CT-based radiomics models predict spontaneous intracerebral hemorrhage expansion and are comparable with CT angiography spot sign.

Background and purpose: This study aimed to investigate the efficacy of radiomics, based on non-contrast computed tomography (NCCT) and computed tomography angiography (CTA) images, in predicting early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (SICH). Additionally, the predictive performance of these models was compared with that of the established CTA spot sign. Materials and methods: A retrospective analysis was conducted using CT images from 182 patients with SICH. Data from the patients were divided into a training set (145 cases) and a testing set (37 cases) using random stratified sampling. Two radiomics models were constructed by combining quantitative features extracted from NCCT images (the NCCT model) and CTA images (the CTA model) using a logistic regression (LR) classifier. Additionally, a univariate LR model based on the CTA spot sign (the spot sign model) was established. The predictive performance of the two radiomics models and the spot sign model was compared according to the area under the receiver operating characteristic (ROC) curve (AUC). Results: For the training set, the AUCs of the NCCT, CTA, and spot sign models were 0.938, 0.904, and 0.726, respectively. Both the NCCT and CTA models demonstrated superior predictive performance compared to the spot sign model (all P < 0.001), with the performance of the two radiomics models being comparable (P = 0.068). For the testing set, the AUCs of the NCCT, CTA, and spot sign models were 0.925, 0.873, and 0.720, respectively, with only the NCCT model exhibiting significantly greater predictive value than the spot sign model (P = 0.041). Conclusion: Radiomics models based on NCCT and CTA images effectively predicted HE in patients with SICH. The predictive performances of the NCCT and CTA models were similar, with the NCCT model outperforming the spot sign model. These findings suggest that this approach has the potential to reduce the need for CTA examinations, thereby reducing radiation exposure and the use of contrast agents in future practice for the purpose of predicting hematoma expansion.

Plasma proteome profiling reveals the therapeutic effects of the PPAR pan-agonist chiglitazar on insulin sensitivity, lipid metabolism, and inflammation in type 2 diabetes.

Chiglitazar is a novel peroxisome proliferator-activated receptor (PPAR) pan-agonist, which passed phase III clinical trials and was newly approved in China for use as an adjunct to diet and exercise in glycemic control in adult patients with Type 2 Diabetes (T2D). To explore the circulating protein signatures associated with the administration of chiglitazar in T2D patients, we conducted a comparative longitudinal study using plasma proteome profiling. Of the 157 T2D patients included in the study, we administered chiglitazar to a specific group, while the controls were given either placebo or sitagliptin. The plasma proteomes were profiled at baseline and 12 and 24 weeks post-treatment using data-independent acquisition mass spectrometry (DIA-MS). Our study indicated that 13 proteins were associated with chiglitazar treatment in T2D patients, including 10 up-regulated proteins (SHBG, TF, APOA2, APOD, GSN, MBL2, CFD, PGLYRP2, A2M, and APOA1) and 3 down-regulated proteins (PRG4, FETUB, and C2) after treatment, which were implicated in the regulation of insulin sensitivity, lipid metabolism, and inflammation response. Our study provides insight into the response of chiglitazar treatment from a proteome perspective and demonstrates the multi-faceted effects of chiglitazar in T2D patients, which will help the clinical application of chiglitazar and further study of its action mechanism.

Repeat-Enhancing Featured Ion-Guided Stoichiometry for Identification and Quantification of Direct Infusion Proteome.

The direct infusion-shotgun proteome analysis (DI-SPA) alongside data-independent acquisition mass spectrometry achieved fast proteome identification and quantification without chromatographic separation. However, robust peptide identification and quantification (label and label-free) for the DI-SPA data is still insufficient. We find that in the absence of chromatography, the identification of DI-SPA can be boosted by extending acquisition cycles repeatedly and maximizing the utilization of the featured repetition characteristics, combined with the machine learning-based automatic peptide scoring strategy. Here, we present the repeat-enhancing featured ion-guided stoichiometry (RE-FIGS), a complete and compact solution to (repeated) DI-SPA data. Using our strategy, the peptide identification can be improved above 30% with high reproducibility (70.0%). Notably, the label-free quantification of repeated DI-SPA can be successfully obtained with high accuracy (mean median error, 0.108) and high reproducibility (median error, 0.001). We believe our RE-FIGS method could boost the broad application of the (repeated) DI-SPA method and offer a new choice for proteomic analysis.

RNA granule-clustered mitochondrial aminoacyl-tRNA synthetases form multiple complexes with the potential to fine-tune tRNA aminoacylation.

