Global Profiling Research Articles

Global zenith wet delay modeling with surface meteorological data and machine learning

The tropospheric delay is a major error source for space geodetic techniques, and the performance of its modeling is significantly limited due to the high spatiotemporal variability of the moisture in the lower atmosphere. In this study, global modeling of the tropospheric zenith wet delay (ZWD) was realized based on surface meteorological data obtained from radiosondes and Global Positioning System (GPS) radio occultation (RO) measurements through the random forest (RF) and backpropagation neural network (BPNN) regression analysis. The modeling performance was further validated based on two kinds of global atmospheric profiles for the year 2020. Our results show that the ZWD modeling accuracy gained by two machine learning regression approaches is significantly improved by taking into account surface meteorological parameters, especially the surface water vapor pressure when compared to the Global Pressure and Temperature 3 (GPT3) model. When surface meteorological data are available, the RF-B model yields ZWD estimations with an overall agreement of 3.1 cm in comparison with the sounding profiles and 2.4 cm in contrast to the GPS RO atmospheric profiles. The RF-B is superior to other models based on surface meteorological parameters for ZWD calculation, e.g., the accuracy improves by 21.8–23.8% against the approach by Saastamoinen and 7–12.2% against the formula by Askne and Nordius.

Gated Spatial–Temporal Merged Transformer Inspired by Multimask and Dual Branch for Traffic Forecasting

As an essential part of intelligent transportation system (ITS), traffic forecasting has provided crucial role for traffic management and risk assessment. However, complex spatial–temporal dependencies, heterogeneity, dynamicity, and periodicity of traffic data influence the traffic forecasting performance. Consequently, we propose a novel effective gated spatial–temporal merged transformer (GSTMT) inspired by multimask and dual branch for accurate traffic forecasting in this paper. Specifically, we first conduct a concatenation of gated spatial static mask transformer (GSSMT) and gated spatial dynamic mask transformer (GSDMT) with residual network. The GSSMT and GSDMT evolve from the traditional transformer by making preferable modifications that include gated linear unit (GLU), multimask mechanism including static mask matrix (SMM) and dynamic mask matrix (DMM), and spatial attention (SA). Among them, GLU is to promote the performance of capturing spatial dependency, dynamicity, and heterogeneity due to advanced performance for controlling information flow through layers. Additionally, by developing multimask mechanism including two novel SMM and DMM, the proposed GSTMT can precisely model the static and dynamic spatial structure for effectively highlighting static dependency and dynamicity. And SA is injected for enhancing the ability of capturing spatial dependency of GSSMT and GSDMT. Secondly, we develop a dual‐branch gated temporal transformer (DBGTT) for capturing temporal dependency, heterogeneity, dynamicity, and periodicity via incorporating the GLU and mixed time series decomposition (MTD) into traditional transformer. Similarly, we also introduce the GLU for empowering DBGTT with capability of capturing temporal dependency, dynamicity, and heterogeneity. In addition, MTD, which brings dual‐branch mechanism, can enhance the DBGTT for capturing more detailed temporal information via exploiting global and periodic profile of traffic data. At last, some experiments, which are performed on several real‐world traffic datasets, demonstrate the better results over classic traffic forecasting methods.

5-Fluorouracil dose escalation generated desensitized colorectal cancer cells with reduced expression of protein methyltransferases and no epithelial-to-mesenchymal transition potential.

