the liver and the brain was preliminarily revealed in this study.

ALS is imprinted in the chromatin accessibility of blood cells

Amyotrophic Lateral Sclerosis (ALS) is a complex and incurable neurodegenerative disorder in which genetic and epigenetic factors contribute to the pathogenesis of all forms of ALS. The interplay of genetic predisposition and environmental footprints generates epigenetic signatures in the cells of affected tissues, which then alter transcriptional programs. Epigenetic modifications that arise from genetic predisposition and systemic environmental footprints should in theory be detectable not only in affected CNS tissue but also in the periphery. Here, we identify an ALS-associated epigenetic signature ('epiChromALS') by chromatin accessibility analysis of blood cells of ALS patients. In contrast to the blood transcriptome signature, epiChromALS includes also genes that are not expressed in blood cells; it is enriched in CNS neuronal pathways and it is present in the ALS motor cortex. By combining simultaneous ATAC-seq and RNA-seq with single-cell sequencing in PBMCs and motor cortex from ALS patients, we demonstrate that epigenetic changes associated with the neurodegenerative disease can be found in the periphery, thus strongly suggesting a mechanistic link between the epigenetic regulation and disease pathogenesis.

Diagnostic signature composed of seven genes in HIF-1 signaling pathway for preeclampsia

PURPOSE

In this study, we explored the relationship of genes in HIF-1 signaling pathway with preeclampsia and establish a logistic regression model for diagnose preeclampsia using bioinformatics analysis.

METHOD

Two microarray datasets GSE75010 and GSE35574 were downloaded from the Gene Expression Omnibus database, which was using for differential expression analysis. DEGs were performed the Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene set enrichment analysis (GSEA). Then we performed unsupervised consensus clustering analysis using genes in HIF-1 signaling pathway, and clinical features and immune cell infiltration were compared between these clusters, as well as the least absolute shrinkage and selection operator (LASSO) method to screened out key genes to constructed logistic regression model, and receiver operating characteristic (ROC) curve was plotted to evaluate the accuracy of the model.

RESULTS

57 DEGs were identified, of which GO, KEGG and analysis GSEA showed DEGs were mostly involved in HIF-1 signaling pathway. Two subtypes were identified of preeclampsia and 7 genes in HIF1-signaling pathway were screened out to establish the logistic regression model for discrimination preeclampsia from controls, of which the AUC are 0.923 and 0.845 in training and validation datasets respectively.

CONCLUSION

Seven genes (including MKNK1, ARNT, FLT1, SERPINE1, ENO3, LDHA, BCL2) were screen out to build potential diagnostic model of preeclampsia.

Constructing a seventeen-gene signature model for non-obstructive azoospermia based on integrated transcriptome analyses and WGCNA

BACKGROUND

Non-obstructive azoospermia (NOA) affects approximately 1% of the male population worldwide. The underlying mechanism and gene transcription remain unclear. This study aims to explore the potential pathogenesis for the detection and management of NOA.

METHODS

Based on four microarray datasets from the Gene Expression Omnibus database, integrated analysis and weighted correlation network analysis (WGCNA) were used to obtain the intersected common differentially expressed genes (DESs). Differential signaling pathways were identified via GO and GSVA-KEGG analyses. We constructed a seventeen-gene signature model using least absolute shrinkage and selection operation (LASSO) regression, and validated its efficacy in another two GEO datasets. Three patients with NOA and three patients with obstructive azoospermia were recruited. The mRNA levels of seven key genes were measured in testicular samples, and the gene expression profile was evaluated in the Human Protein Atlas (HPA) database.

RESULTS

In total, 388 upregulated and 795 downregulated common DEGs were identified between the NOA and control groups. ATPase activity, tubulin binding, microtubule binding, and metabolism- and immune-associated signaling pathways were significantly enriched. A seventeen-gene signature predictive model was constructed, and receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) values were 1.000 (training group), 0.901 (testing group), and 0.940 (validation set). The AUCs of seven key genes (REC8, CPS1, DHX57, RRS1, GSTA4, SI, and COX7B) were all > 0.8 in both the testing group and the validation set. The qRT-PCR results showed that consistent with the sequencing data, the mRNA levels of RRS1, GSTA4, and COX7B were upregulated, while CPS1, DHX57, and SI were downregulated in NOA. Four genes (CPS1, DHX57, RRS1, and SI) showed significant differences. Expression data from the HPA database showed the localization characteristics and trajectories of seven key genes in spermatogenic cells, Sertoli cells, and Leydig cells.

CONCLUSIONS

Our findings suggest a novel seventeen-gene signature model with a favorable predictive power, and identify seven key genes with potential as NOA-associated marker genes. Our study provides a new perspective for exploring the underlying pathological mechanism in male infertility.

Exploratory integrated analysis of circulating exosomal miRNA and tissue mRNA related to long-term physical activity for more than 25 years: a bioinformatics study

Physical activity exerts various positive effects on both physical and mental health. Although the comprehensive expression profiles of each microRNA (miRNA) or messenger RNA (mRNA) related to physical activity have already been reported, the association between miRNA and mRNA remains unclear. Here, the integrated study was conducted to comprehensively explore the potential miRNA-mRNA relationships related to long-term physical activity over 25 years. Genome-wide public deposited mRNA expression data of adipose tissue (GSE20536) from six same-sex twin pairs (no information regarding gender) and of skeletal muscle tissue (GSE20319) from ten same-sex twin pairs (four female twin pairs) were used, and differentially expressed mRNAs (DEMs) related to discordant leisure-time physical activity for 30 years were identified using GEO2R. Overlapped mRNAs between DEMs and predicted possible target mRNAs, based on a previous study and TargetScan tool, were then identified and used as long-term physical activity-related mRNAs targeted by miRNAs. In adipose tissue, 36 mRNAs and 42 mRNAs were identified as upregulated or downregulated DEMs, respectively. Based on the results of the overlapped analysis between DEMs and predicted possible target mRNAs targeted by miRNAs, 15 upregulated mRNAs, including NDRG4, FAM13A, ST3GAL6, and AFF1, and 10 downregulated mRNAs, including RPL14, LBP, and GLRX, were identified. In muscle tissue, three downregulated mRNAs overlapped with the predicted target mRNAs targeted by miRNAs. Fifteen upregulated mRNAs in adipose tissue showed a tendency to enrich in "Cardiovascular" in GAD_DISEASE_CLASS category. Potential miRNA-mRNA relationships related to long-term physical activity over 25 years were identified through bioinformatics analysis.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Integrated analysis of transcriptomics and metabolomics in human hepatocellular carcinoma HepG2215 cells after YAP1 knockdown

Yes-associated protein 1 (YAP1) plays a critical role in hepatocellular carcinoma (HCC). Inhibition of YAP1 expression suppresses HCC progression, but the underlying mechanism is still unclear. In this study, we studied the effects and molecular mechanisms of YAP1 knockdown on the growth and metabolism in human HCC HepG2215 cells. Inhibition of YAP1 expression inhibits the proliferation and metastasis in HepG2215 cells, and differentially expressed genes (DEGs) and metabolites were identified in shYAP1-HepG2215 cells. Further, 805 DEGs, mainly associated with metabolism and particularly lipid metabolism, were identified by transcriptome sequencing analyses in shYAP1-HepG2215 cells. YAP1 knockdown increased albumin (ALB) levels by Protein-protein interaction (PPI) network analyses in HepG2215 cells. Metabolomic profiling identified 37 metabolites with significant differences in the shYAP1 group, and amino acid metabolism generally decreased in the shYAP1 group. Comprehensive analysis of transcriptomics and metabolomics revealed that the ATP-binding cassette (ABC) transporters play a central role after YAP1 knockdown in HepG2215 cells. Therefore, YAP1 knockdown inhibited HCC growth, which affected the metabolism of lipids and amino acids by regulating the expression of ALB and ABC transporters in HepG2215 cells.