Mitochondrial RNA metabolism is suggested to occur in identified compartmentalized foci, i.e. mitochondrial RNA granules (MRGs). Mitochondrial aminoacyl-tRNA synthetases (mito aaRSs) catalyze tRNA charging and are key components in mitochondrial gene expression. Mutations of mito aaRSs are associated with various human disorders. However, the suborganelle distribution, interaction network and regulatory mechanism of mito aaRSs remain largely unknown. Here, we found that all mito aaRSs partly colocalize with MRG, and this colocalization is likely facilitated by tRNA-binding capacity. A fraction of human mitochondrial AlaRS (hmtAlaRS) and hmtSerRS formed a direct complex via interaction between catalytic domains in vivo. Aminoacylation activities of both hmtAlaRS and hmtSerRS were fine-tuned upon complex formation in vitro. We further established a full spectrum of interaction networks via immunoprecipitation and mass spectrometry for all mito aaRSs and discovered interactions between hmtSerRS and hmtAsnRS, between hmtSerRS and hmtTyrRS and between hmtThrRS and hmtArgRS. The activity of hmtTyrRS was also influenced by the presence of hmtSerRS. Notably, hmtSerRS utilized the same catalytic domain in mediating several interactions. Altogether, our results systematically analyzed the suborganelle localization and interaction network of mito aaRSs and discovered several mito aaRS-containing complexes, deepening our understanding of the functional and regulatory mechanisms of mito aaRSs.

TreeQNet: a webserver for Treatment evaluation with Quantified Network.

BACKGROUND: Personalized therapy has been at the forefront of cancer care, making cancer treatment more effective. Since cancer patients respond individually to drug therapy, predicting the sensitivity of each patient to specific drugs is very helpful to apply therapeutic agents. Traditional methods focus on node (molecular) information but ignore relevant interactions among different nodes, which has very limited application in complex situations, such as cancer drug responses in real clinical practice. RESULTS: Treatment evaluation with Quantified Network (TreeQNet) is a webserver which could predict sensitivity to drugs for patients through the innovative use of proteomic and phosphoproteomic network from tumor tissues. CONCLUSION: TreeQNet service: http://bioinfo.ustc.edu.cn/ . TreeQNet source code: https://github.com/Really00/treeqnet-web-front/ .

Synthesis and shaping of metal-organic frameworks: a review.

Metal-organic frameworks (MOFs) possess excellent advantages, such as high porosity, large specific surface area, and an adjustable structure, showing good potential for applications in gas adsorption and separation, catalysis, conductivity, sensing, magnetism, etc. However, they still suffer from significant limitations in terms of the scale-up synthesis and shaping, hindering the realization of large-scale commercial applications. Despite some attempts having been devoted to addressing this, challenges remain. In this paper, we outline the advantages and drawbacks of existing synthetic routes such as electrochemistry, microwave, ultrasonic radiation, green solvent reflux, room temperature stirring, steam-assisted transformation, mechanochemistry, and fluid chemistry in terms of scale-up production. Then, the shaping methods of MOFs such as extrusion, mechanical compaction, rolling granulation, spray drying, gel technology, embedded granulation, phase inversion, 3D printing and other shaping methods for the preparation of membranes, coatings and nanoparticles are discussed. Finally, perspectives on the large-scale synthesis and shaping of MOFs are also proposed. This work helps provide in-depth insight into the scale-up production and shaping process of MOFs and boost commercial applications of MOFs.

HDL quality features revealed by proteome‒lipidome connectivity are associated with atherosclerotic disease.

Lipoprotein, especially high-density lipoprotein (HDL), particles are composed of multiple heterogeneous subgroups containing various proteins and lipids. The molecular distribution among these subgroups is closely related to cardiovascular disease (CVD). Here, we established high-resolution proteomics and lipidomics (HiPL) methods to depict the molecular profiles across lipoprotein (Lipo-HiPL) and HDL (HDL-HiPL) subgroups by optimizing the resolution of anion-exchange chromatography and comprehensive quantification of proteins and lipids on the omics level. Furthermore, based on the Pearson correlation coefficient analysis of molecular profiles across high-resolution subgroups, we achieved the relationship of proteome‒lipidome connectivity (PLC) for lipoprotein and HDL particles. By application of these methods to high-fat, high-cholesterol diet-fed rabbits and acute coronary syndrome (ACS) patients, we uncovered the delicate dynamics of the molecular profile and reconstruction of lipoprotein and HDL particles. Of note, the PLC features revealed by the HDL-HiPL method discriminated ACS from healthy individuals better than direct proteome and lipidome quantification or PLC features revealed by the Lipo-HiPL method, suggesting their potential in ACS diagnosis. Together, we established HiPL methods to trace the dynamics of the molecular profile and PLC of lipoprotein and even HDL during the development of CVD.

