Long noncoding RNAs in human reproductive processes and diseases.

Infertility has become a global disease burden. Although assisted reproductive technologies are widely used, the assisted reproduction birth rate is no more than 30% worldwide. Therefore, understanding the mechanisms of reproduction can provide new strategies to improve live birth rates and clinical outcomes of enhanced implantation. Long noncoding RNAs (lncRNAs) have been reported to exert regulatory roles in various biological processes and diseases in many species. In this review, we especially focus on the role of lncRNAs in human reproduction. We summarize the function and mechanisms of lncRNAs in processes vital to reproduction, such as spermatogenesis and maturation, sperm motility and morphology, follicle development and maturation, embryo development and implantation. Then, we highlight the importance and diverse potential of lncRNAs as good diagnostic molecular biomarkers and therapeutic targets for infertility treatment.

Influence of an indigenous yeast, CECA, from the Ningxia wine region of China, on the fungal and bacterial dynamics and function during Cabernet Sauvignon wine fermentation.

BACKGROUND: Saccharomyces cerevisiae CECA was a potential indigenous Chinese wine yeast that can produce aroma and flavor in Cabernet Sauvignon wines. High-throughput sequencing combined with metabolite analysis was applied to analyze the effects of CECA inoculation on the native microbial community interaction and metabolism during Cabernet Sauvignon wine fermentation. RESULTS: Fermentations were performed with three different inoculant strategies: spontaneous fermentation without inoculation, inoculation with CECA after grape must sterilization, and direct inoculation of CECA. Results showed that the diversity of bacteria (P = 0.033) is more sensitive to CECA inoculation than fungi (P = 0.563). In addition, CECA inoculation altered the species composition of core microorganisms (relative abundance >1%) and the keystone species (accounting for the top 1% of the most important interactions), as well as of the biomarkers (linear discriminant analysis > 3.0, P < 0.05). Furthermore, the inoculation could change the cluster of metabolites, and these differential metabolite sets were correlated with four fungal taxa of Issatchenkia, Issatchenkia orientalis, Saccharomycetales, Saccharomycetes and two bacterial taxa of Pantoea, Tatumella ptyseos, were significantly correlated. Inoculated fermentation also altered the correlation between dominant microorganisms and aroma compounds, giving Cabernet Sauvignon wines more herbal, floral, fruity, and cheesy aromas. CONCLUSION: Saccharomyces cerevisiae CECA and dimethyl dicarbonate (DMDC) inhibition treatments significantly altered the microbial community structure of Cabernet Sauvignon wines, which in turn affected the microbial-metabolite correlation. These findings will help winemakers to control the microbial dynamics and functions during wine fermentation, and be more widely used in regional typical wine fermentations. © 2024 Society of Chemical Industry.

Metabolomics Identifies a Panel of Diagnostic Biomarkers for Early Human Embryonic Development Arrest.

Early embryonic development arrest (EEDA) is a unique form of early spontaneous abortion in pregnant women, which is previously suggested to be associated with metabolic abnormalities. Noninvasive biomarkers would significantly improve its diagnosis and clinical outcome. Here, we performed a targeted metabolomics study in plasma from EEDA patients (n = 27) and normal pregnant women (NPW, n = 27) using liquid chromatography coupled with mass spectrometry (LC-MS) to identify potential diagnostic marker metabolites. Our results showed significantly different plasma metabolic profiles between EEDA patients and NPW. Particularly, EEDA patients showed significant alterations in amino acid, carbohydrate, and vitamin metabolism, which were characterized by 21 significantly increased metabolites and five decreased metabolites in plasma. Further receiver operating characteristic analysis showed that an optimal combination of S-methyl-5'-thioadenosine, kynurenine, leucine, and malate could be used as a panel of metabolites for EEDA diagnosis. The area under the curve of the metabolite panel was 0.941, suggesting a better performance than any single metabolite for the diagnosis of EEDA. In summary, our study identifies a panel of differential metabolites in plasma that could act as potential biomarkers for the diagnosis of EEDA in clinical settings.

Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia.