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers. In many cases, the poor prognosis of advanced CRC is associated with resistance to treatment with chemotherapeutic drugs such as 5-Fluorouracil (5-FU). The epithelial-to-mesenchymal transition (EMT) and dysregulation in protein methylation are two mechanisms associated with chemoresistance in many cancers. This study looked into the effect of 5-FU dose escalation on EMT and protein methylation in CRC. HCT-116, Caco-2, and DLD-1 CRC cell lines were exposed to dose escalation treatment of 5-FU. The motility and invasive potentials of the cells before and after treatment with 5-FU were investigated through wound healing and invasion assays. This was followed by a Western blot which analyzed the protein expressions of the epithelial marker E-cadherin, mesenchymal marker vimentin, and the EMT transcription factor (EMT-TF), the snail family transcriptional repressor 1 (Snail) in the parental and desensitized cells. Western blotting was also conducted to study the protein expressions of the protein methyltransferases (PMTs), Euchromatic histone lysine methyltransferase 2 (EHMT2/G9A), protein arginine methyltransferase (PRMT5), and SET domain containing 7/9 (SETD7/9) along with the global lysine and arginine methylation profiles. The dose escalation method generated 5-FU desensitized CRC cells with distinct morphological features and increased tolerance to high doses of 5-FU. The 5-FU desensitized cells experienced a decrease in migration and invasion when compared to the parental cells. This was reflected in the observed reduction in E-cadherin, vimentin, and Snail in the desensitized cell lines. Additionally, the protein expressions of EHMT2/G9A, PRMT5, and SETD7/9 also decreased in the desensitized cells and global protein lysine and arginine methylation became dysregulated with 5-FU treatment. This study showed that continuous, dose-escalation treatment of 5-FU in CRC cells generated 5-FU desensitized cancer cells that seemed to be less aggressive than parental cells.

Generation of single-cysteine E. coli ProQ variants to study RNA-protein interaction mechanisms.

ProQ is a FinO-domain protein found in E. coli and other proteobacteria that has a global RNA-binding profile. In order to probe the detailed mechanism of RNA interactions, we have developed a collection of 13 E. coli ProQ variants that possess single-cysteine residues at varied positions on the surface of the N-terminal FinO domain and retain the ability to bind well to RNA. This set of variant ProQ proteins will support future biochemical and biophysical studies to map the orientation of bound RNAs to different sites around the ProQ protein, shedding light on the mechanism of ProQ-RNA interactions.

Proteomic and phosphoproteomic profiling of urinary small extracellular vesicles in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer and a major cause of cancer-related mortality worldwide. Small extracellular vesicles (sEVs) are heterogeneous populations of membrane-structured vesicles that can be found in many biological fluids and are currently considered as a potential source of disease-associated biomarkers for diagnosis. The purpose of this study was to define the proteomic and phosphoproteomic landscape of urinary sEVs in patients with HCC. Mass spectrometry-based methods were used to detect the global proteome and phosphoproteome profiles of sEVs isolated by differential ultracentrifugation. Label-free quantitation analysis showed that 348 differentially expressed proteins (DEPs) and 548 differentially expressed phosphoproteins (DEPPs) were identified in the HCC group. Among them, multiple phosphoproteins related to HCC, including HSP90AA1, IQGAP1, MTOR, and PRKCA, were shown to be upregulated in the HCC group. Pathway enrichment analysis indicated that the upregulated DEPPs participate in the regulation of autophagy, proteoglycans in cancer, and the MAPK/mTOR/Rap1 signaling pathway. Furthermore, kinase-substrate enrichment analysis revealed activation of MTOR, AKT1, MAP2Ks, and MAPKs family kinases in HCC-derived sEVs, indicating that dysregulation of the MAPK and mTOR signaling pathways may be the primary sEV-mediated molecular mechanisms involved in the development and progression of HCC. This study demonstrated that urinary sEVs are enriched in proteomic and phosphoproteomic signatures that could be further explored for their potential use in early HCC diagnostic and therapeutic applications.