An integrated approach for sediment characterization of Dead Sea, Israel: Implications to marine environment

The Dead Sea (DS) sediment samples from two different sites on the west coast were analyzed. The objective is to document sediment characterization in order to study the interrelation existing among ingredients. The analyses show that Fe, Mg and Zn are the most significant trace elements found in the Sediment. Anthropogenic activities such as Industries, untreated sewage, agricultural wastes are some of the pollution sources that are considered to be lethal to the marine ecosystem. The DS is slowly disappearing at an alarming rate of 1 m/year. Hence a constant and precise mitigation, monitoring and management is mandatory. The present work is part of such goal in order to understand the health of the DS ecosystem. A cumulative and consistent effort of the Governments, stakeholders, tourists and the public will help in order to preserve and protect the health of the rare DS marine ecosystem for future generations.

Interannual variability of heat waves over the Korean Peninsula based on integrated approach

Heat waves can provide detrimental impacts on human society and the environmental system, and thus have received substantial attention in scientific research. Since heat waves are relevant to a wide range of stakeholders, definitions for heat wave events vary in terms of threshold values, durations, and utilized variables. While there is a value in this diversity of perspectives, the various definitions often complicate the assessment of heat wave risk, thereby underscoring the improved utility of a unified definition. In this study, we examine the interannual variability of heat wave patterns by using a proposed copula-based framework. From five observed temperature-related variables, this study first evaluates the individual changes of fifteen previously published heat wave indices focused on heat wave events across the Korean Peninsula for the last 49 years (1973-2021). We then extract the integrated signals to understand the overall trend patterns using the multiple heat wave indices. Results indicate that different heat wave definitions present distinctive attributes (e.g., in the magnitude of temporal changes) depending on the locations, implying that the diversity of heat wave definitions leads to potentially inconsistent conclusions. Using the integrated analysis, we identify that the expected heat wave day has increased across the majority of the regions in the Korean Peninsula. To be specific, substantial increases are shown in North Korea, while rapid increases in heat wave events have been observed after the year 2010 over South Korea. Finally, through the sensitivity analysis, we demonstrate the importance of choosing the heat wave definition in the integrated analysis.

Association of heat shock protein 8 with atopic march in a murine experimental model

Background

Atopic march (AM), a unique characteristic of allergic diseases, refers to the sequential progression of atopic dermatitis (AD) in infants to allergic asthma and allergic rhinitis in children and young adults, respectively. Although there are several studies on AM, the establishment of an AM murine model to expand our understanding of the underlying mechanism and to identify the potential biomarkers is yet to be achieved. In this study, an improved murine model was established by applying a method to minimize skin irritation in inducing AD, and it was used to perform integrated analyses to discover candidate biomarkers.

Methods

To induce atopic dermatitis, 2,4-dinitrochlorobenzene (DNCB) was applied to the ear skin once a week, and this was continued for 5 weeks. From the second application of DNCB, Dermatophagoides pteronyssinus (Dp) extract was applied topically 2 days after each DNCB application; this was continued for 4 weeks. Dp sensitization and intranasal challenges were then performed for 4 weeks to develop conditions mimicking AM.

Results

Exacerbated airway inflammation and allergic responses observed in the AM-induced group suggested successful AM development in our model. Two-dimensional gel electrophoresis (2-DE) and mass spectrometry analysis identified 753 candidate proteins from 124 2-DE spots differentially expressed among the experimental groups. Functional analyses, such as Gene Ontology (GO) annotation and protein-protein interaction (PPI) analysis were conducted to investigate the relationship among the candidate proteins. Seventy-two GO terms were significant between the two groups; heat shock protein 8 (Hspa8) was found to be included in six of the top 10 GO terms. Hspa8 scored high on the PPI parameters as well.

Conclusion

We established an improved murine model for AM and proposed Hspa8 as a candidate biomarker for AM.

Identification of novel genes in Behcet's disease using integrated bioinformatic analysis

Behcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein–protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD.

Irinotecan plus temozolomide in relapsed Ewing sarcoma: an integrated analysis of retrospective studies

BACKGROUND

The prognosis of patients with relapsed Ewing sarcoma is poor. In this study, we aimed to pooled-analyze the efficacy and safety of the combination of irinotecan and temozolomide in treating patients with relapsed Ewing sarcoma.

METHODS

PubMed, Cochrane CENTRAL, Web of Science, and EMBASE were systematically searched on September 27, 2021. The primary outcomes were rates of objective response and disease control, and the secondary outcomes were toxicities.

RESULTS

Six retrospective studies with 184 patients were enrolled in the analysis. The median age ranged from 14 to 21. The integrated rates were 44% (95% confidence interval [CI] 31-58) for objective response and 66% (55-77) for disease control. Grade 3-4 neutropenia, thrombocytopenia, and diarrhea occurred in 8% (3-16), 7% (3-11), and 8% (5-10) of chemotherapeutic cycles, respectively. 18% (7-32) and 6% (2-11) of patients suffered grade 3-4 neutropenia and thrombocytopenia after irinotecan plus temozolomide treatment.

CONCLUSION

Irinotecan plus temozolomide combination chemotherapy showed antitumor activity and an acceptable safety profile in patients with relapsed Ewing sarcoma. More future prospective studies are needed to confirm the retrospective results.