Acute myocardial ischemia (AMI) remains the leading cause of death worldwide, and the post-mortem diagnosis of AMI represents a current challenge for both clinical and forensic pathologists. In the present study, the untargeted metabolomics based on ultra-performance liquid chromatography combined with high-resolution mass spectrometry was applied to analyze serum metabolic signatures from AMI in a rat model (n = 10 per group). A total of 28 endogenous metabolites in serum were significantly altered in AMI group relative to control and sham groups. A set of machine learning algorithms, namely gradient tree boosting (GTB), support vector machine (SVM), random forest (RF), logistic regression (LR), and multilayer perceptron (MLP) models, was used to screen the more valuable metabolites from 28 metabolites to optimize the biomarker panel. The results showed that classification accuracy and performance of MLP model were better than other algorithms when the metabolites consisting of L-threonic acid, N-acetyl-L-cysteine, CMPF, glycocholic acid, L-tyrosine, cholic acid, and glycoursodeoxycholic acid. Finally, 17 blood samples from autopsy cases were applied to validate the classification model's value in human samples. The MLP model constructed based on rat dataset achieved accuracy of 88.23%, and ROC of 0.89 for predicting AMI type II in autopsy cases of sudden cardiac death. The results demonstrated that MLP model based on 7 molecular biomarkers had a good diagnostic performance for both AMI rats and autopsy-based blood samples. Thus, the combination of metabolomics and machine learning algorithms provides a novel strategy for AMI diagnosis.

Quantitative Detection of 15 Serum Bile Acid Metabolic Products by LC/MS/MS in the Diagnosis of Primary Biliary Cholangitis.

To determine 15 bile acid metabolic products in human serum by liquid chromatography-tandem mass spectrometry (LC/MS/MS) and value their diagnostic outcome in primary biliary cholangitis (PBC). Serum from 20 healthy controls and 26 patients with PBC were collected and went LC/MS/MS analysis of 15 bile acid metabolic products. The test results were analyzed by bile acid metabolomics, and the potential biomarkers were screened and their diagnostic performance was judged by statistical methods such as principal component and partial least squares discriminant analysis and area under curve (AUC). 8 differential metabolites can be screened out: Deoxycholic acid (DCA), Glycine deoxycholic acid (GDCA), Lithocholic acid (LCA), Glycine ursodeoxycholic acid (GUDCA), Taurolithocholic acid (TLCA), Tauroursodeoxycholic acid (TUDCA), Taurodeoxycholic acid (TDCA), Glycine chenodeoxycholic acid (GCDCA). The performance of the biomarkers was evaluated by the AUC, specificity and sensitivity. In conclusion, DCA, GDCA, LCA, GUDCA, TLCA, TUDCA, TDCA and GCDCA were identified as eight potential biomarkers to distinguish between healthy people and PBC patients by multivariate statistical analysis, which provided reliable experimental basis for clinical practice.

Transcriptome of pituitary function changes in rat model of high altitude cerebral edema.

High altitude cerebral edema (HACE) is a serious subtype of acute mountain sickness (AMS). Studies have suggested that increased expression of corticotropin releasing hormone receptor 1 (CRFR1) in pituitary is related to the development of HACE, but no study has revealed the molecular landscape of pituitary function changes in this process. Rat model of HACE was established by simulating the high-altitude hypobaric hypoxia environment. Then RNA-sequencing was performed of rat pituitary gland (PG) in HACE and non-HACE groups. The function annotations, enrichment analysis, protein-protein interaction (PPI) network, chromosome location and drug repositioning of differentially expressed genes (DEGs) were explored based on the transcriptomic data. And we found pituitary secretion function was disordered in HACE, which was partly due to activated inflammation and oxidative stress. In addition, we identified potential biomarkers for early recognition of pituitary dysfunction and potential protective drugs for pituitary function in HACE.

Potential Early Markers for Breast Cancer: A Proteomic Approach Comparing Saliva and Serum Samples in a Pilot Study.

Breast cancer is the second leading cause of death for women in the United States, and early detection could offer patients the opportunity to receive early intervention. The current methods of diagnosis rely on mammograms and have relatively high rates of false positivity, causing anxiety in patients. We sought to identify protein markers in saliva and serum for early detection of breast cancer. A rigorous analysis was performed for individual saliva and serum samples from women without breast disease, and women diagnosed with benign or malignant breast disease, using isobaric tags for relative and absolute quantitation (iTRAQ) technique, and employing a random effects model. A total of 591 and 371 proteins were identified in saliva and serum samples from the same individuals, respectively. The differentially expressed proteins were mainly involved in exocytosis, secretion, immune response, neutrophil-mediated immunity and cytokine-mediated signaling pathway. Using a network biology approach, significantly expressed proteins in both biological fluids were evaluated for protein-protein interaction networks and further analyzed for these being potential biomarkers in breast cancer diagnosis and prognosis. Our systems approach illustrates a feasible platform for investigating the responsive proteomic profile in benign and malignant breast disease using saliva and serum from the same women.