Inhibition of a Novel CLK1-THRAP3-PPARγ Axis Improves Insulin Sensitivity.

Increasing energy expenditure by promoting "browning" in adipose tissues is a promising strategy to prevent obesity and associated diabetes. To uncover potential targets of cold exposure, which induces energy expenditure, we performed phosphoproteomics profiling in brown adipose tissue of mice housed in mild cold environment at 16°C. We identified CDC2-like kinase 1 (CLK1) as one of the kinases that were significantly downregulated by mild cold exposure. In addition, genetic knockout of CLK1 or chemical inhibition in mice ameliorated diet-induced obesity and insulin resistance at 22°C. Through proteomics, we uncovered thyroid hormone receptor-associated protein 3 (THRAP3) as an interacting partner of CLK1, further confirmed by co-immunoprecipitation assays. We further demonstrated that CLK1 phosphorylates THRAP3 at Ser243, which is required for its regulatory interaction with phosphorylated peroxisome proliferator-activated receptor gamma (PPARγ), resulting in impaired adipose tissue browning and insulin sensitivity. These data suggest that CLK1 plays a critical role in controlling energy expenditure through the CLK1-THRAP3-PPARγ axis.

DDX56 modulates post-transcriptional Wnt signaling through miRNAs and is associated with early recurrence in squamous cell lung carcinoma.

BACKGROUND: Early recurrence is a major obstacle to prolonged postoperative survival in squamous cell lung carcinoma (SqCLC). The molecular mechanisms underlying early SqCLC recurrence remain unclear, and effective prognostic biomarkers for predicting early recurrence are needed. METHODS: We analyzed primary tumor samples of 20 SqCLC patients using quantitative proteomics to identify differentially-expressed proteins in patients who experienced early versus late disease recurrence. The expression and prognostic significance of DDX56 was evaluated using a SqCLC tumor tissue microarray and further verified using different online databases. We performed in vitro and in vivo experiments to obtain detailed molecular insight into the functional role of DDX56 in SqCLC. RESULTS: We found that DDX56 exhibited increased expression in tumors of patients who experienced early versus late disease recurrence. Increased DDX56 expression in SqCLC tumors was subsequently confirmed as an independent prognostic factor of poor recurrence-free survival in independent SqCLC cohorts. Functionally, DDX56 promotes SqCLC cell growth and migration in vitro, and xenograft tumor progression in vivo. Mechanistically, DDX56 post-transcriptionally promotes expression of multiple Wnt signaling pathway-related genes, including CTNNB1, WNT2B, and represses a subset of miRNAs, including miR-378a-3p, a known suppressor of Wnt signaling. Detailed analysis revealed that DDX56 facilitated degradation of primary miR-378a, leading to down-regulation of mature miR-378a-3p and thus derepression of the target gene WNT2B. CONCLUSION: We identified DDX56 as a novel independent prognostic biomarker that exerts its oncogenic effects through miRNA-mediated post-transcriptional regulation of Wnt signaling genes to promote early SqCLC recurrence. DDX56 may assist in identifying SqCLC patients at increased risk of early recurrence and who could benefit from Wnt signaling-targeted therapies.

Mutually exclusive substrate selection strategy by human m3C RNA transferases METTL2A and METTL6.

tRNAs harbor the most diverse posttranscriptional modifications. The 3-methylcytidine (m3C) is widely distributed at position C32 (m3C32) of eukaryotic tRNAThr and tRNASer species. m3C32 is decorated by the single methyltransferase Trm140 in budding yeasts; however, two (Trm140 and Trm141 in fission yeasts) or three enzymes (METTL2A, METTL2B and METTL6 in mammals) are involved in its biogenesis. The rationale for the existence of multiple m3C32 methyltransferases and their substrate discrimination mechanism is hitherto unknown. Here, we revealed that both METTL2A and METTL2B are expressed in vivo. We purified human METTL2A, METTL2B, and METTL6 to high homogeneity. We successfully reconstituted m3C32 modification activity for tRNAThr by METT2A and for tRNASer(GCU) by METTL6, assisted by seryl-tRNA synthetase (SerRS) in vitro. Compared with METTL2A, METTL2B exhibited dramatically lower activity in vitro. Both G35 and t6A at position 37 (t6A37) are necessary but insufficient prerequisites for tRNAThr m3C32 formation, while the anticodon loop and the long variable arm, but not t6A37, are key determinants for tRNASer(GCU) m3C32 biogenesis, likely being recognized synergistically by METTL6 and SerRS, respectively. Finally, we proposed a mutually exclusive substrate selection model to ensure correct discrimination among multiple tRNAs by multiple m3C32 methyltransferases.