Aerosol optical depth disaggregation: toward global aerosol vertical profiles

Abstract Aerosol-cloud interactions constitute the largest source of uncertainty in assessments of anthropogenic climate change. This uncertainty arises in part from the difficulty in measuring the vertical distributions of aerosols, and only sporadic vertically resolved observations are available. We often have to settle for less informative vertically aggregated proxies such as aerosol optical depth (AOD). In this work, we develop a framework for the vertical disaggregation of AOD into extinction profiles, that is, the measure of light extinction throughout an atmospheric column, using readily available vertically resolved meteorological predictors such as temperature, pressure, or relative humidity. Using Bayesian nonparametric modeling, we devise a simple Gaussian process prior over aerosol vertical profiles and update it with AOD observations to infer a distribution over vertical extinction profiles. To validate our approach, we use ECHAM-HAM aerosol-climate model data which offers self-consistent simulations of meteorological covariates, AOD, and extinction profiles. Our results show that, while very simple, our model is able to reconstruct realistic extinction profiles with well-calibrated uncertainty, outperforming by an order of magnitude the idealized baseline which is typically used in satellite AOD retrieval algorithms. In particular, the model demonstrates a faithful reconstruction of extinction patterns arising from aerosol water uptake in the boundary layer. Observations however suggest that other extinction patterns, due to aerosol mass concentration, particle size, and radiative properties, might be more challenging to capture and require additional vertically resolved predictors.

FedCluster: a global user profile generation method based on vertical federated clustering

FedCluster: a global user profile generation method based on vertical federated clustering

Phytochemical and medicinal profiling of Russula vinosa Lindbl (RVL) using multiomics techniques

Russula vinosa Lindbl (RVL) is a multifunctional edible fungus that has recently gained widespread attention due to its numerous nutritious, delicious, and medicinal properties. However, little attention has been directed toward analyzing comprehensive phytochemical profiling and bioactivity in RVL. This study aimed to evaluate the phytochemical and medicinal profiling of RVL systematically. Herein, we characterized global RVL phytochemical profiling using the LC/GC-MS-based multiomics strategy through initial methodological optimization. A total of 633 metabolites were identified using untargeted multiomics, with fatty acids, amino acids, polyphenols, terpenoids, organic acids, sugars, and phospholipids as the primary metabolites. Polyphenols served as the main active components by quantitative analysis and antioxidant evaluation, impling that they may be related to antitumor effects. Moreover, based on phytochemical profiling, the potential gene targets and mechanisms of anticancer properties of RVL were explored through network pharmacology. The significance of this study lies in expanding our understanding of the phytochemical and bioactive components of RVL and providing references for its further utilization and exploitation. Therefore, RVL could be an excellent raw material for the food, nutraceutical, and pharmaceutical industries due to its richness in nutrients and bioactive ingredients.

Multi-omic analysis of longitudinal acute myeloid leukemia patient samples reveals potential prognostic markers linked to disease progression.

Relapse remains a determinant of treatment failure and contributes significantly to mortality in acute myeloid leukemia (AML) patients. Despite efforts to understand AML progression and relapse mechanisms, findings on acquired gene mutations in relapse vary, suggesting inherent genetic heterogeneity and emphasizing the role of epigenetic modifications. We conducted a multi-omic analysis using Omni-C, ATAC-seq, and RNA-seq on longitudinal samples from two adult AML patients at diagnosis and relapse. Herein, we characterized genetic and epigenetic changes in AML progression to elucidate the underlying mechanisms of relapse. Differential interaction analysis showed significant 3D chromatin landscape reorganization between relapse and diagnosis samples. Comparing global open chromatin profiles revealed that relapse samples had significantly fewer accessible chromatin regions than diagnosis samples. In addition, we discovered that relapse-related upregulation was achieved either by forming new active enhancer contacts or by losing interactions with poised enhancers/potential silencers. Altogether, our study highlights the impact of genetic and epigenetic changes on AML progression, underlining the importance of multi-omic approaches in understanding disease relapse mechanisms and guiding potential therapeutic interventions.