Mass spectrometry-based metabolic profiling for identification of biomarkers related to footpad dermatitis in ducks.

1. A new assessment method for duck footpad dermatitis (FPD) evaluation was developed, combining visual and histological characters using the images and sections of 400 ducks' feet at 340 d of age. All ducks were graded as G0 (healthy), G1 (mild), G2 (moderate) and G3 (severe) according to the degree of FPD.2. To reveal the potential biomarkers in serum related to duck FPD, non-targeted metabolomics and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to explore differential metabolites in each group.3. There were 57, 91 and 210 annotated differential metabolites in groups G1, G2 and G3 compared with G0, which meant that the severity of FPD increased in line with the number of metabolites. Four metabolites, L-phenylalanine, L-arginine, L-leucine and L-lysine, were considered potential biomarkers related to FPD.4. KEGG enrichment analysis showed that the FPD was mainly involved in glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway and amino acid metabolism. These are related to production metabolism and can affect the physiological activities of ducks, which might explain the decrease in production performance.

[Linderae Radix water extract treats diarrhea-predominant irritable bowel syndrome in rats: a serum metabolomics study].

This study aims to investigate the mechanism of Linderae Radix water extract(LRWE) in the prevention and treatment of diarrhea-predominant irritable bowel syndrome(IBS-D) based on serum metabolomics. Eighteen 2-week-old male SD rats were randomized into control, IBS-D model, and LRWE groups. The rats in other groups except the control group received gavage of senna concentrate combined with restraint stress for the modeling of IBS-D. The rats in the LRWE group were administrated with LRWE(5.4 g·kg~(-1)) by gavage, and those in the control and IBS-D model groups with an equal volume of distilled water for a total of 14 days. The visceral sensitivity was evaluated by the abdominal withdrawal reflex(AWR) score, and the degree of diarrhea was assessed by the fecal water content(FWC). The morphological changes of the colon and the morphology and number of goblet cells were observed by hematoxylin-eosin(HE) and periodic acid-schiff(PAS) staining, respectively. Ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS) was used for the screening of the potential biomarkers in the rat serum and their related metabolic pathways. The results showed that LRWE reduced the AWR score, decreased FWC, and alleviated visceral sensitivity and diarrhea symptoms in IBS-D rats. HE and PAS staining showed that LRWE mitigated low-grade intestinal inflammation and increased the number of mature secretory goblet cells in the colonic epithelium of IBS-D rats. A total of 25 potential biomarkers of LRWE in treating IBS-D were screened out in this study, which were mainly involved in riboflavin, tryptophan, glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, and cysteine and methionine metabolism. The regulatory effects were the most significant on the riboflavin and tryptophan metabolism pathways. LRWE may alleviate the visceral hypersensitivity by promoting energy metabolism and amino acid metabolism, enhancing intestinal barrier function, and improving intestinal immune function in IBS-D rats.

Microarray analysis of potential biomarkers of brachial plexus avulsion caused neuropathic pain in male rat.

The present study aimed to investigate the expression of mRNA in the brachial plexus avulsion neuropathic pain model and analyze biological functions. Microarray mRNA assay and reverse transcriptase quantitative polymerase chain reaction (RT-PCR) were conducted. The whole blood was collected from two groups for Microarray mRNA analysis. The predicted mRNA targets were studied by gene ontology analysis and pathway analysis. We identified 3 targeted mRNAs, including PIK3CB, HRAS, and JUN. The results showed that PIK3CB, HRAS, and JUN gene expression was increased in the control group but decreased in the neuropathic pain group. These findings indicate that certain genes may be important biomarkers for the potential targets for the prevention and treatment of brachial plexus avulsion caused neuropathic pain.

An investigation of the antidepressant-like effect of Jiaotaiwan in rats by nontargeted metabolomics based on ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry.