Integrated proteome and lipidome analysis of naturally aged safflower seeds varying in vitality

Seed ageing has an important effect on germination and productivity. During natural ageing, seed vigour decreases rapidly but, to date, the molecular mechanisms underlying this decrease have not been fully elucidated. Using omics, some of the details regarding seed vigour decline during natural ageing might be elucidated through integrated analysis. Safflower seed germination and physio-biochemical changes during natural ageing (stored for 4, 16 and 28 months) were determined. Proteome and lipidome profiling during natural seed ageing was performed, and the differentially expressed proteins and lipid metabolite species analysed. The surface and internal structures of cotyledons were observed. An integrating analysis of the proteome and lipidome was also carried out. Natural seed ageing significantly decreased safflower seed germination and vigour. 4,184 proteins and 1,193 lipids were quantified, both of which show huge differences among the different naturally aged seeds. The surface of the cotyledons collapsed and cracked, and the oil bodies become looser during natural ageing. The total content of DAG and PA increased, while the content of TAG and PL (PC, PE, PS, PI and PL) significantly decreased during seeds ageing. Two lipase genes (HH-026818-RA and HH-025320) likely participated in this degradation of lipids. We conclude that the enzymes that participate in glycerolipid metabolism and fatty acid degradation probably lead to the degradation of oil bodies (TAG) and membrane lipids (PC, PE, PS, PI, PG) and, ultimately, destroy the structure, causing a decline in seed vigour during natural seed ageing.

Remodeling and protecting the membrane system to resist phosphorus deficiency in wild soybean (Glycine soja) seedling leaves

MAIN CONCLUSION

The poor-soil-tolerant wild soybean resist phosphorus deficiency by remodeling membrane lipids to reuse phosphorus. The plants synthesize phenolic acids and flavonoids to remove reactive oxygen species and protect membrane stability. Poor soil largely limits plant yields, and the development and utilization of high-quality wild plant resources is an effective approach to resolving this problem. Two ecotypes of wild soybean were used as experimental materials in this experiment. We integrated metabolomics and transcriptomics to determine whether wild soybean (Glycine soja) could resist phosphorus deficiency by remodeling and protecting its membrane system. Under phosphorus-deficient conditions, the plant height and aboveground fresh and dry weight of poor-soil-tolerant wild soybean seedlings were less inhibited than those in common wild soybean. In poor-soil-tolerant wild soybean seedling leaves, the glycerol-3-phosphate content decreased significantly, while caffeic acid, ferulic acid, shikimic acid, phenylalanine, tyrosine, and tryptophan increased significantly. β-Glucosidase and chalcone synthase genes and those that encode SQD2, a crucial enzyme in thiolipid biosynthesis, were specifically up-regulated, whereas the glucosyltransferase UGT74B1 gene was down-regulated. The poor-soil-tolerant wild soybean enhanced glycerolipid metabolism to decompose phospholipids and release phosphorus for reuse to improve resistance to phosphorus deficiency. The plants synthesized thiolipids to replace phospholipids and maintain membrane structure integrity and inhibited glucosinolate biosynthesis to promote phenylpropanoid biosynthesis, leading to the production of phenolic acids and flavonoids that removed reactive oxygen species and protected membrane system stability. The experiments evaluated and provided insight into the innovative utilization of wild soybean germplasm resources.

Commonly expressed key transcriptomic profiles of sepsis in the human circulation and brain via integrated analysis

BACKGROUND

Sepsis is the leading cause of death in intensive care units and is characterized by multiple organ failure, including dysfuction of the immune system and brain. This study aims to determine the differential effect of sepsis on specific circulating immune cell subsets compared with brain transcriptome and identify the genes co-expressed by them, so as to identify key genes and regulatory factors involved in the pathogenesis of sepsis induced brain injury and identify novel therapeutic targets.

METHODS

The GSE133822 and GSE135838 datasets were obtained from the Gene Expression Omnibus (GEO) database and utilized for bioinformatics analyses. Functional enrichment analysis was used to identify commonly expressed genes that were differentially expressed between sepsis patients and non-sepsis patients with critical illness; protein-protein interaction (PPI) networks were also generated. Then, key transcriptomic biomarkers were further validated in an external dataset from the GEO. We also investigated the expression of key mRNAs in peripheral blood mononuclear cells (PBMCs) from sepsis patients by quantitative PCR (qPCR) and an in-vitro model stimulated by lipopolysaccharide (LPS) was generated in brain cell lines.

RESULTS

The transcriptomic profiles of brain tissue were relatively similar as those of specific immune cells. In addition, our validation showed that these key genes were up regulated both in PBMCs in sepsis patients and LPS-treated brain cells.

CONCLUSION

Brain injury in sepsis was correlated with circulating immune responses, and the expression of DEFA3, MMP8, MMP9 and LCN2 might be potential diagnostic biomarkers as well as therapeutic target in septic brain dysfunction.

A Bioinformatic Framework for Dissecting the Dynamics of T Cells from Single-Cell Transcriptome

The quantitative tracking of the dynamics of T cells is challenging in human immunology. Although bulk sequencing of T cell receptor (TCR) α- and β-chains has been widely used for determining the clonality of T cells, such methods are limited in unveiling the phenotypic differences of T cells with the same clonotypes. Here, we describe a bioinformatics framework, STARTRAC, that integrates the single-cell transcriptome and TCR sequences as lineage-specific markers to quantitatively assess the dynamics of T cells, including their clonal expansion, tissue migration, and developmental transition properties.

Single-Cell Transcriptomic and Epigenetic Analyses of Mouse Mammary Development Starting with the Embryo

Cancers are caricatures of normal development. Yet, for most organs we are only beginning to learn about the molecular events underlying the embryonic antecedents of organogenesis and when differentiation into the cell types found in the adult actually begins. Here, we will focus on the powerful single-cell RNA sequencing and Assay for Transposase Accessible DNA by DNA sequencing (ATAC-seq) that we and others have been using to decipher the key regulators and signal transduction pathways involved in normal mammary development. We will first describe the techniques we use to identify, dissect, and isolate embryonic mammary rudiments and their constituent cells. We then describe the methods we have employed to perform single-cell RNA-seq and single-nucleus ATAC-seq using the small number of cells obtainable from mouse embryos. Finally, we will discuss the bioinformatic techniques we have used to interpret the vast amount of data obtained with these methods.

Geomorphometric environmental fragility of a watershed: a multicriteria spatial approach

Knowledge and understanding of the functioning of watersheds is essential for constructing future scenarios that aim to minimize instability. However, new approaches including variables, methods, and techniques into traditional methodologies contribute to environmental planning and management of such territorial units. This study aims to propose a model based on a multicriterion spatial approach for the analysis of the geomorphometric environmental fragility of watersheds. This study was conducted in the Murundú-Paiol watershed, located in the state of São Paulo, Brazil. Morphometric, geological, pedological, hypsometric, slope, land use, and land cover data were evaluated and integrated using geotechnologies for processing and analytical hierarchy process (AHP) considering a weighted linear combination for an integrated spatial analysis of the watershed. The study area shows a greater predisposition to fragility in areas of flat and smooth reliefs, especially around the main river, where there is a greater presence of anthropic areas. The methodology proposed here, which uses a multicriterion spatial approach and AHP, combined with technical and scientific data, allows replicating the model to another watersheds. Modeling was validated in a cooperative way using an in-field, traditional method. The watershed evaluated showed that 49.13% and 26.83% of lands have medium and low fragility, respectively, while about 17% of lands have a high fragility and their management should be a priority. Modeling correlates strongly and positively with fragility class detailing, and field areas corroborate the model proposed here. This evidenced a robust analysis of factors that affect the geomorphometric environmental fragility of watersheds. The method is efficient in contributing to environmental planning and management of this territorial unit.

