Rat Model of Neuropathic Pain Induced by Spinal Nerve Ligation: A New Approach via an Oblique Lateral Incision.

Purpose: The spinal nerve ligation (SNL) model is a typical peripheral neuropathic pain model. During its construction, the removal of paraspinal muscles and transverse processes typically occurs, resulting in additional trauma that may potentially affect the pathophysiologic process of neuropathic pain. This study aimed to investigate the feasibility of establishing a more reliable SNL model using an oblique lateral approach. Methods: 36 adult male Sprague-Dawley rats were randomly divided into three groups: the traditional SNL (T-SNL) group, the new SNL (N-SNL) group (where the left L5 spinal nerve was ligated with a titanium clip via an oblique lateral approach), and the sham-operated (Sham) group. The operation time, Intraoperative bleeding, the number of rats that died, gait behavior, mechanical and cold pain threshold were recorded and measured. Stereology technology was used to calculate the number of microglia in spinal dorsal horn, and the Enzyme-linked immunosorbent assay (ELISA) technology was used to detect the expression of TNF-α and IL-1ß in spinal cord as well as C-reactive protein (CRP) in serum in order to assess the effect of surgery on animal inflammation. Results: Compared with the T-SNL group, operative time and intraoperative bleeding were significantly decreased in the N-SNL group. Within 14 days postoperation, one rat in the N-SNL group was died, two rats in the T-SNL group were died. Compared with the Sham group, the N-SNL group showed obvious spontaneous pain behavior, decreased the pain thresholds, the number of microglia and the expression of TNF-α and IL-1ß were significantly increased, and there was no significant difference in these indexes compared with T-SNL group. There was no significant difference in serum CRP levels among the three groups. Conclusion: This study suggests that the oblique lateral approach SNL model is a reliable NP model with the advantages of good reproducibility, accessibility, and low trauma.

Hydrological response and crack resistance of polypropylene-fiber reinforced compacted steel slag-bentonite mixtures under wetting-drying cycles.

Desiccation-induced cracks in a compacted clay liner significantly deteriorate the hydraulic barrier performance of landfill covers. The present study explores the effects of polypropylene (PP) fiber reinforcement on the hydrological response and crack resistance of compacted steel slag (SS; 90 wt%) - bentonite (10 wt%) mixtures under drying and wetting cycles. Comprehensive tests were conducted to explore the impact of different fiber lengths (6-12 mm) and contents (0-0.4 % wt.%), including hydraulic conductivity tests for measuring the saturated hydraulic conductivity (ks), unconfined-penetration tests for measuring the tensile strength, small-sized plate tests for quantifying crack development, and large-sized bucket tests for studying the hydrological response and crack characteristics. Higher fiber contents and longer fiber lengths increased the ks-value of the specimens. For a 0.3 % fiber content, the tensile strength peaked for the 9-mm fiber. Consistently, the specimen reinforced with the 9-mm fibers exhibited significantly fewer cracks than those reinforced with the 6-mm and 12-mm fibers. It was because the 6-mm fibers had a shorter anchorage length, while the 12-mm fibers tended to agglomerate. The large-sized bucket tests showed that fiber reinforcement limited crack development significantly under wetting and drying cycles, reducing the rainfall infiltration by 40 % and enhancing the soil water retention capacity. Finally, a 0.3 wt% of 9-mm PP was recommended to reinforce the compacted SS-bentonite mixtures.

Identification of stable reference genes for relative quantification of long RNA expression in urinary extracellular vesicles.