Depression is a mental disorder characterized by persistent unhappiness, lack of interest, with cognitive and sleep disorders. Jiaotaiwan is a traditional Chinese medicine for the treatment of insomnia and depressive-like symptoms. In this study, the major chemical components in Jiaotaiwan were qualitatively analyzed using ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry, and a model of depression in rats was subsequently established with chronic unpredictable mild stress followed by Jiaotaiwan intervention. Next, the metabolic profile of rat serum samples was analyzed using nontargeted metabolomics, wherein changes in the metabolites in serum samples before and after Jiaotaiwan administration were measured by multiple statistical approaches. Principal component analysis and partial least squares discriminant analysis indicated that the Jiaotaiwan treatment improved the metabolic phenotype depression. Moreover, the heatmap analysis identified the most important ten biomarkers involved in depression. According to the pathway analysis, the therapeutic effect of Jiaotaiwan on depression may involve the regulation of amino acid metabolism, glycerophospholipid metabolism, and energy metabolism. These findings help us understand the pathogenesis of depression in-depth, and discover targets for clinical diagnosis and treatment. And it also lays a foundation for the use of Jiaotaiwan as an antidepressant agent.

Non-coding RNAs in aortic dissection: From biomarkers to therapeutic targets.

Aortic dissection (AD) is the rupture of the aortic intima, causing the blood in the cavity to enter the middle of the arterial wall. Without urgent and proper treatment, the mortality rate increases to 50% within 48 hours. Most patients present with acute onset of symptoms, including sudden severe pain and complex and variable clinical manifestations, which can be easily misdiagnosed. Despite this, the molecular mechanisms underlying AD are still unknown. Recently, non-coding RNAs have emerged as novel regulators of gene expression. Previous studies have proven that ncRNAs can regulate several cardiovascular diseases; therefore, their potential as clinical biomarkers and novel therapeutic targets for AD has aroused widespread interest. To date, several studies have reported that microRNAs are crucially involved in AD progression. Additionally, several long non-coding RNAs and circular RNAs have been found to be differentially expressed in AD samples, suggesting their potential roles in vascular physiology and disease. In this review, we discuss the functions of ncRNAs in AD pathophysiology and highlight their potential as biomarkers and therapeutic targets for AD. Meanwhile, we present the animal models previously used for AD research, as well as the specific methods for constructing mouse or rat AD models.

Proteomic analysis of bovine mammary epithelial cells after in vitro incubation with S. agalactiae: potential biomarkers.

Streptococcus agalactiae is one of the causative agents of subclinical mastitis, a common disease of dairy cows that causes great economic losses in the industry worldwide. It is thought that pathology is mainly due to inflammatory damage of bovine mammary epithelial cells (bMECs); however, the mechanism by which S. agalactiae damages the bMECs is not clear. The aim of this study was to evaluate the inflammatory effects of S. agalactiae on bMECs and the resulting changes in protein profiles. The bMECs were incubated with S. agalactiae for different times and assayed for cell viability by MTT assay, apoptosis by annexin V and propidium iodide dual staining, and morphological and ultrastructural changes by scanning and transmission electron microscopy. Quantitative real-time PCR was used to determine the effect of S. agalactiae on expression of mRNA of inflammatory factors in bMECs and protein levels were quantitated by liquid chromatography/mass spectrometry. Exposure to S. agalactiae significantly decreased the cell viability and triggered apoptosis, as well as up-regulating TNF-α, IL-1ß and IL-6 mRNA, and inhibiting IL-8 expression. S. agalactiae also induced morphological and ultrastructural changes. Furthermore, we identified 325 up-regulated and 704 down-regulated proteins in the treated vs control group. All significant differentially expressed proteins (DSEPs) were classified into three major areas by function: biological processes, cellular components and molecular functions. These differentially expressed proteins included enzymes and proteins associated with various metabolic processes and cellular immunity. Pathway enrichment analysis showed that eight down-regulated signaling pathways were significantly enriched. Exposure to even subclinical levels of S. agalactiae can lead to inflammation and bMEC damage. Our data suggest some possible molecular mechanisms for the harmful effects of subclinical mastitis in dairy cows.

Serum metabolomics study of patients with allergic rhinitis.

Allergic rhinitis (AR) negatively affects the healthy lives of many individuals. Most previous studies on AR focused on the expression of cytokines, with only a few analyzing cytokine expression from a metabolomics viewpoint. Therefore, it is worthwhile to study AR at the metabolic level. Consequently, we aimed to identify differential serum biomarkers by metabolomics. In this study, the orthogonal partial least squares discriminant analysis (OPLS-DA) model was applied to characterize the differences in serum samples collected from patients with AR and healthy volunteers. Ten metabolites (except hexadecanoic acid) were found to be altered significantly (p < .05) in the former group, according to results of principal component analysis and OPLS-DA, indicating that these metabolites could be potential biomarkers. MetaboAnalyst 4.0 and pathway enrichment analysis showed that these changes in metabolites mainly involved three pathways, namely, porphyrin and chlorophyll metabolism, arachidonic acid metabolism, and purine metabolism. Our findings may contribute to a better understanding of the potential pathogenesis mechanisms and provide a metabolic evidence for in-depth studies of AR.