Evaluation of coastal farming under salinization and optimized fertilization strategies in China

Nitrogen (N) application and salinity are key factors influencing crop yield and net economic benefit in coastal saline-alkali soils. Integrated analysis and optimization of the benefits of wheat-corn cropping under different nitrogen applications in saline soils could provide lay the scientific basis for sustainable development of agriculture in coastal farmlands. A total of 571 pair-reviewed literature data on two-factor cross-over trials, involving soil salinity and nitrogen application, were integratively analyzed. Based on multi-objective optimization of crop yield, agronomic and net economic benefits, and soil nitrate residue in coastal saline-alkali soils, area-specific nitrogen application strategies were developed. The results showed that increasing the N application rate under 1.8-2.9‰ salinity can increase crop yield and economic benefits. The net economic benefit of crops was negative under 3.5‰ salinity. Above that threshold of 3.5‰, it is not suitable for planting food crops. Consequently, it is necessary to strengthen the management of saline-alkali soils. While the application rate of 2.78 × 10⁸ kg N in winter wheat/summer corn cropping ensured environmental protection, farmers preferred 3.08 × 10⁸ kg of nitrogen dose. These were respectively 40.4% and 33.9% lower than the traditional dose and with relatively higher benefits too.

Integrated Safety and Efficacy Among Patients Receiving Benralizumab for Up to 5 Years

BACKGROUND

Benralizumab is an IL-5Rα-directed monoclonal antibody indicated for patients with severe, uncontrolled eosinophilic asthma.

OBJECTIVE

To evaluate the long-term safety and tolerability of benralizumab among adults treated for up to 5 years.

METHODS

This analysis included adults treated with placebo or subcutaneous benralizumab 30 mg every 4 or 8 weeks in the 48-week SIROCCO, 56-week CALIMA, and 28-week ZONDA pivotal trials, who were subsequently enrolled in the 56-week double-blind BORA extension and continued assigned regimens or initiated benralizumab (if previously on placebo) for 16 to 40 weeks, before entering the open-label MELTEMI extension. Safety was measured by adverse and serious adverse event rates. Exacerbations were evaluated in patients with blood eosinophils greater than or equal to 300 cells/μL receiving high-dose inhaled corticosteroids at baseline.

RESULTS

Overall, 446 received treatment and 384 (86.1%) completed the study; 157 (35.2%) received benralizumab for 4 or more years. Adverse and serious adverse event rates (28.5-32.4 and 6.3-8.4 per 100 patient-years, respectively) were low, stable over time, and did not increase with exposure; few (n = 8) discontinued because of adverse events. Serious infections and hypersensitivity event rates were consistent with those in previous studies. Among patients with blood eosinophils greater than or equal to 300 cells/μL-high-dosage inhaled corticosteroids receiving benralizumab every 8 weeks, at least 75% had zero exacerbations annually during the integrated analysis period.

CONCLUSIONS

In patients with severe, uncontrolled eosinophilic asthma, long-term benralizumab was safe and well tolerated for up to 5 years. There were no new safety signals, and exacerbations were eliminated in similar percentages of patients as in predecessor studies.

Integrated Bioinformatics Analysis to Identify Alternative Therapeutic Targets for Alzheimer's Disease: Insights from a Synaptic Machinery Perspective

Alzheimer's disease (AD), the most common type of dementia, is a serious neurodegenerative disease that has no cure yet, but whose symptoms can be alleviated with available medications. Therefore, early and accurate diagnosis of the disease and elucidation of the molecular mechanisms involved in the progression of pathogenesis are critically important. This study aimed to identify dysregulated miRNAs and their target mRNAs through the integrated analysis of miRNA and mRNA expression profiling in AD patients versus unaffected controls. Expression profiles in postmortem brain samples from AD patients and healthy individuals were extracted from the Gene Expression Omnibus database and were analyzed using bioinformatics approaches to identify gene ontologies, pathways, and networks. Finally, the module analysis of the PPI network and hub gene selection was carried out. A total of five differentially expressed miRNAs were extracted from the miRNA dataset, and 4312 differentially expressed mRNAs were obtained from the mRNA dataset. By comparing the DEGs and the putative targets of the altered miRNAs, 116 (3 upregulated and 113 downregulated) coordinated genes were determined. Also, six hub genes (SNAP25, GRIN2A, GRIN2B, DLG2, ATP2B2, and SCN2A) were identified by constructing a PPI network. The results of the present study provide insight into mechanisms such as synaptic machinery and neuronal communication underlying AD pathogenesis, specifically concerning miRNAs.

Comparative analysis of sRNAs, degradome and transcriptomics in sweet sorghum reveals the regulatory roles of miRNAs in Cd accumulation and tolerance

Key miRNAs including sbi-miR169p/q, sbi-miR171g/j, sbi-miR172a/c/d, sbi-miR172e, sbi-miR319a/b, sbi-miR396a/b, miR408, sbi-miR5384, sbi-miR5565e and nov_23 were identified to function in the regulation of Cd accumulation and tolerance. As an energy plant, sweet sorghum shows great potential in the phytoremediation of Cd-contaminated soils. However, few studies have focused on the regulatory roles of miRNAs and their targets under Cd stress. In this study, comparative analysis of sRNAs, degradome and transcriptomics was conducted in high-Cd accumulation (H18) and low-Cd accumulation (L69) genotypes of sweet sorghum. A total of 38 conserved and 23 novel miRNAs with differential expressions were identified under Cd stress or between H18 and L69, and 114 target genes of 41 miRNAs were validated. Furthermore, 25 miRNA-mRNA pairs exhibited negatively correlated expression profiles and sbi-miR172e together with its target might participate in the distinct Cd tolerance between H18 and L69 as well as sbi-miR172a/c/d. Additionally, two groups of them: miR169p/q-nov_23 and miR408 were focused through the co-expression analysis, which might be involved in Cd uptake and tolerance by regulating their targets associated with transmembrane transportation, cytoskeleton activity, cell wall construction and ROS (reactive oxygen species) homeostasis. Further experiments exhibited that cell wall components of H18 and L69 were different when exposed to cadmium, which might be regulated by miR169p/q, miR171g/j, miR319a/b, miR396a/b, miR5384 and miR5565e through their targets. Through this study, we aim to reveal the potential miRNAs involved in sweet sorghum in response to Cd stress and provide references for developing high-Cd accumulation or high Cd-resistant germplasm of sweet sorghum that can be used in phytoremediation.