Urinary extracellular vesicles (uEVs) are rich in valuable biomolecule information which are increasingly recognized as potential biomarkers for various diseases. uEV long RNAs are among the critical cargos capable of providing unique transcriptome information of the source cells. However, consensus regarding ideal reference genes for relative long RNAs quantification in uEVs is not available as of date. Here we explored stable reference genes through profiling the long RNA expression by RNA-seq following unsupervised analysis and validation studies. Candidate reference genes were identified using four algorithms: NormFinder, GeNorm, BestKeeper and the Delta Ct method, followed by validation. RNA profile showed uEVs contained abundant long RNAs information and the core transcriptome was related to cellular structures, especially ribosome which functions mainly as translation, protein and RNA binding molecules. Analysis of RNA-seq data identified RPL18A, RPL11, RPL27, RACK1, RPSA, RPL41, H1-2, RPL4, GAPDH, RPS27A as candidate reference genes. RT-qPCR validation revealed that RPL41, RPSA and RPL18A were reliable reference genes for long RNA quantification in uEVs from patients with diabetes mellitus (DM), diabetic nephropathy (DN), IgA nephropathy (IgAN) and prostate cancer (PCA). Interestingly, RPL41 also outperformed traditional reference genes in renal tissues of DN and IgAN, as well as in plasma EVs of several types of cancers. The stable reference genes identified in this study may facilitate development of uEVs as novel biomarkers and increase the accuracy and comparability of biomarker studies.

Knockdown the moyamoya disease susceptibility gene, RNF213, upregulates the expression of basic fibroblast growth factor and matrix metalloproteinase-9 in bone marrow derived mesenchymal stem cells.

Moyamoya disease (MMD) is a chronic, progressive cerebrovascular occlusive disease. Ring finger protein 213 (RNF213) is a susceptibility gene of MMD. Previous studies have shown that the expression levels of angiogenic factors increase in MMD patients, but the relationship between the susceptibility gene RNF213 and these angiogenic mediators is still unclear. The aim of the present study was to investigate the pathogenesis of MMD by examining the effect of RNF213 gene knockdown on the expression of matrix metalloproteinase-9 (MMP-9) and basic fibroblast growth factor (bFGF) in rat bone marrow-derived mesenchymal stem cells (rBMSCs). Firstly, 40 patients with MMD and 40 age-matched normal individuals (as the control group) were enrolled in the present study to detect the levels of MMP-9 and bFGF in serum by ELISA. Secondly, Sprague-Dawley male rat BMSCs were isolated and cultured using the whole bone marrow adhesion method, and subsequent phenotypic analysis was performed by flow cytometry. Alizarin red and oil red O staining methods were used to identify osteogenic and adipogenic differentiation, respectively. Finally, third generation rBMSCs were transfected with lentivirus recombinant plasmid to knockout expression of the RNF213 gene. After successful transfection was confirmed by reverse transcription-quantitative PCR and fluorescence imaging, the expression levels of bFGF and MMP-9 mRNA in rBMSCs and the levels of bFGF and MMP-9 protein in the supernatant of the culture medium were detected on the 7th and 14th days after transfection. There was no significant difference in the relative expression level of bFGF among the three groups on the 7th day. For the relative expression level of MMP-9, there were significant differences on the 7th day and 14th day. In addition, there was no statistically significant difference in the expression of bFGF in the supernatant of the RNF213 shRNA group culture medium, while there was a significant difference in the expression level of MMP-9. The knockdown of the RNF213 gene affects the expression of bFGF and MMP-9. However, further studies are needed to determine how they participate in the pathogenesis of MMD. The findings of the present study provide a theoretical basis for clarifying the pathogenesis and clinical treatment of MMD.

Numerical investigation and optimal design of capillary barrier cover with passive gas collection pipes on the performance at limiting landfill gas emissions.

Relying solely on soil properties may not fully ensure the performance of capillary barrier covers at limiting landfill gas (LFG) emissions. This study proposed to install passive gas collection pipes in the coarse-grained soil layers of capillary barrier covers to enhance their performance at limiting LFG emissions. First, the LFG generation rate of municipal solid waste and its influencing factors were analyzed based on empirical formulas. This information provided necessary bottom boundary conditions for the analyses of LFG transport through capillary barrier covers with passive gas collection pipes (CBCPPs). Then, numerical simulations were conducted to investigate the LFG transport properties through CBCPPs and reveal relevant influencing factors. Finally, practical suggestions were proposed to optimize the design of CBCPPs. The results indicated that the maximum whole-site LFG generation rate occurred at the end of landfilling operation. The gas collection efficiency (E) of CBCPPs was mainly controlled by the ratio of the intrinsic permeability between the coarse- and fine-grained soil (K2/K1) and the laying spacing between gas collection pipes (D). E increased as K2/K1 increased but decreased as D increased. An empirical expression for estimating E based on K2/K1 and D was proposed. In practice, CBCPPs were supposed to be constructed once the landfilling operation finished. It is best to select the fine- and coarse-grained soils with K2/K1 exceeding 10,000 to construct CBCPPs.