Differential DNA methylation and metabolite profiling of Atlantic killifish (Fundulus heteroclitus) from the New Bedford Harbor Superfund site

Atlantic killifish (Fundulus heteroclitus) is a valuable model in evolutionary toxicology to study how the interactions between genetic and environmental factors serve the adaptive ability of organisms to resist chemical pollution. Killifish populations inhabiting environmental toxicant-contaminated New Bedford Harbor (NBH) show phenotypes tolerant to polychlorinated biphenyls (PCBs) and differences at the transcriptional and genomic levels. However, limited research has explored epigenetic alterations and metabolic effects in NBH killifish. To identify the involvement of epigenetic and metabolic regulation in the adaptive response of killifish, we investigated tissue- and sex-specific differences in global DNA methylation and metabolomic profiles of NBH killifish populations, compared to sensitive populations from a non-polluted site, Scorton Creek (SC). The results revealed that liver-specific global DNA hypomethylation and differential metabolites were evident in fish from NBH compared with those from SC. The sex-specific differences were not greater than the tissue-specific differences. We demonstrated liver-specific enriched metabolic pathways (e.g., amino acid metabolic pathways converged into the urea cycle and glutathione metabolism), suggesting possible crosstalk between differential metabolites and DNA hypomethylation in the livers of NBH killifish. Additional investigation of methylated gene regions is necessary to understand the functional role of DNA hypomethylation in the regulation of enzyme-encoding genes associated with metabolic processes and physiological changes in NBH populations.

Microbiome-gut-brain axis contributes to patients and Bama miniature pigs with acute large ischemic stroke.

Acute large hemispheric infarction (ALHI) is an overwhelming emergency with a great challenge of gastrointestinal dysfunction clinically. Here, we initially proposed delayed bowel movements as the clinical phenotype of strike to gut-brain axis (GBA) in ALHI patients by epidemiological analysis of 499 acute ischemic stroke (AIS) patients. 1H NMR-based metabolomics revealed that AIS markedly altered plasma global metabolic profiling of patients compared with healthy controls. Risk factors of strike on GBA were the National Institutes of Health Stroke Scale (NIHSS) score ≥ 5 and stroke onset time ≤ 24 h. As a result, first defecating time after admission to the hospital ≥2 days could be considered as a potential risk factor for strike on GBA. Subsequently, the ALHI Bama miniature (BM) pig model with acute symptomatic seizure was successfully established by ligation of the left ascending pharyngeal artery combined with local air injection. Clinical phenotypes of brain necrosis such as hemiplegia were examined with brain diffusion-weighted imaging (DWI) and pathological diagnosis. In addition to global brain injury and inflammation, we also found that ALHI induced marked alterations of intestinal barrier integrity, the gut microbial community, and microbiota-derived metabolites including serotonin and neurotransmitters in both plasma and multiple brain tissues of BM pigs. These findings revealed that microbiota-gut-brain axis highly contributed to the occurrence and development of ALHI.

Shared and Distinct Renal Transcriptome Signatures in 3 Standard Mouse Models of Chronic Kidney Disease

Introduction: Several mouse models with diverse disease etiologies are used in preclinical research for chronic kidney disease (CKD). Here, we performed a head-to-head comparison of renal transcriptome signatures in standard mouse models of CKD to assess shared and distinct molecular changes in three mouse models commonly employed in preclinical CKD research and drug discovery. Methods: All experiments were conducted on male C57BL/6J mice. Mice underwent sham, unilateral ureter obstruction (UUO), or unilateral ischemic-reperfusion injury (uIRI) surgery and were terminated two- and 6-weeks post-surgery, respectively. The adenine-supplemented diet-induced (ADI) model of CKD was established by feeding with adenine diet for 6 weeks and compared to control diet feeding. For all models, endpoints included plasma biochemistry, kidney histology, and RNA sequencing. Results: All models displayed increased macrophage infiltration (F4/80 IHC) and fibrosis (collagen 1a1 IHC). Compared to corresponding controls, all models were characterized by an extensive number of renal differentially expressed genes (≥11,000), with a notable overlap in transcriptomic signatures across models. Gene expression markers of fibrosis, inflammation, and kidney injury supported histological findings. Interestingly, model-specific transcriptome signatures included several genes representing current drug targets for CKD, emphasizing advantages and limitations of the three CKD models in preclinical target and drug discovery. Conclusion: The UUO, uIRI, and ADI mouse models of CKD have significant commonalities in their renal global transcriptome profile. Model-specific renal transcriptional signatures should be considered when selecting the specific model in preclinical target and drug discovery.