Integrated analysis of microRNA and mRNA expression profiles in homozygous familial hypercholesterolemia patients and validation of atherosclerosis associated critical regulatory network

Homozygous familial hypercholesterolemia (HoFH) is a rare, life-threatening genetic disorder characterized by an extremely elevated serum level of low-density lipoprotein cholesterol (LDL-C) and accelerated premature atherosclerotic cardiovascular diseases (ASCVD). However, the detailed mechanism of how the pathogenic mutations of HoFH trigger the acceleration of ASCVD is not well understood. Therefore, we performed high-throughput RNA and small RNA sequencing on the peripheral blood RNA samples of six HoFH patients and three healthy controls. The gene and miRNA expression differences were analyzed, and seven miRNAs and six corresponding genes were screened out through regulatory network analysis. Validation through quantitative PCR of genes and miRNAs from 52 HoFH patients and 20 healthy controls revealed that the expression levels of hsa-miR-486-3p, hsa-miR-941, and BIRC5 were significantly upregulated in HoFH, while ID1, PLA2G4C, and CACNA2D2 were downregulated. Spearman correlation analysis found that the levels of ID1, hsa-miR-941, and hsa-miR-486-3p were significantly correlated with additional ASCVD risk factors in HoFH patients. This study represents the first integrated analysis of transcriptome and miRNA expression profiles in patients with HoFH, a rare disease, and as a result, six differentially expressed miRNAs/genes that may be related to atherosclerosis in HoFH are reported. The miRNA-mRNA regulatory network may be the critical regulation mechanism by which ASCVD is accelerated in HoFH.

Integrated Analysis of Two Probucol Trials for the Secondary Prevention of Atherosclerotic Cardiovascular Events: PROSPECTIVE and IMPACT

Aims: In this study, we integrated two randomized control trials, PROSPECTIVE and IMPACT, to address the effect of probucol on cerebrocardiovascular events and carotid intima-media thickness (IMT) in Japanese, Korean, and Chinese patients with coronary artery disease (CAD).

Methods: A total of 1,025 patients from the PROSPECTIVE and IMPACT studies were enrolled. The time to the first major adverse cerebrocardiovascular event, in addition to carotid IMT and lipid levels, was compared between the control and probucol groups.

Results: In the integrated analysis, the adjusted hazard ratio (HR) and 95% confidence interval (CI) were 0.67 and 0.44–1.03, respectively, indicating a tendency to show the effect of probucol on cerebrocardiovascular events in secondary prevention. We also found no significant differences between the control and probucol groups in the mean IMT of the carotid arteries and its changes. However, we found a significant decrease in cerebrocardiovascular events in patients with reduced levels of HDL cholesterol (HDL-C) (≥ 6.25 mg/dL) compared with those with levels ＜6.25 mg/dL (p=0.024), without any increase in adverse events such as severe ventricular arrhythmias.

Conclusion: We demonstrated a marginal effect of probucol on cerebrocardiovascular events in Asian patients with CAD, with reasonable safety profiles. A larger study may be needed to support the effect of probucol for cardiovascular prevention.

Integrated analysis of cell shape and movement in moving frame

The cell's movement and morphological change are two interrelated cellular processes. An integrated analysis is needed to explore the relationship between them. However, it has been challenging to investigate them as a whole. The cell's trajectory can be described by its speed, curvature, and torsion. On the other hand, the three-dimensional (3D) cell shape can be studied by using a shape descriptor such as spherical harmonic (SH) descriptor, which is an extension of a Fourier transform in 3D space. We propose a novel method using parallel-transport (PT) to integrate these shape-movement data by using moving frames as the 3D-shape coordinate system. This moving frame is purely determined by the velocity vector. On this moving frame, the movement change will influence the coordinate system for shape analysis. By analyzing the change of the SH coefficients over time in the moving frame, we can observe the relationship between shape and movement. We illustrate the application of our approach using simulated and real datasets in this paper.

Structure-preserving integrated analysis for risk stratification with application to cancer staging

To provide appropriate and practical level of health care, it is critical to group patients into relatively few strata that have distinct prognosis. Such grouping or stratification is typically based on well-established risk factors and clinical outcomes. A well-known example is the American Joint Committee on Cancer staging for cancer that uses tumor size, node involvement, and metastasis status. We consider a statistical method for such grouping based on individual patient data from multiple studies. The method encourages a common grouping structure as a basis for borrowing information, but acknowledges data heterogeneity including unbalanced data structures across multiple studies. We build on the "lasso-tree" method that is more versatile than the well-known classification and regression tree method in generating possible grouping patterns. In addition, the parametrization of the lasso-tree method makes it very natural to incorporate the underlying order information in the risk factors. In this article, we also strengthen the lasso-tree method by establishing its theoretical properties for which Lin and others (2013. Lasso tree for cancer staging with survival data. Biostatistics 14, 327-339) did not pursue. We evaluate our method in extensive simulation studies and an analysis of multiple breast cancer data sets.

Integrated microRNA and transcriptome profiling reveal key miRNA-mRNA interaction pairs associated with seed development in Tartary buckwheat (Fagopyrum tataricum)

BACKGROUND

Tartary buckwheat seed development is an extremely complex process involving many gene regulatory pathways. MicroRNAs (miRNAs) have been identified as the important negative regulators of gene expression and performed crucial regulatory roles in various plant biological processes. However, whether miRNAs participate in Tartary buckwheat seed development remains unexplored.

RESULTS

In this study, we first identified 26 miRNA biosynthesis genes in the Tartary buckwheat genome and described their phylogeny and expression profiling. Then we performed small RNA (sRNA) sequencing for Tartary buckwheat seeds at three developmental stages to identify the miRNAs associated with seed development. In total, 230 miRNAs, including 101 conserved and 129 novel miRNAs, were first identified in Tartary buckwheat, and 3268 target genes were successfully predicted. Among these miRNAs, 76 exhibited differential expression during seed development, and 1534 target genes which correspond to 74 differentially expressed miRNAs (DEMs) were identified. Based on integrated analysis of DEMs and their targets expression, 65 miRNA-mRNA interaction pairs (25 DEMs corresponding to 65 target genes) were identified that exhibited significantly opposite expression during Tartary buckwheat seed development, and 6 of the miRNA-mRNA pairs were further verified by quantitative real-time polymerase chain reaction (qRT-PCR) and ligase-mediated rapid amplification of 5' cDNA ends (5'-RLM-RACE). Functional annotation of the 65 target mRNAs showed that 56 miRNA-mRNA interaction pairs major involved in cell differentiation and proliferation, cell elongation, hormones response, organogenesis, embryo and endosperm development, seed size, mineral elements transport, and flavonoid biosynthesis, which indicated that they are the key miRNA-mRNA pairs for Tartary buckwheat seed development.

CONCLUSIONS

Our findings provided insights for the first time into miRNA-mediated regulatory pathways in Tartary buckwheat seed development and suggested that miRNAs play important role in Tartary buckwheat seed development. These findings will be help to study the roles and regulatory mechanism of miRNAs in Tartary buckwheat seed development.