Comprehensive single-cell analysis reveals heterogeneity of fibroblast subpopulations in ovarian cancer tissue microenvironment.

Background: Ovarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated. Methods: In this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer. Results: Through integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFß signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance. Conclusions: In the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.

Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution.

Tumor deconvolution enables the identification of diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold-standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA sequencing) rather than protein levels. Despite the popularity of gene expression datasets, protein levels often provide a more accurate view of rare cell types. To facilitate the use, development, and reproducibility of multiomic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic datasets. Decomprolute incorporates the large-scale multiomic datasets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. http://pnnl-compbio.github.io/decomprolute.

Harnessing redox proteomics to study metabolic regulation and stress response in lignin-fed Rhodococci.

BACKGROUND: Rhodococci are studied for their bacterial ligninolytic capabilities and proclivity to accumulate lipids. Lignin utilization is a resource intensive process requiring a variety of redox active enzymes and cofactors for degradation as well as defense against the resulting toxic byproducts and oxidative conditions. Studying enzyme expression and regulation between carbon sources will help decode the metabolic rewiring that stymies lignin to lipid conversion in these bacteria. Herein, a redox proteomics approach was applied to investigate a fundamental driver of carbon catabolism and lipid anabolism: redox balance. RESULTS: A consortium of Rhodococcus strains was employed in this study given its higher capacity for lignin degradation compared to monocultures. This consortium was grown on glucose vs. lignin under nitrogen limitation to study the importance of redox balance as it relates to nutrient availability. A modified bottom-up proteomics workflow was harnessed to acquire a general relationship between protein abundance and protein redox states. Global proteomics results affirm differential expression of enzymes involved in sugar metabolism vs. those involved in lignin degradation and aromatics metabolism. As reported previously, several enzymes in the lipid biosynthetic pathways were downregulated, whereas many involved in ß-oxidation were upregulated. Interestingly, proteins involved in oxidative stress response were also upregulated perhaps in response to lignin degradation and aromatics catabolism, which require oxygen and reactive oxygen species and generate toxic byproducts. Enzymes displaying little-to-no change in abundance but differences in redox state were observed in various pathways for carbon utilization (e.g., ß­ketoadipate pathway), lipid metabolism, as well as nitrogen metabolism (e.g., purine scavenging/synthesis), suggesting potential mechanisms of redox-dependent regulation of metabolism. CONCLUSIONS: Efficient lipid production requires a steady carbon and energy flux while balancing fundamental requirements for enzyme production and cell maintenance. For lignin, we theorize that this balance is difficult to establish due to resource expenditure for enzyme production and stress response. This is supported by significant changes to protein abundances and protein cysteine oxidation in various metabolic pathways and redox processes.

Exosomes derived from ovarian cancer cells regulate proliferation and migration of cancer-associated fibroblasts.

Cancer-associated fibroblast (CAF) is an essential risk factor for ovarian cancer. Exosomes can mediate cellular communication in the tumour microenvironment, but the interaction of tumour cell exosomes with CAF is less studied in Ovarian cancer. This study identified H19/miR-29c-3p/LOXL2-COL1A1 as a ceRNA regulatory network involved in regulating tumour matrix-associated signaling pathways associated with CAF. Cellular assays demonstrated that exosomes from ovarian cancer cell line SKOV3 significantly promoted the proliferation and migration of CAF. The results of mixed transplantation tumour experiments in nude mice showed that exosomes of SKOV3 significantly promoted tumour growth. Ovarian cancer tumour-derived exosomes can regulate CAF proliferation and migration through H19/miR-29c-3p/LOXL2-COL1A1. This study reveals the regulatory role of tumour exosomes on CAF, which may provide a theoretical basis for the development of therapeutic regimens targeting fibroblasts in ovarian cancer.