STEP: profiling cellular-specific targets and pathways of bioactive small molecules in tissues via integrating single-cell transcriptomics and chemoproteomics.

Identifying the cellular targets of bioactive small molecules within tissues has been a major concern in drug discovery and chemical biology research. Compared to cell line models, tissues consist of multiple cell types and complicated microenvironments. Therefore, elucidating the distribution and heterogeneity of targets across various cells in tissues would enhance the mechanistic understanding of drug or toxin action in real-life scenarios. Here, we present a novel multi-omics integration pipeline called Single-cell TargEt Profiling (STEP) that enables the global profiling of protein targets in mammalian tissues with single-cell resolution. This pipeline integrates single-cell transcriptome datasets with tissue-level protein target profiling using chemoproteomics. Taking well-established classic drugs such as aspirin, aristolochic acid, and cisplatin as examples, we confirmed the specificity and precision of cellular drug-target profiles and their associated molecular pathways in tissues using the STEP analysis. Our findings provide more informative insights into the action modes of bioactive molecules compared to in vitro models. Collectively, STEP represents a novel strategy for profiling cellular-specific targets and functional processes with unprecedented resolution.

Computational Multi-Models Enabled Design of Safe & Sustainable Multi-Component High-Entropy Coatings

The project M2DESCO is directed at addressing new challenges for developing next-generation high-entropy-alloy-based multi-component green (free of toxic substances) and sustainable (rare earth free & minimum critical metal elements) coatings with predictable functionalities, performance and life - aiming at increasing wear resistance by 100%, corrosion/oxidation resistance by 50~60 %, and effectively reducing the criticality of coating materials by at least 70%. To achieve these goals, the project is to integrate artificial intelligence/machine learning AI/ML underpinned, highly effective and highly efficient Computational Modelling that is guided by a novel Safe and Sustainability by Design Framework and facilitated by high-throughput characterisations and evaluations, to speed up the material-design to coating-product development process (reducing the development cycle-time by 400~500%). At the same time, M2DESCO is to enable optimal alloy/material design and coating process optimisation for high efficiency and high quality, so to reduce the overall product manufacturing cost (due to use of the new tooling developed) by 20%. The advancement of M2DESCO will contribute significantly to combating the loss in EU region caused by corrosion and wear, to the enhancement of the global profile and leadership of the EU material modelling/research community, to strengthening of the innovation capability of the EU coating industry/business.

Looking for a Third Way. Tsai Ing-wen and the Taiwanese Nation-Building

Tsai Ing-wen, the president of the Republic of China (Taiwan) in 2016–2024, is one of Asia’s most extraordinary female political leaders. A self-made woman who managed to enter politics independently – she was not born into a political family as is usually the case in East Asia, Southeast Asia, and South Asia – and who succeeded in her presidency. Tsai has enhanced the global profile of her country and impressed the world by combating the COVID-19 pandemic in a model way. She has also skillfully handled delicate cross-strait relations despite Beijing’s growing assertiveness. Tsai and her presidency are important for several reasons; the one highlighted here is her role in enhancing and trying to modify Taiwanese nation-building. During her presidency, Tsai Ing-wen advocated a “Third Way,” officially called “21st Century Taiwan’s Overall Cultural Construction”, based on accepting both the Taiwaneseness and the heritage of the Republic of China and merging both of these features. In other words, it emphasizes Taiwaneseness while not rejecting Chineseness. This is an interesting and bold attempt to forge a compromised identity, but one with an uncertain future due to domestic and international variables.

Genome-wide kinetic profiling of pre-mRNA 3' end cleavage.

