Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders.

Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (ß = -4.36, P < 0.001) and neuropsychological function (ß = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (ß = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.

Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3.

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Unveiling the potential of machine learning in schizophrenia diagnosis: A meta-analytic study of task-based neuroimaging data.

The emergence of machine learning (ML) techniques has opened up new avenues for identifying biomarkers associated with schizophrenia (SCZ) using task-related fMRI (t-fMRI) designs. To evaluate the effectiveness of this approach, we conducted a comprehensive meta-analysis of 31 t-fMRI studies using a bivariate model. Our findings revealed a high overall sensitivity of 0.83 and specificity of 0.82 for t-fMRI studies. Notably, neuropsychological domains modulated the classification performance, with selective attention demonstrating a significantly higher specificity than working memory (ß = 0.98, z = 2.11, P = 0.04). Studies involving older, chronic patients with SCZ reported higher sensitivity (P <0.015) and specificity (P <0.001) than those involving younger, first-episode patients or high-risk individuals for psychosis. Additionally, we found that the severity of negative symptoms was positively associated with the specificity of the classification model (ß = 7.19, z = 2.20, P = 0.03). Taken together, these results support the potential of using task-based fMRI data in combination with machine learning techniques to identify biomarkers related to symptom outcomes in SCZ, providing a promising avenue for improving diagnostic accuracy and treatment efficacy. Future attempts to deploy ML classification should consider the factors of algorithm choice, data quality and quantity, as well as issues related to generalization.

Novel methods in glycomics: a 2019 update.

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

Straightforward and Highly Efficient Strategy for Hepatocellular Carcinoma Glycoprotein Biomarker Discovery Using a Nonglycopeptide-Based Mass Spectrometry Pipeline.

Efficient detection of aberrant glycoproteins in serum is particularly important for biomarker discovery. However, direct quantitation of glycoproteins in serum remains technically challenging because of the extraordinary complexity of the serum proteome. In the current work, we proposed a straightforward and highly efficient strategy by using the nonglycopeptides releasing from the specifically enriched glycoproteins for targeted glycoprotein quantification. With this so-called nonglycopeptide-based mass spectrometry (NGP-MS) strategy, a powerful and nondiscriminatory pipeline for hepatocellular carcinoma (HCC) glycoprotein biomarker discovery, verification, and validation has been developed. First, a data set of 234 NGPs was strictly established for multiple-reaction monitoring (MRM) quantification in serum. Second, the NGPs enriched from 20 HCC serum mixtures and 20 normal serum mixtures were labeled with mTRAQ reagents (Δ0 and Δ8, respectively) to find the differentially expressed glycoproteins in HCC. A total of 97 glycoprotein candidates were preliminarily screened and submitted for absolute quantitation with NGP-based stable-isotope-labeled (SID)-MRM in the individual samples of 38 HCC serum and 24 normal controls. Finally, 21 glycoproteins were absolutely quantified with high quality. The diagnostic sensitivity results showed that three glycoproteins, ß-2-glycoprotein 1 (APOH), α-1-acid glycoprotein 2 (ORM2), and complement C3 (C3), could be used for the discrimination between HCC patients and healthy people. A novel glycoprotein biomarker panel [APOH, ORM2, C3, and α-fetoprotein (AFP)] has proven to outperform AFP, the known HCC serum biomarker, alone, in this study. We believe that this strategy and the panel of glycoproteins might hold great clinical value for HCC detection in the future.

A comparative assessment of adipose-derived stem cells from subcutaneous and visceral fat as a potential cell source for knee osteoarthritis treatment.

The intra-articular injection of adipose-derived stem cells (ASCs) is a novel potential therapy for patients with osteoarthritis (OA). However, the efficacy of ASCs from different regions of the body remains unknown. This study investigated whether ASCs from subcutaneous or visceral adipose tissue provide the same improvement of OA. Mouse and human subcutaneous and visceral adipose tissue were excised for ASC isolation. Morphology, proliferation, surface markers and adipocyte differentiation of subcutaneous ASCs (S-ASCs) and visceral ASCs (V-ASCs) were analysed. A surgically induced rat model of OA was established, and 4 weeks after the operation, S-ASCs, V-ASCs or phosphate-buffered saline (PBS, control) were injected into the articular cavity. Histology, immunohistochemistry and gene expression analyses were performed 6 weeks after ASC injection. The ability of ASCs to differentiate into chondrocytes was assessed by in vitro chondrogenesis, and the immunosuppressive activity of ASCs was evaluated by co-culturing with macrophages. The proliferation of V-ASCs was significantly greater than that of S-ASCs, but S-ASCs had the greater adipogenic capacity than V-ASCs. In addition, the infracted cartilage treated with S-ASCs showed significantly greater improvement than cartilage treated with PBS or V-ASCs. Moreover, S-ASCs showed better chondrogenic potential and immunosuppression in vitro. Subcutaneous adipose tissue is an effective cell source for cell therapy of OA as it promotes stem cell differentiation into chondrocytes and inhibits immunological reactions.