FIGS: Featured Ion-Guided Stoichiometry for Data-Independent Proteomics through Dynamic Deconvolution.

Data-independent acquisition (DIA) has significant advantages for mass spectrometry (MS)-based peptide quantification, while mixed spectra remain challenging for precise stoichiometry. We here choose to analyze the library spectra in specific sets preferentially and locally. Accordingly, the featured ions are defined as the fragment ions uniquely assigned to corresponding precursors in a given spectrum set, which are generated by dynamic deconvolution of the mixed mass spectra. Then, we present featured ion-guided stoichiometry (FIGS), a universal method for accurate and robust peptide quantification for the DIA-MS data. We validate the high performance on the quantification sensitivity, accuracy, and efficiency of FIGS. Notably, our FIGS dramatically improves the quantification accuracy for the full dynamic range, especially for low-abundance peptides.

MKRN3-mediated ubiquitination of Poly(A)-binding proteins modulates the stability and translation of GNRH1 mRNA in mammalian puberty.

The family of Poly(A)-binding proteins (PABPs) regulates the stability and translation of messenger RNAs (mRNAs). Here we reported that the three members of PABPs, including PABPC1, PABPC3 and PABPC4, were identified as novel substrates for MKRN3, whose deletion or loss-of-function mutations were genetically associated with human central precocious puberty (CPP). MKRN3-mediated ubiquitination was found to attenuate the binding of PABPs to the poly(A) tails of mRNA, which led to shortened poly(A) tail-length of GNRH1 mRNA and compromised the formation of translation initiation complex (TIC). Recently, we have shown that MKRN3 epigenetically regulates the transcription of GNRH1 through conjugating poly-Ub chains onto methyl-DNA bind protein 3 (MBD3). Therefore, MKRN3-mediated ubiquitin signalling could control both transcriptional and post-transcriptional switches of mammalian puberty initiation. While identifying MKRN3 as a novel tissue-specific translational regulator, our work also provided new mechanistic insights into the etiology of MKRN3 dysfunction-associated human CPP.

The human tRNA taurine modification enzyme GTPBP3 is an active GTPase linked to mitochondrial diseases.

GTPBP3 and MTO1 cooperatively catalyze 5-taurinomethyluridine (τm5U) biosynthesis at the 34th wobble position of mitochondrial tRNAs. Mutations in tRNAs, GTPBP3 or MTO1, causing τm5U hypomodification, lead to various diseases. However, efficient in vitro reconstitution and mechanistic study of τm5U modification have been challenging, in part due to the lack of pure and active enzymes. A previous study reported that purified human GTPBP3 (hGTPBP3) is inactive in GTP hydrolysis. Here, we identified the mature form of hGTPBP3 and showed that hGTPBP3 is an active GTPase in vitro that is critical for tRNA modification in vivo. Unexpectedly, the isolated G domain and a mutant with the N-terminal domain truncated catalyzed GTP hydrolysis to only a limited extent, exhibiting high Km values compared with that of the mature enzyme. We further described several important pathogenic mutations of hGTPBP3, associated with alterations in hGTPBP3 localization, structure and/or function in vitro and in vivo. Moreover, we discovered a novel cytoplasm-localized isoform of hGTPBP3, indicating an unknown potential noncanonical function of hGTPBP3. Together, our findings established, for the first time, the GTP hydrolysis mechanism of hGTPBP3 and laid a solid foundation for clarifying the τm5U modification mechanism and etiology of τm5U deficiency-related diseases.

Integrated Omics of Metastatic Colorectal Cancer.

We integrate the genomics, proteomics, and phosphoproteomics of 480 clinical tissues from 146 patients in a Chinese colorectal cancer (CRC) cohort, among which 70 had metastatic CRC (mCRC). Proteomic profiling differentiates three CRC subtypes characterized by distinct clinical prognosis and molecular signatures. Proteomic and phosphoproteomic profiling of primary tumors alone successfully distinguishes cases with metastasis. Metastatic tissues exhibit high similarities with primary tumors at the genetic but not the proteomic level, and kinase network analysis reveals significant heterogeneity between primary colorectal tumors and their liver metastases. In vivo xenograft-based drug tests using 31 primary and metastatic tumors show personalized responses, which could also be predicted by kinase-substrate network analysis no matter whether tumors carry mutations in the drug-targeted genes. Our study provides a valuable resource for better understanding of mCRC and has potential for clinical application.

Proteome-wide data analysis reveals tissue-specific network associated with SARS-CoV-2 infection.

For patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the damages to multiple organs have been clinically observed. Since most of current investigations for virus-host interaction are based on cell level, there is an urgent demand to probe tissue-specific features associated with SARS-CoV-2 infection. Based on collected proteomic datasets from human lung, colon, kidney, liver, and heart, we constructed a virus-receptor network, a virus-interaction network, and a virus-perturbation network. In the tissue-specific networks associated with virus-host crosstalk, both common and different key hubs are revealed in diverse tissues. Ubiquitous hubs in multiple tissues such as BRD4 and RIPK1 would be promising drug targets to rescue multi-organ injury and deal with inflammation. Certain tissue-unique hubs such as REEP5 might mediate specific olfactory dysfunction. The present analysis implies that SARS-CoV-2 could affect multi-targets in diverse host tissues, and the treatment of COVID-19 would be a complex task.

Multi-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation.

Although a multiple-protease based shotgun proteomics method was shown to improve coverage for phosphosite identification, this traditional pipeline is time-consuming and can be of low reproducibility. Here, we demonstrated a multi-in-one strategy to saturate the phosphosite coverage by combining the multiple-proteases based digestion, one-step enrichment, and one-shot data-independent acquisition (DIA) as short as 1 h. In the "three-in-one" workflow, more than 19,700 and 13,500 phosphosites could be identified in the trypsin-like and nontrypsin-like mixture, respectively. By combining and applying our "three-in-one" strategy, nearly 30,000 phosphosites could be successfully quantified with high reproducibility across samples. Meanwhile, we developed a faster and more robust method, in which over a single 66 min chromatographic method by "six-in-one" strategy, 19,445 phosphosites could be successfully localized, drastically reducing the database search time required in the traditional method. Inspiringly, this strategy further enabled us to discover 2,675 phosphorylation events on the low abundant transcription factors (TFs) in living cells with high coverage. More broadly, the multi-in-one strategy makes the multiple-protease digestion in large-scale analysis applicable, with low time-consuming, high sensitivity, improved coverage, and high reproducibility.

Ionic Self-Assembled Luminescent Nanospheres from Cationic Polyelectrolyte and Eu-Containing Polyoxometalate.

Using the ionic self-assembly (ISA) strategy to combine Eu-containing polyoxometalates (Eu-POMs) and organic molecules mainly through noncovalent electrostatic interactions can protect Eu-POMs from solvent quenching of luminescence and enhance their processability. For this reason, a cationic polyelectrolyte, branched polyethyleneimine (PEI), and a Eu-POM, Na9(EuW10O36)·32H2O (EuW10), were used here to construct luminescence-enhanced spherical aggregates with diameters ranging from 50 to 200 nm. At a fixed concentration of EuW10, the phase behavior and luminescence properties of the mixture could be modulated by the PEI concentration. Such ISA-induced aggregates could effectively shield water molecules and result in better photophysical properties. Compared to bare EuW10, the absolute quantum yield and lifetime of luminescence for aggregates increased 10 and 5 times, respectively. Meanwhile, the sensitivity of the EuW10 coordination structure to the environment made it possible for obtained aggregates being used to detect either copper cations or permanganate anions due to their strong specific quenching effects to luminescence. Such a new type of luminescent soft material not only provided a reference for exploring the luminescence enhancement mechanism of lanthanide through self-assembly in aqueous solution but also exhibited potential in detection by luminescence analysis.

Luminescent Vesicles Self-assembled Directly from an Amphiphilic Europium Complex in an Ionic Liquid.

Novel luminescent vesicles with enhanced emission were successfully achieved for the first time by an amphiphilic europium complex through its spontaneously self-assembly in an ionic liquid, 1-butyl-3-methylimidazolium hexafluorophosphate ([Bmim]PF6). The complex was prepared by europium ions coordinated with terpyridine ligands, which were modified with the hydrophilic ethoxy chains. The enhanced absolute quantum yield and prolonged fluorescence lifetime of complex in vesicles were observed because of the effective shielding of the quench effects caused by both solvent and complex concentration. Compared to the aggregates formed in other solvents, the vesicles obtained in [Bmim]PF6 showed the best luminescence intensity with the quantum efficiency (37.74%) and luminescent emission lifetime (1.915 ms) both increased about 10 times more. Furthermore, this europium complex was designed to show unsaturated coordination, which made the vesicle luminescence easily quenched when contacting with water. The fluorescence sensing of water with this vesicle as probe was therefore possible, where several unique properties like high sensitivity, low detection limit (0.05 vol %), visible color change, and fast response had been observed. Such designed systems are expected to provide strategies to develop novel supramolecular aggregates in ionic liquids and offer guidance for luminescence detection with facile and wide applications.