Cleavage and polyadenylation is necessary for the formation of mature mRNA molecules. The rate at which this process occurs can determine the temporal availability of mRNA for subsequent function throughout the cell and is likely tightly regulated. Despite advances in high-throughput approaches for global kinetic profiling of RNA maturation, genome-wide 3' end cleavage rates have never been measured. Here, we describe a novel approach to estimate the rates of cleavage, using metabolic labeling of nascent RNA, high-throughput sequencing, and mathematical modeling. Using in silico simulations of nascent RNA-seq data, we show that our approach can accurately and precisely estimate cleavage half-lives for both constitutive and alternative sites. We find that 3' end cleavage is fast on average, with half-lives under a minute, but highly variable across individual sites. Rapid cleavage is promoted by the presence of canonical sequence elements and an increased density of polyadenylation signals near a cleavage site. Finally, we find that cleavage rates are associated with the localization of RNA polymerase II at the end of a gene, and faster cleavage leads to quicker degradation of downstream readthrough RNA. Our findings shed light on the features important for efficient 3' end cleavage and the regulation of transcription termination.

Ethnic Differences in Thrombotic Profiles of Acute Coronary Syndrome Patients and Relationship to Cardiovascular Outcomes: A Comparison of East Asian and White subjects.

East Asians (EAs), compared to white Caucasians (W), have a lower risk of ischemic heart disease and a higher risk of bleeding with antithrombotic medications. The underlying mechanisms are incompletely understood. We sought to compare thrombotic profiles of EA and W patients with myocardial infarction (MI) and relate these to cardiovascular outcomes. In a prospective study in the United Kingdom and Korea, blood samples from patients (n = 515) with ST- or non-ST-elevation MI (STEMI and NSTEMI) were assessed using the Global Thrombosis Test, measuring thrombotic occlusion (OT) and endogenous fibrinolysis (lysis time [LT]). Patients were followed for 1 year for major adverse cardiovascular events (MACE) and bleeding. EA patients showed reduced OT (longer OT) compared to W (646 seconds [470-818] vs. 436 seconds [320-580], p < 0.001), with similar LT. In STEMI, OT (588 seconds [440-759] vs. 361 seconds [274-462], p < 0.001) and LT (1,854 seconds [1,389-2,729] vs. 1,338 seconds [1,104-1,788], p < 0.001) were longer in EA than W. In NSTEMI, OT was longer (OT: 734 seconds [541-866] vs. 580 seconds [474-712], p < 0.001) and LT shorter (1519 seconds [1,058-2,508] vs. 1,898 seconds [1,614-2,806], p = 0.004) in EA than W patients. MACE was more frequent in W than EA (6.3 vs. 1.9%, p = 0.014) and bleeding infrequent. While OT was unrelated, LT was a strong independent predictor of MACE event after adjustment for risk factors (hazard ratio: 3.70, 95% confidence interval: 1.43-9.57, p = 0.007), predominantly in W patients, and more so in STEMI than NSTEMI patients. EA patients exhibit different global thrombotic profiles to W, associated with a lower rate of cardiovascular events.

Hippocampal metabolic profile during epileptogenesis in the pilocarpine model of epilepsy.

Temporal lobe epilepsy (TLE) is a common form of refractory epilepsy in adulthood. The metabolic profile of epileptogenesis is still poorly investigated. Elucidation of such a metabolic profile using animal models of epilepsy could help identify new metabolites and pathways involved in the mechanisms of epileptogenesis process. In this study, we evaluated the metabolic profile during the epileptogenesis periods. Using a pilocarpine model of epilepsy, we analyzed the global metabolic profile of hippocampal extracts by untargeted metabolomics based on ultra-performance liquid chromatography-high-resolution mass spectrometry, at three time points (3h, 1 week, and 2weeks) after status epilepticus (SE) induction. We demonstrated that epileptogenesis periods presented different hippocampal metabolic profiles, including alterations of metabolic pathways of amino acids and lipid metabolism. Six putative metabolites (tryptophan, N-acetylornithine, N-acetyl-L-aspartate, glutamine, adenosine, and cholesterol) showed significant different levels during epileptogenesis compared to their respective controls. These putative metabolites could be associated with the imbalance of neurotransmitters, mitochondrial dysfunction, and cell loss observed during both epileptogenesis and epilepsy. With these findings, we provided an overview of hippocampal metabolic profiles during different stages of epileptogenesis that could help investigate pathways and respective metabolites as predictive tools in epilepsy.