Systematic analysis of multigene predictors in gastric cancer exploiting gene expression signature.

Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. In this study, we investigated the top 10% overexpressed genes in GC from five data sets of the Oncomine platform, with 265 GC samples versus 174 normal gastric mucosa samples. Sixteen candidate genes were identified as predictors of GC, of which 14 genes were verified through the comparison of expression levels in specimens from normal (chronic gastritis, 21 samples) and GC groups (38 samples). In addition, unique molecular portraits of diffuse adenocarcinoma (DA), intestinal adenocarcinoma (IA), and mixed adenocarcinoma (MA) were studied through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, where DA showed higher extracellular matrix alteration while IA and MA showed higher cell-cycle alteration than other types. We also found that the elevated expressions of genes during GC progression were independent of gene mutations, and high core-binding factor subunit ß expression is correlated with a high overall survival rate in GC patients. Our research may provide an efficient clinical diagnosis of GC at an early stage with high accuracy and thus help improve the overall survival rate through early therapeutic interventions.

LC-MS Analysis of Serum for the Metabolomic Investigation of the Effects of Pulchinenoside b4 Administration in Monosodium Urate Crystal-Induced Gouty Arthritis Rat Model.

Gouty arthritis (GA) is commonly caused by deposition of monosodium urate (MSU) crystals within the joint capsule, bursa, cartilage, bone, or other periarticular tissues after chronic hyperuricemia. Clinically, GA is characterized by acute episodes of joint inflammation, which is most frequently encountered in the major joints, and also has a significant impact on quality of life. Pulchinenoside b4(P-b4) has a wide range of biological activities, including antitumor, anti-inflammatory, antiviral and immunomodulatory activities. Currently, the anti-GA activity and metabolomic profiles after being treated by P-b4 have not been reported. In this paper, for the first time, we have performed a non-targeted metabolomics analysis of serum obtained from an MSU crystal-induced GA rat model intervened by P-b4, using ultra-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. In this study, the main pharmacodynamics of different dosing methods and dosages of P-b4 was firstly investigated. Results have shown that P-b4 possesses high anti-inflammatory activity. These results demonstrated changes in serum metabolites with 32 potential biomarkers. Arachidonic acid, sphingolipid, and glycerophospholipid metabolism are considered to be the most relevant metabolic pathway with P-b4 treatment effect in this study. Moreover, the changes of metabolites and the self-extinction of model effects within 24 h reveals important information for GA diagnostic criteria: The regression of clinical symptoms or the decline of some biochemical indicators cannot be regarded as the end point of GA treatment. Furthermore, our research group plans to conduct further metabolomics research on the clinical course of GA.

[Lipid metabolism study of sodium norcantharidate in LO2 hepatocytes based on lipidomics].

In order to find the endogenous potential biomarkers of in vitro hepatic injury caused by NCTD-Na and elucidate the mechanism of hepatic injury of NCTD-Na,ultra-high performance liquid chromatography coupled quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS) was used for lipidomics detection.Multivariate statistical analysis was used to study the endogenous lipid metabolic changes of human normal liver cells LO2 injury after the treatment with sodium norcantharidate(NCTD-Na).The results showed that the half maximal inhibitory concentration(IC50) of NCTD-Na was 0.034 mmol·L-1.A total of 280 differential metabolites were found between the control group and the low-dose group,with VIP > 2.0 and P<0.05.At the same time,a total of 273 differential metabolites were found between the control group and the high-dose group,with VIP > 2.0 and P<0.05.Cell metabolite profiles showed clear separation among control group,the low-dose group and the high-dose group,and 111 differential metabolites were found,with VIP > 2.0,P<0.05,RSD<30% and in a dose-dependent manner.It was found that most of the above differential metabolites were lipid metabolites after the analysis of simple preparnation methods and database search.A total of 32 potential biomarkers were identified,including 3 phosphatidylcholine(PC),5 lysophosphatidylcholine(Lyso PC),3 ceramide(Cer),1 sphingomyelin(SM),1 phosphatidylethanolamine(PE),10 lysophosphatidylethanolamine(LysoPE),4 diacylglycerol(DG),1 Phosphatidic acid(PA),1 lysophosphatidic acid(Lyso PA),1 phosphatidyl glycerol(PG),1 fatty acid hydroxy fatty acid(FAHFA) and 1 phosphatidylserine(PS).The changes of PCs,Cers,SM,PE and DGs were closely related liver protection,DNA methylation and self-repair in hepatocytes,apoptosis,methylation and detoxification of carcinogens,as well as lipid peroxides production process.Also,they had impact on the proliferation of hepatocytes,differentiation and gene transcription disorders.Cells stimulated by NCTD-Na could promote the production of PA as well as the synthesis and catabolism of FAHFA in a variety of ways.The levels of Lyso PCs,LysoPEs and Lyso PA were correlated with PCs,PE and PA;PE and PS might have valgus during apoptosis,triggering phagocytosis.