Multiomics landscape of synovial fibroblasts in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease characterized by tumor-like hyperplasia and inflammation of the synovium, which causes synovial cell invasion into the bone and cartilage. In RA pathogenesis, various molecules in effector cells (i.e., immune cells and mesenchymal cells) are dysregulated by genetic and environmental factors. Synovial fibroblasts (SFs), the most abundant resident mesenchymal cells in the synovium, are the major local effectors of the destructive joint inflammation and exert their effects through the pathogenic production of molecules such as interleukin-6.

MAIN BODY

To date, more than 100 RA susceptibility loci have been identified in genome-wide association studies (GWASs), and finding novel therapeutic targets utilizing genome analysis is considered a promising approach because some candidate causal genes identified by GWASs have previously been established as therapeutic targets. For further exploration of RA-responsible cells and cell type-specific therapeutic targets, integrated analysis (or functional genome analysis) of the genome and intermediate traits (e.g., transcriptome and epigenome) is crucial.

CONCLUSION

This review builds on the existing knowledge regarding the epigenomic abnormalities in RASFs and discusses the recent advances in single-cell analysis, highlighting the prospects of SFs as targets for safer and more effective therapies against RA.

Integrated analysis of multiple microarray studies to identify novel gene signatures in preeclampsia

INTRODUCTION

Preeclampsia (PE) is one of the major causes of maternal and fetal morbidity and mortality in pregnancy worldwide. However, the intrinsic molecular mechanisms underlying the pathogenesis of PE have not yet been fully elucidated.

METHODS

Robust rank aggregation (RRA), weighted correlation network analysis (WGCNA) and protein-protein interaction (PPI) methods were used to identify robust differentially expressed genes (DEGs) and hub genes in preeclampsia and subgroups based on 10 Gene Expression Omnibus (GEO) datasets. Subsequently, enrichment analysis and correlation analysis were performed to explore the potential function of the robust DEGs and hub genes. The diagnostic role of hub genes was further investigated by GSE12767. The miRNA regulators and the effect of hypoxia on hub genes were explored by using GSE84260 and GSE65271, respectively.

RESULTS

Robust DEGs were identified in each subgroup including preeclampsia. Totally, 24 hub genes enriched in inflammatory response, renin-angiotensin system and JAK-STAT pathway, and 24 related miRNA regulators were identified.

DISCUSSION

Our integrated analysis identified novel gene signatures in preeclampsia and subgroups and will contribute to the understanding of comprehensive molecular changes in preeclampsia.

Optimal interruption time of dabigatran oral administration to ablation (O-A time) in patients with atrial fibrillation: Integrated analysis of 2 randomized controlled clinical trials

BACKGROUND

RE-CIRCUIT (NCT02348723) and ABRIDGE-J (UMIN000013129) are recently published randomized clinical trials showing that anticoagulation therapy with dabigatran during the periprocedural period of catheter ablation (CA) for atrial fibrillation (AF) was associated with fewer complications. However, the dabigatran administration protocols were different (uninterrupted in RE-CIRCUIT and minimally interrupted in ABRIDGE-J). The aim of this present study was to clarify the optimal interruption time of dabigatran Oral administration to Ablation (O-A time).

METHODS

We conducted an integrated analysis of the 2 prospective trials. The endpoint of the study was the incidence of major bleeding events during and up to 8 weeks after CA across participants with different O-A times.

RESULTS

The 535 patients in the dabigatran groups of the 2 trials were divided into 3 groups based on their O-A times (<8 h, n = 258; 8-24 h, n = 191; >24 h, n = 86). Major bleeding events occurred in 5 patients (1.9%) in the <8 h group, and 3 (3.5%) in the >24 h group; however, no major bleeding events occurred in the 8-24 h group (3 group-comparison, p = 0.026). No thromboembolic complication was observed in any of the 3 O-A time groups.

CONCLUSION

In patients undergoing CA for AF using dabigatran as a periprocedural anticoagulant, an O-A time of 8-24 h was associated with no bleeding complications. These data suggest that an O-A time of 8-24 h may be an appropriate option, especially in a low thromboembolic-risk patient.

Identification of pathogenic genes and transcription factors in respiratory syncytial virus

BACKGROUND

Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory infections in children, especially bronchiolitis. Our study aimed to identify the key genes and upstream transcription factors in RSV.

METHODS

To screen for RSV pathogenic genes, an integrated analysis was performed using the RSV microarray dataset in GEO. Functional annotation and potential pathways for differentially expressed genes (DEGs) were further explored by GO and KEGG enrichment analysis. We constructed the RSV-specific transcriptional regulatory network to identify key transcription factors for DEGs in RSV.

RESULTS

From three GEO datasets, we identified 1059 DEGs (493 up-regulated and 566 down-regulated genes, FDR < 0.05 and |Combined.ES| > 0.8) between RSV patients and normal controls. GO and KEGG analysis revealed that 'response to virus' (FDR = 7.13E-15), 'mitochondrion' (FDR = 1.39E-14) and 'Asthma' (FDR = 1.28E-06) were significantly enriched pathways for DEGs. The expression of IFI27, IFI44, IFITM3, FCER1A, and ISG15 were shown to be involved in the pathogenesis of RSV.

CONCLUSIONS

We concluded that IFI27, IFI44, IFITM3, FCER1A, and ISG15 may play a role in RSV. Our finding may contribute to the development of new potential biomarkers, reveal the underlying pathogenesis and also identify novel therapeutic targets for RSV.

Identification of Candidate Genes and Pathways in Nonsegmental Vitiligo Using Integrated Bioinformatics Methods

BACKGROUND

Nonsegmental vitiligo (NSV) is an acquired depigmentation disorder of unknown origin. Enormous interests focus on finding novel biomarkers and pathways responsible for NSV.

METHODS

The gene expression level was obtained by integrating microarray datasets (GSE65127 and GSE75819) from the Gene Expression Omnibus database using the sva R package. Differentially expressed genes (DEGs) between each group were identified by the limma R package. The interaction network was constructed using STRING, and significant modules coupled with hub genes were identified by cytoHubba and molecular complex detection. Pathway analyses were conducted using generally applicable gene set enrichment and further visualized in R environment.

RESULTS

A total of 102 DEGs between vitiligo lesional skin and healthy skin, 14 lesion-specific genes, and 29 predisposing genes were identified from the integrated dataset. Except for the anticipated decrease in melanogenesis, three major functional changes were identified, including oxidative phosphorylation, p53, and peroxisome proliferator-activated receptor (PPAR) signaling in lesional skin. PPARG, MUC1, S100A8, and S100A9 were identified as key hub genes involved in the pathogenesis of vitiligo. Besides, upregulation of the T cell receptor signaling pathway was considered to be associated with susceptibility of the skin in NSV patients.

CONCLUSION

Our study reveals several potential pathways and related genes involved in NSV using integrated bioinformatics methods. It might provide references for targeted strategies for NSV.