ITMSQ: A software tool for N- and C-terminal fragment ion pairs based isobaric tandem mass spectrometry quantification.

Tandem MS (MS2) quantification using the series of N- and C-terminal fragment ion pairs generated from isobaric-labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N- and C-terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solution for N- and C-terminal fragment ion pairs based isobaric MS2 quantitative methods.

Direct-S: a directed mass spectrometry method for biomarker verification in native serum.

Serum has been the logical choice and most-used bio-specimen for monitoring biomarkers. However, direct analysis of low-abundance biomarkers in serum is still a problem. Here, we have established a directed mass spectrometry (inclusion list driven MS) method, Direct-S, for direct quantification of protein biomarkers in native serum samples without high-abundance protein depletion or pre-fractionation. In Direct-S, an (18)O-labeling technique was used to produce internal standards of the targeted peptides, and only targeted peptides were selected for tandem mass spectrometry (MS/MS) fragmentation to increase sensitivity and efficiency. The (16)O/(18)O ion pairs of target peptides and the elution time/fragmental pattern of the internal standards were used to facilitate the identification of the low-abundance peptides. Using Direct-S, three candidate biomarkers, α1-antitrypsin (A1AT), galectin-3 binding protein (LG3BP) and cathepsin D (CTSD), which represent different abundance levels, were quantified in serum samples of colorectal cancer (CRC) patients and healthy candidates. Direct-S exhibited good linearity of response from 20 fmol to 0.5 nmol (r > 0.9845). Reliable quantification across five orders of magnitude and as low as 71 pg µL(-1) was achieved in serum samples. In conclusion, Direct-S is a low cost, convenient and accurate method for verifying serum biomarkers.

Proteome profiling of mitotic clonal expansion during 3T3-L1 adipocyte differentiation using iTRAQ-2DLC-MS/MS.

Mitotic clonal expansion (MCE) is one of the important events taking place at the early stage during 3T3-L1 adipocyte differentiation. To investigate the mechanism underlying this process, we carried out a temporal proteomic analysis to profile the dynamic changes in MCE. Using 8-plex-iTRAQ-2DLC-MS/MS analysis, 3152 proteins were quantified during the initial 28 h of 3T3-L1 adipogenesis. Functional analysis was performed on 595 proteins with maximum or minimum quantities at 20 h of adipogenic induction that were potentially involved in MCE, which identified PI3K/AKT/mTOR as the most relevant pathway. Among the 595 proteins, PKM2 (Pyruvate kinase M2), a patterned protein identified as a potential target gene of C/EBPß in our previous work, was selected for further investigation. Network analysis suggested positive correlations among C/EBPß, PIN1, and PKM2, which may be related with the PI3K-AKT pathway. Knockdown of PKM2 with siRNA inhibited both MCE and adipocyte differentiation of 3T3-L1 cells. Moreover, PKM2 was down-regulated at both the mRNA level and the protein level upon the knockdown of C/EBPß. And overexpressed PKM2 can partially restore MCE, although it did not restore terminal adipocyte differentiation, which was inhibited by siC/EBPß. Thus, PKM2, potentially regulated by C/EBPß, is involved in MCE during adipocyte differentiation. The dynamic proteome changes quantified here provide a promising basis for revealing molecular mechanism regulating adipogenesis.

Reduced expression of the chromatin remodeling gene ARID1A enhances gastric cancer cell migration and invasion via downregulation of E-cadherin transcription.

The chromatin remodeling gene AT-rich interactive domain-containing protein 1A (ARID1A) encodes the protein BAF250a, a subunit of human SWI/SNF-related complexes. Recent studies have identified ARID1A as a tumor suppressor. Here, we show that ARID1A expression is reduced in gastric cancer (GC) tissues, which are significantly associated with local lymph node metastasis, tumor infiltration and poor patient prognosis. ARID1A silencing enforces the migration and invasion of GC cells, whereas ectopic expression of ARID1A inhibits migration. The adhesive protein E-cadherin is remarkably downregulated in response to ARID1A silencing, but it is upregulated by ARID1A overexpression. E-cadherin overexpression significantly inhibits GC cell migration and invasion, whereas CDH1 (coded E-cadherin) silencing promotes migration. Restored expression of CDH1 in ARID1A-silenced cell lines restores the inhibition of cell migration. Luciferase reporter assays and chromatin immunoprecipitation indicate that the ARID1A-associated SWI/SNF complex binds to the CDH1 promoter and modulates CDH1 transcription. ARID1A knockdown induces evident morphological changes of GC cells with increased expression of mesenchymal markers, indicating an epithelial-mesenchymal transition. ARID1A silencing does not alter the level of ß-catenin but induces a subcellular redistribution of ß-catenin from the plasma membrane to the cytoplasm and nucleus. Immunohistochemical studies demonstrate that reduced expression of E-cadherin is associated with local lymph node metastasis, tumor infiltration and poor clinical prognosis. ARID1A and E-cadherin expression show a strong correlation in 75.4% of the analyzed GC tissues. They are synergistically downregulated in 23.5% of analyzed GC tissues. In conclusion, ARID1A targets E-cadherin during the modulation of GC cell migration and invasion.