E2F family play important roles in tumorigenesis.

Tumors are serious threats to human health. The transcription factors are regarded as the potential targets for tumor treatment. As an important family of transcription factors, E2F family transcription factors (E2Fs) play vital roles in cell proliferation and regulation. However, the expression feature, gene functions, and molecular interactions of E2Fs in tumorigenesis are not clear. In this study, the transcriptome data, mutation data, and protein-protein interaction data of 10 high-incidence tumors in China from the TCGA database were integrated and analyzed to explore the expression, structure, function, mutation, and phylogenetic characteristics of E2Fs. The results showed that E2F1 and E2F7 were regularly upregulated in the tumor samples. Moreover, E2Fs participated in the regulation of the cell cycle, cell aging, and other signaling pathways. As an important regulator, E2F1 interacted with more proteins than other E2Fs. At the same time, the genetic mutation types of E2Fs varied in tumor type and patient sex, of which gene amplification accounts for the largest proportion. Phylogenetic analysis showed that E2Fs were conserved in 41 species, including fruit flies, nematodes, and humans. Meanwhile, E2Fs had a tendency for gene expansion during evolution. In conclusion, this study clarified the expression pattern, mutation characteristics, and evolutionary trend of E2Fs in high-incidence tumors in China, and suggested that E2F family transcription factors could be novel diagnostic markers for tumor diseases. Furthermore, this work can provide a theoretical basis for the development of anti-tumor-targeted drugs.

Comparison of oral sodium phosphate tablets and polyethylene glycol lavage solution for colonoscopy preparation: a systematic review and meta-analysis of randomized clinical trials.

Objective: To systematically compare the bowel cleaning ability, patient tolerance and safety of oral sodium phosphate tablets (NaPTab) and oral polyethylene glycol electrolyte lavage solution (PEGL) to inform clinical decision making. Methods: PubMed, Embase, CBM, WanFang Data, CNKI, and VIP databases were searched for studies that used randomized controlled trials (RCTs) to compare the roles of NaPTab and PEGL in bowel preparation before colonoscopy. Two reviewers independently screened the studies, extracted data, and assessed the risk of bias in the included papers. A meta-analysis was performed using RevMan 5.3 software. Results: A total of 13 RCTs were eligible for inclusion, including 2,773 patients (1,378 and 1,395 cases in the NaPTab and PEGL groups, respectively). Meta-analysis revealed no significant difference in the cleansing quality of the NaPTab and PEGL groups [RR 1.02, 95% CI (0.96-1.08), P = 0.46]. The incidence of nausea was lower in the NaPTab group than in the PEGL group [RR 0.67, 95% CI (0.58-0.76), p < 0.00001]. Patients rated the taste of NaPTab higher than PEGL [RR 1.33, 95% CI (1.26-1.40), P < 0.00001]. Willingness to repeat the treatment was also higher in the NaPTab group than in the PEGL group [RR 1.52, 95% CI (1.28-1.80), P < 0.00001]. Both serum potassium and serum calcium decreased in both groups after the preparation; however, meta-analysis revealed that both minerals decreased more in the NaPTab group than in the PEGL group [MD = 0.38, 95% CI (0.13-0.62), P = 0.006 for serum potassium and MD = 0.41, 95% CI (0.04-0.77), P = 0.03 for serum calcium]. Meanwhile, serum phosphorus increased in both groups after the preparation; however, levels increased more in the NaPTab group than in the PEGL group [MD 4.51, (95% CI 2.9-6.11), P < 0.00001]. Conclusions: While NaP tablets and PEGL were shown to have a similar cleaning effect before colonoscopy, NaP tablets had improved patient tolerance. However, NaP tablets had a strong effect on serum potassium, calcium, and phosphorus levels. For patients with low potassium, low calcium, and renal insufficiency, NaP tablets should be prescribed with caution. For those at high-risk for acute phosphate nephropathy, NaP tablets should be avoided. Given the low number and quality of included studies, these conclusions will require additional verification by large high-quality studies. Systematic review registration: 10.37766/inplasy2023.5.0013, identifier: NPLASY202350013.