Anti-inflammatory activities and glycerophospholipids metabolism in KLA-stimulated RAW 264.7 macrophage cells by diarylheptanoids from the rhizomes of Alpinia officinarum.

Alpinia officinarum is used for its anti-inflammatory activity historically in China. Diarylheptanoids isolated from A. officinarum play important biological roles in the prevention and treatment of inflammatory disorders. Seven diarylheptanoids (1-7) were isolated from A. officinarum. The cell viabilities and anti-inflammatory activities of diarylheptanoids were evaluated by MTT assay and tumor necrosis factor-α production in Kdo2-lipid A-stimulated RAW 264.7 cells in vitro. The relationships between their anti-inflammatories and structure-activities are discussed. The results indicated that compounds 1 and 3-7 had significant anti-inflammatory activities. The relationships between inflammation and phospholipids metabolism were elucidated by multivariate data analysis. Twenty-two potential biomarkers were identified in inflammatory group vs. blank group, and 11 potential biomarkers were identified for inflammatory group vs. drug-treatment groups. Ten common phospholipids were characterized. On the basis of a previous study in our laboratory, we found that phosphatidylethanolamine (18:0/18:1) might be the important glycerophospholipid biomarker in inflammation. In this study, we firstly combined anti-inflammatory activities and glycerophospholipids changes of traditional Chinese medicine. This work suggests that the anti-inflammatory activities of diarylheptanoids might be significantly related to glycerophospholipids and could provide a useful database for investigating the anti-inflammatory effects of traditional Chinese medicine.

A critical overview of long non-coding RNA in glioma etiology 2016: an update.

With the development of whole genome and transcriptome sequencing technologies, a growing body of long non-coding RNAs (lncRNAs) has been identified and is receiving increasing attention. LncRNAs are non-protein encoding transcripts whose functions are crucial for advancing our comprehensive understanding of biological processes in human health and diseases, specifically glioma. It has been established that lncRNAs are differently expressed in the central nervous system and may play a vital role in glioma. As of June 2016, 20 lncRNAs have been identified that may play a role in glioma pathogenesis. Investigation into the role of lncRNAs in glioma may help to identify potential biomarkers which can improve the diagnosis and treatment of glioma. In this paper, we review current understanding of the function of lncRNAs in glioma initiation and progression.

Serum protein S100A9, SOD3, and MMP9 as new diagnostic biomarkers for pulmonary tuberculosis by iTRAQ-coupled two-dimensional LC-MS/MS.

This study aimed to discover the novel noninvasive biomarkers for the diagnosis of pulmonary tuberculosis (TB). We applied iTRAQ 2D LC-MS/MS technique to investigate protein profiles in patients with pulmonary TB and other lung diseases. A total of 34 differentially expressed proteins (24 upregulated proteins and ten downregulated proteins) were identified in the serum of pulmonary TB patients. Significant differences in protein S100-A9 (S100A9), extracellular superoxide dismutase [Cu-Zn] (SOD3), and matrix metalloproteinase 9 (MMP9) were found between pulmonary TB and other lung diseases by ELISA. Correlations analysis revealed that the serum concentration of MMP9 in the pulmonary TB was in moderate correlation with SOD3 (r = 0.581) and S100A9 (r = 0.471), while SOD3 was in weak correlation with S100A9 (r = 0.287). The combination of serum S100A9, SOD3, and MMP9 levels could achieve 92.5% sensitivity and 95% specificity to discriminate between pulmonary TB and healthy controls, 90% sensitivity and 87.5% specificity to discriminate between pulmonary TB and pneumonia, and 85% sensitivity and 92.5% specificity to discriminate between pulmonary TB and lung cancer, respectively. The results showed that S100A9, SOD3, and MMP9 may be potential diagnostic biomarkers for pulmonary TB, and provided experimental basis for the diagnosis of pulmonary TB.