Integrated Bioinformatics Analysis for the Screening of Associated Pathways and Therapeutic Drugs in Coronavirus Disease 2019

Background

COVID-19 caused by a novel coronavirus, a severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has recently broken out worldwide. Up to now, the development of vaccine is still in the stage of clinical research, and there is no clinically approved specific antiviral drug for human coronavirus infection. The purpose of this study is to investigate the key molecules involved in response during SARS-CoV-2 infection and provide references for the treatment of SARS-CoV-2.

Methods

We conducted in-depth and comprehensive bioinformatics analysis of human proteins identified with SARS-CoV-2, including functional enrichment analysis, protein interaction network analysis, screening of hub genes, and evaluation of their potential as therapeutic targets. In addition, we used the gene-drug database to search for inhibitors of related biological targets.

Results

Several significant pathways, such as PKA, centrosome and transcriptional regulation, may greatly contribute to the development and progression of COVID-2019 disease. Taken together 15 drugs and 18 herb ingredients were screened as potential drugs for viral treatment. Specially, the trans-resveratrol can significantly reduce the expression of N protein of MERS-CoV and inhibit MERS-CoV. In addition, trans-resveratrol, Epigallocatechin-3-gallate (EGCG) and BX795 all show good anti multiple virus effects.

Conclusion

Some drugs selected through our methods have been proven to have antiviral effects in previous studies. We aim to use global bioinformatics analysis to provide insights to assist in the design of new drugs and provide new choices for clinical treatment.

How to construct and validate an Integrated Socio-Economic Vulnerability Index: Implementation at regional scale in urban areas prone to flash flooding

Flash flooding is the natural hazard provoking the largest number of casualties, so adequately characterizing vulnerability is key to improve flood risk analysis and management. Developing composite indices is the most widely used methodology in vulnerability analysis. However, very few studies have so far assessed vulnerability in urban areas prone to flash flooding and the resulting research presents two main drawbacks: i) a fragmented approach is often pursued, i.e. without jointly considering the vulnerability components (exposure, sensitivity and resilience) and the two most influential dimensions in urban environments (social and economic); and ii) vulnerability indices are not usually validated because an ancillary dataset is not generally available and flash flooding events do not happen simultaneously in all urban areas of a particular region. Considering the above gaps, this paper describes the construction of an Integrated Socio-Economic Vulnerability Index (ISEVI) at the regional scale, which considers all vulnerability components and social and economic dimensions. ISEVI was subsequently validated through an uncertainty and sensitivity analysis using the Monte Carlo method. Further, regional spatial patterns of vulnerability were identified implementing a Latent Class Cluster Analysis. Uncertainty analysis reveals the high stability of vulnerability categories of the ISEVI and sensitivity analysis shows that the type and the conservation state of buildings are the vulnerability factors that cause a greater variability in ISEVI scores. The method deployed here may allow specific strategies for vulnerability reduction to be developed based on disaggregating the validated ISEVI into dimensions and components and using the regional spatial patterns characterized.

A potential endogenous gibberellin-mediated signaling cascade regulated floral transition in Magnolia × soulangeana 'Changchun'

The floral transition is a critical developmental switch in plants, and has profound effects on the flower production and yield. Magnolia × soulangeana 'Changchun' is known as a woody ornamental plant, which can bloom in spring and summer, respectively. In this study, anatomical observation, physiological measurement, transcriptome, and small RNA sequencing were performed to investigate potential endogenous regulatory mechanisms underlying floral transition in 'Changchun'. Transition of the shoot apical meristem from vegetative to reproductive growth occurred between late April and early May. During this specific developmental process, a total of 161,645 unigenes were identified, of which 73,257 were significantly differentially expressed, while a number of these two categories of miRNAs were 299 and 148, respectively. Further analysis of differentially expressed genes (DEGs) revealed that gibberellin signaling could regulate floral transition in 'Changchun' in a DELLA-dependent manner. In addition, prediction and analysis of miRNA targeted genes suggested that another potential molecular regulatory module was mediated by the miR172 family and other several novel miRNAs (Ms-novel_miR139, Ms-novel_miR229, and Ms-novel_miR232), with the participation of up- or down-regulating genes, including MsSVP, MsAP2, MsTOE3, MsAP1, MsGATA6, MsE2FA, and MsMDS6. Through the integrated analysis of mRNA and miRNA, our research results will facilitate the understanding of the potential molecular mechanism underlying floral transition in 'Changchun', and also provide basic experimental data for the plant germplasm resources innovation in Magnolia.

Integrating multiple microarray dataset analysis and machine learning methods to reveal the key genes and regulatory mechanisms underlying human intervertebral disc degeneration

Intervertebral disc degeneration (IDD), a major cause of lower back pain, has multiple contributing factors including genetics, environment, age, and loading history. Bioinformatics analysis has been extensively used to identify diagnostic biomarkers and therapeutic targets for IDD diagnosis and treatment. However, multiple microarray dataset analysis and machine learning methods have not been integrated. In this study, we downloaded the mRNA, microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) expression profiles (GSE34095, GSE15227, GSE63492 GSE116726, GSE56081 and GSE67566) associated with IDD from the GEO database. Using differential expression analysis and recursive feature elimination, we extracted four optimal feature genes. We then used the support vector machine (SVM) to make a classification model with the four optimal feature genes. The ROC curve was used to evaluate the model's performance, and the expression profiles (GSE63492, GSE116726, GSE56081, and GSE67566) were used to construct a competitive endogenous RNA (ceRNA) regulatory network and explore the underlying mechanisms of the feature genes. We found that three miRNAs (hsa-miR-4728-5p, hsa-miR-5196-5p, and hsa-miR-185-5p) and three circRNAs (hsa_circRNA_100723, hsa_circRNA_104471, and hsa_circRNA_100750) were important regulators with more interactions than the other RNAs across the whole network. The expression level analysis of the three datasets revealed that BCAS4 and SCRG1 were key genes involved in IDD development. Ultimately, our study proposes a novel approach to determining reliable and effective targets in IDD diagnosis and treatment.

Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer

BACKGROUND

It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.

METHODS

We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.

RESULTS

A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.