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways.

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)-also known as multiple reaction monitoring (MRM)-and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

Virome analysis provides new insights into the association between viruses and Parkinson's disease.

Parkinson's disease (PD) is a kind of neurodegenerative disease that causes a huge burden to society. Previous studies have suggested the association between PD and multiple viruses. However, there is still a lack of a virome study about PD. This study systematically identified viruses from the public RNA-sequencing data of more than 700 samples from both PD patients and the control group (most were healthy people). Only nine viruses such as human betaherpesvirus 5 and Merkel cell polyomavirus have been detected in several human brain tissues of the central nervous system, the appendix, and blood of PD patients, and all of these viruses were also detected in the control group. Most viruses were observed to have low abundance in no more than three tissues. No statistically significant differences were observed between the virus abundance in the PD patients and the control group for all viruses. The positive rates of most viruses in PD patients were higher or similar to that in the control group, although those were less than 5% for most viruses. Overall, this is the first study to systematically investigate the virome in PD patients, and provides new insights into the association between viruses and PD.

Defining the S-Glutathionylation Proteome by Biochemical and Mass Spectrometric Approaches.

Protein S-glutathionylation (SSG) is a reversible post-translational modification (PTM) featuring the conjugation of glutathione to a protein cysteine thiol. SSG can alter protein structure, activity, subcellular localization, and interaction with small molecules and other proteins. Thus, it plays a critical role in redox signaling and regulation in various physiological activities and pathological events. In this review, we summarize current biochemical and analytical approaches for characterizing SSG at both the proteome level and at individual protein levels. To illustrate the mechanism underlying SSG-mediated redox regulation, we highlight recent examples of functional and structural consequences of SSG modifications. Finally, we discuss the analytical challenges in characterizing SSG and the thiol PTM landscape, future directions for understanding of the role of SSG in redox signaling and regulation and its interplay with other PTMs, and the potential role of computational approaches to accelerate functional discovery.

Screening of traditional Chinese medicine monomers as ribonucleotide reductase M2 inhibitors for tumor treatment.

BACKGROUND: Ribonucleotide reductase (RR) is a key enzyme in tumor proliferation, especially its subunit-RRM2. Although there are multiple therapeutics for tumors, they all have certain limitations. Given their advantages, traditional Chinese medicine (TCM) monomers have become an important source of anti-tumor drugs. Therefore, screening and analysis of TCM monomers with RRM2 inhibition can provide a reference for further anti-tumor drug development. AIM: To screen and analyze potential anti-tumor TCM monomers with a good binding capacity to RRM2. METHODS: The Gene Expression Profiling Interactive Analysis database was used to analyze the level of RRM2 gene expression in normal and tumor tissues as well as RRM2's effect on the overall survival rate of tumor patients. TCM monomers that potentially act on RRM2 were screened via literature mining. Using AutoDock software, the screened monomers were docked with the RRM2 protein. RESULTS: The expression of RRM2 mRNA in multiple tumor tissues was significantly higher than that in normal tissues, and it was negatively correlated with the overall survival rate of patients with the majority of tumor types. Through literature mining, we discovered that berberine, ursolic acid, gambogic acid, cinobufagin, quercetin, daphnetin, and osalmide have inhibitory effects on RRM2. The results of molecular docking identified that the above TCM monomers have a strong binding capacity with RRM2 protein, which mainly interacted through hydrogen bonds and hydrophobic force. The main binding sites were Arg330, Tyr323, Ser263, and Met350. CONCLUSION: RRM2 is an important tumor therapeutic target. The TCM monomers screened have a good binding capacity with the RRM2 protein.