Long noncoding RNA lncPostn links TGF-β and p53 signaling pathways to transcriptional regulation of cardiac fibrosis.

Cardiac fibroblasts are essential for the homeostasis of the extracellular matrix, whose remodeling in many cardiovascular diseases leads to fibrosis. Long noncoding RNAs (lncRNAs) are associated with cardiac pathologies, but their functions in cardiac fibroblasts and contributions to cardiac fibrosis remain unclear. Here, we aimed to identify fibroblast-enriched lncRNAs essential in myocardial infarction (MI)-induced fibrosis and explore the molecular mechanisms responsible for their functions. Global lncRNA profiling was performed in post-MI mouse heart ventricles and transforming growth factor-β (TGF-β)-treated primary cardiac fibroblasts and confirmed in published data sets. We identified the cardiac fibroblast-enriched lncPostn, whose expression is stimulated in cardiac fibrosis induced by MI and the extracellular growth factor TGF-β. The promoter of lncPostn contains a functional TGF-β response element, and lncPostn knockdown suppresses TGF-β-stimulated cardiac fibroblast activation and improves cardiac functions post-MI. LncPostn stabilizes and recruits EP300 to the profibrotic periostin's promoter, representing a major mechanism for its transcriptional activation. Moreover, both MI and TGF-β enhance lncPostn expression while suppressing the cellular growth gatekeeper p53. TGF-β and p53 knockdown-induced profibrotic gene expression and fibrosis occur mainly through lncPostn and show additive effects. Finally, levels of serum lncPostn are significantly increased in patients' postacute MI and show a strong correlation with fibrosis markers, revealing a potential biomarker of cardiac fibrosis. Our findings identify the fibroblast-enriched lncPostn as a potent profibrotic factor, providing a transcriptional link between TGF-β and p53 signaling pathways to regulate fibrosis in cardiac fibroblasts.NEW & NOTEWORTHY Cardiac fibroblasts are essential for the homeostasis of the extracellular matrix, whose remodeling in many cardiovascular diseases leads to fibrosis. Long noncoding RNAs are functional and contribute to the biological processes of cardiovascular development and disorders. Our findings identify the fibroblast-enriched lncPostn as a potent profibrotic factor and demonstrate that serum lncPostn level may serve as a potential biomarker of human cardiac fibrosis postacute myocardial infarction.

Global deletome profile of Saccharomyces cerevisiae exposed to lithium.

The increasing use of lithium (Li) in new technologies raises the question of its impact on living microorganisms. In the present study, we aimed to identify putative Li targets and resistance mechanisms in the yeast model Saccharomyces cerevisiae using a deletomic approach based on the screening of a collection of 4733 knockout mutants under Li exposure. This screening highlighted 60 mutants resistant to Li and 124 mutants sensitive to Li. Through functional enrichment analyses, transport systems were identified as playing a central role in cell resistance to toxic concentrations of Li. In contrast, the AKT/protein kinase B family, signal transduction or cell communication were identified as potential toxic targets of Li. The majority of the mutants with a Li-sensitive phenotype were also sensitive to other alkali and alkaline earth metals, whereas the Li-resistance phenotype was mostly resistant to Na but poorly resistant to other metals. A comparison with the results of deletomics studies carried out in the presence of other metals highlighted Li-specific phenotypes. Three genes (NAM7, NMD2, UPF3) of the nonsense-mediated decay pathway were specifically involved in resistance to Li. In contrast, mutants with the NCA2, SPT20, GCN5, YOR376W, YPK3, and DCW1 genes deleted were specifically resistant to Li. These genes encode various functions from putative mannosidase to constitution of the Spt-Ada-Gcn5 acetyltransferase complex. This work provides a better understanding of potential specific resistance mechanisms and cellular targets of Li in yeast.