CONCLUSION

Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

In-depth analysis of the Quercus suber metabolome under drought stress and recovery reveals potential key metabolic players

Cork oak (Quercus suber L.) is a species of ecological, social and economic importance in the Mediterranean region. Given its xerophytic adaptability, the study of cork oak's response to drought stress conditions may provide important data in the global scenario of climate change. The mechanisms behind cork oak's adaptation to drought conditions can inform the design and development of tools to better manage this species under the changing climate patterns. Metabolomics is one of the most promising omics layers to capture a snapshot of a particular physiological state and to identify putative biomarkers of stress tolerance. Drastic changes were observed in the leaf metabolome of Q. suber between the different experimental conditions, namely at the beginning of the drought stress treatment, after one month under drought and post rehydration. All experimental treatments were analyzed through sPLS to inspect for global changes and stress and rehydration responses were analyzed independently for specific alterations. This allowed a more in-depth study and a search for biomarkers specific to a given hydric treatment. The metabolome analyses showed changes in both primary and secondary metabolism, but highlighted the role of secondary metabolism. In addition, a compound-specific response was observed in stress and rehydration. Key compounds such as L-phenylalanine and epigallocatechin 3-gallate were identified in relation to early drought response, terpenoid leonuridine and the flavonoid glycoside (-)-epicatechin-3'-O-glucuronide in long-term drought response, and flavone isoscoparine was identified in relation to the recovery process. The results here obtained provide novel insights into the biology of cork oak, highlighting pathways and metabolites potentially involved in the response of this species during drought and recovery that may be essential for its adaptation to long periods of drought. It is expected that this knowledge can encourage further functional studies in order to validate potential biomarkers of drought and recovery that maybe used to support decision-making in cork oak breeding programs.

Integrated analysis of energy, indoor environment, and occupant satisfaction in green buildings using real-time monitoring data and on-site investigation

Recently, a growing literature pay attention to the green buildings, and most of them focuses on design, energy simulation, and post-occupancy evaluation but rarely involves the integration analysis of energy consumption, indoor environmental quality, and occupant satisfaction in the operational stage. In this paper, the authors propose a comprehensive quantitative study based on energy-environment-satisfaction (EES) and take a three-star green building in Shanghai as an example. Through the use of real-time monitoring data, the study analyses the distribution characteristics of the parameters of EES. Meanwhile, this study discusses the differences between operational energy consumption and design parameters and also quantifies the exponential relationship between per floor personnel density and building energy consumption. Moreover, combined with the user satisfaction survey, some improvements are suggested. Furthermore, the relationship between daily energy consumption and the environmental parameters of daily energy consumption, PM2.5, CO₂, temperature, relative humidity, and illumination is fitted, and the results indicate that there is a multivariate linear relationship with a correlation of 0.876. Through the sensitivity analysis, we found that the relative humidity affects 1.4 times as much as CO₂. Therefore, its control value is critical to reduce energy consumption in the operation of green buildings.

Integrative analysis of microRNA and mRNA expression profiles in MARC-145 cells infected with PRRSV

Porcine reproductive and respiratory syndrome virus (PRRSV) causes tremendous economic losses to the swine industry worldwide. miRNAs are crucial regulators of gene expression and a wide range of complex interactions of miRNAs-mRNAs is possible during virus infection. However, there is no comprehensive integrated study of miRNA and mRNA networks in MARC-145 cells after infection with PRRSV. We analyzed the differential expressions, co-relations, annotations, and putative functions of miRNA and mRNA networks in PRRSV-infected MARC-145 cells. Based on the filtering criterion, 22 differentially expressed miRNAs (DEmiRs) (15 up- and 7 downregulated) were filtered out. miRNA-mRNA interaction networks were constructed. For the 18 selected miRNAs, 390 potential target genes were predicted from the differentially expressed mRNAs (DEmRs). GO and KEGG pathway annotations predicted 34 KEGG pathways, 12 of which are known to be involved in virus infection. Real-time PCR validated the RNA-seq results. Our analysis showed that miR-27a-5p and miR-21-3p downregulate the expression of two of their potential target genes-SPARC, CLIC1, and cofilin-1, COX7A2, respectively. Further experiments proved that miR-21-3p and miR-27a-5p can promote PRRSV replication significantly. It is the first report that these two miRNAs participate in the interaction of host cells with PRRSV. Our results provide insights into the role of miRNAs in response to PRRSV infection, which will aid the research for developing novel therapies against PRRSV.

Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database

BACKGROUND

Ischemic cardiomyopathy (ICM) is one of the most usual causes of death worldwide. This study aimed to find the candidate gene for ICM.

METHODS

We studied differentially expressed genes (DEGs) in ICM compared to healthy control. According to these DEGs, we carried out the functional annotation, protein-protein interaction (PPI) network and transcriptional regulatory network constructions. The expression of selected candidate genes were confirmed using a published dataset and Quantitative real time polymerase chain reaction (qRT-PCR).

RESULTS

From three Gene Expression Omnibus (GEO) datasets, we acquired 1081 DEGs (578 up-regulated and 503 down-regulated genes) between ICM and healthy control. The functional annotation analysis revealed that cardiac muscle contraction, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy and dilated cardiomyopathy were significantly enriched pathways in ICM. SNRPB, BLM, RRS1, CDK2, BCL6, BCL2L1, FKBP5, IPO7, TUBB4B and ATP1A1 were considered the hub proteins. PALLD, THBS4, ATP1A1, NFASC, FKBP5, ECM2 and BCL2L1 were top six transcription factors (TFs) with the most downstream genes. The expression of 6 DEGs (MYH6, THBS4, BCL6, BLM, IPO7 and SERPINA3) were consistent with our integration analysis and GSE116250 validation results.

CONCLUSIONS

The candidate DEGs and TFs may be related to the ICM process. This study provided novel perspective for understanding mechanism and exploiting new therapeutic means for ICM.

Distribution of heavy metals in crop soils from an agricultural region of the Yucatan Peninsula and biochemical changes in earthworm Eisenia foetida exposed experimentally

Heavy metals (HM) are natural components of agricultural soils. However, excessive use of agrochemicals (fertilizers and pesticides) can increase the concentration of these elements, making them harmful to crops and soil biota. Therefore, this study aimed to evaluate the concentrations of 6 HM (Cr, Mn, Cu, Zn, Al, and Fe) in soils collected from a typical agricultural region of the Yucatan Peninsula, Mexico, and relate their effects on weight, biotransformation (EROD, GST), and oxidative stress (SOD, CAT, LPO, and MT) in the earthworm Eisenia foetida. The results showed different concentrations of HM accumulation in soils, in the following order, Fe (598.74 ± 223.81 μg g^-1), Al (145.30 ± 33.54 μg g^-1), Cr (88.38 ± 36.23 μg g^-1), Mn (69.53 ± 22.48 μg g^-1), Zn (54.10 ± 12.04 μg g^-1), and Cu (24.91 ± 12.40 μg g^-1), the soils with maize, soybean, and chihua squash crops being the ones with the highest distribution and availability of these elements. These concentrations of metals did not produce mortality. However, Cr, Fe, and Al induced a significant biomass loss of E. foetida. The integrated biomarker response version 2 revealed that soil with maize cultivation was affected the most, with the earthworms exposed to this soil showing greater variations in the dominant biological responses including EROD, TBARS, SOD, and MT (IBRv2 = 9.73). PCA analysis indicated a strong positive relationship between these oxidative stress biomarkers and Cu and Zn concentrations. These findings provide a reference guide that should be part of the monitoring and management programs for different agricultural types in the region under study.