MAGI2-AS3 restrains proliferation, glycolysis, and triggers apoptosis in acute lymphoblastic leukemia via regulating miR-452-5p/FOXN3 pathway.

Objectives: MAGI2-AS3 is a cancer suppressor gene of multiple malignancies. Acute lymphoblastic leukemia (ALL) is an important type of leukemia that especially occurs in children. Our work evaluated the modulation of MAGI2-AS3 in ALL. Materials and Methods: qPCR and Western blotting were adopted for detection of target molecular expression. Growth and apoptosis were determined by CCK8 assay and Annexin V/PI staining. Glycolysis was detected by commercial kits. The direct binding between miR-452-5p and MAGI2-AS3 or FOXN3 was assessed by luciferase reporter assay. Tumor growth was measured in nude mice in vivo. Results: MAGI2-AS3 was down-regulated in ALL. Enforced expression of MAGI2-AS3 inhibited growth and glycolysis while promoting apoptosis of ALL cells. Moreover, MAGI2-AS3 up-regulated FOXN3 via sponging miR-452-5p. FOXN3 depletion abrogated MAGI2-AS3-mediated anti-cancer action. More importantly, MAGI2-AS3 repressed ALL cell growth in nude mice through regulation of miR-452-5p/FOXN3. Conclusion: MAGI2-AS3 inhibits ALL development via modulating miR-452-5p/FOXN3.

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering.

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper's transparent peer review process is included in the supplemental information.

Urinary sediment CCL5 messenger RNA as a potential prognostic biomarker of diabetic nephropathy.

BACKGROUND: Urinary sediment messenger RNAs (mRNAs) have been shown as novel biomarkers of kidney disease. We aimed to identify targeted urinary mRNAs in diabetic nephropathy (DN) based on bioinformatics analysis and clinical validation. METHODS: Microarray studies of DN were searched in the GEO database and Nephroseq platform. Gene modules negatively correlated with estimated glomerular filtration rate (eGFR) were identified by informatics methods. Hub genes were screened within the selected modules. In validation cohorts, a quantitative polymerase chain reaction assay was used to compare the expression levels of candidate mRNAs. Patients with renal biopsy-confirmed DN were then followed up for a median time of 21 months. End-stage renal disease (ESRD) was defined as the primary endpoint. Multivariate Cox proportional hazards regression was developed to evaluate the prognostic values of candidate mRNAs. RESULTS: Bioinformatics analysis revealed four chemokines (CCL5, CXCL1, CXLC6 and CXCL12) as candidate mRNAs negatively correlated with eGFR, of which CCL5 and CXCL1 mRNA levels were upregulated in the urinary sediment of patients with DN. In addition, urinary sediment mRNA of CXCL1 was negatively correlated with eGFR (r = -0.2275, P = 0.0301) and CCL5 level was negatively correlated with eGFR (r = -0.4388, P < 0.0001) and positively correlated with urinary albumin:creatinine ratio (r = 0.2693, P = 0.0098); also, CCL5 and CXCL1 were upregulated in patients with severe renal interstitial fibrosis. Urinary sediment CCL5 mRNA was an independent predictor of ESRD [hazard ratio 1.350 (95% confidence interval 1.045-1.745)]. CONCLUSIONS: Urinary sediment CCL5 and CXCL1 mRNAs were upregulated in DN patients and associated with a decline in renal function and degree of renal interstitial fibrosis. Urinary sediment CCL5 mRNA could be used as a potential prognostic biomarker of DN.

Dynamics and Sensitivity of Signaling Pathways.

Purpose of Review: Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics. Recent Findings: We summarize the current state of understanding the sensitivity of phosphorylation cycles with and without sequestration. We also describe some basic properties of regulatory motifs including feedback and feedforward regulation. Summary: Although much recent work has focused on understanding the dynamics and particularly the sensitivity of signaling networks in eukaryotic systems, there is still an urgent need to build more scalable models of signaling networks that can appropriately represent their complexity across different cell types and tumors.