Global in vivo terminal amino acid labeling for exploring differential expressed proteins induced by dialyzed serum cultivation.

Taking advantage of reliable metabolic labeling and accurate isobaric MS2 quantification, we developed a global in vivo terminal amino acid labeling (G-IVTAL) strategy by combining metabolic labeling and isotopic dimethyl labeling for quantifying tryptic peptides. With G-IVTAL, the scale of qualitative and quantitative data can be increased twofold compared with in vivo termini amino acid labeling (IVTAL) in which Lys-N and Arg-C are used for digestion. As a result, up to 81.78% of the identified proteins have been confidently quantified in G-IVTAL-labeled HepG2 cells. Dialyzed serum has been used in most SILAC studies to ensure complete labeling. However, dialysis requires the removal of low molecular weight hormones, cytokines, and cellular growth factors, which are essential for the cell growth of certain cell lines. To address the influence of dialyzed serum in HepG2 growth, the G-IVTAL strategy was applied to quantify the expression differences between dialyzed serum- and normal serum-cultured HepG2 cells. Finally, we discovered 111 differentially expressed proteins, which could be used as references to improve the reliability of the SILAC quantification. Among these, by using western blotting, the differential expressions of MTDH, BCAP31, and GPC3 were confirmed as being influenced by dialyzed serum. The experimental results demonstrate that the G-IVTAL strategy is a powerful tool to achieve accurate and reliable protein quantification.

Hyperplex-MRM: a hybrid multiple reaction monitoring method using mTRAQ/iTRAQ labeling for multiplex absolute quantification of human colorectal cancer biomarker.

Novel biomarker verification assays are urgently required to improve the efficiency of biomarker development. Benefitting from lower development costs, multiple reaction monitoring (MRM) has been used for biomarker verification as an alternative to immunoassay. However, in general MRM analysis, only one sample can be quantified in a single experiment, which restricts its application. Here, a Hyperplex-MRM quantification approach, which combined mTRAQ for absolute quantification and iTRAQ for relative quantification, was developed to increase the throughput of biomarker verification. In this strategy, equal amounts of internal standard peptides were labeled with mTRAQ reagents Δ0 and Δ8, respectively, as double references, while 4-plex iTRAQ reagents were used to label four different samples as an alternative to mTRAQ Δ4. From the MRM trace and MS/MS spectrum, total amounts and relative ratios of target proteins/peptides of four samples could be acquired simultaneously. Accordingly, absolute amounts of target proteins/peptides in four different samples could be achieved in a single run. In addition, double references were used to increase the reliability of the quantification results. Using this approach, three biomarker candidates, ademosylhomocysteinase (AHCY), cathepsin D (CTSD), and lysozyme C (LYZ), were successfully quantified in colorectal cancer (CRC) tissue specimens of different stages with high accuracy, sensitivity, and reproducibility. To summarize, we demonstrated a promising quantification method for high-throughput verification of biomarker candidates.

A miniaturised electron ionisation time-of-flight mass spectrometer that uses a unique helium ion removal pulsing technique specifically for gas analysis.

A miniaturised reflectron time-of-flight mass spectrometer combined with an electron ionisation ion source has been developed for the analysis of gases. An entirely new helium ion removal pulsing technique in this mass spectrometer is used to achieve an improved performance for the first time. The helium carrier gas, which enters into the source along with the gaseous sample, is simultaneously ionised and then orthogonally introduced into the time-of-fight mass analyser. Once the relatively light helium ions in the ion packet become extremely close to the reflectron plate (B-plate for short in this article), a modulated pulse is instantaneously applied on the B-plate and a negative reflectron voltage is set to the B-plate and lasts for a very short period, during which all the helium ions are directly bumped into the B-plate and subsequently removed. The helium ion removal pulsing technique can efficiently avoid saturation of the micro-channel plate caused by too many helium ions. A compact and durable instrument is designed, which has a mass resolving resolution greater than 400 FWHM for online gas analysis. The technology may also be further developed to remove other ions for TOF mass spectrometry.

Involvement of cytoskeleton-associated proteins in the commitment of C3H10T1/2 pluripotent stem cells to adipocyte lineage induced by BMP2/4.

The developmental pathway that gives rise to mature adipocytes involves two distinct stages: commitment and terminal differentiation. Although the important proteins/factors contributing to terminal adipocyte differentiation have been well defined, the proteins/factors in the commitment of mesenchymal stem cells to the adipocyte lineage cells have not. In this study, we applied proteomics analysis profiling to characterize differences between uncommitted C3H10T1/2 pluripotent stem cells and those that have been committed to the adipocyte lineage by BMP4 or BMP2 with the goal to identify such proteins/factors and to understand the molecular mechanisms that govern the earliest stages of adipocyte lineage commitment. Eight proteins were found to be up-regulated by BMP2, and 27 proteins were up-regulated by BMP4, whereas five unique proteins were up-regulated at least 10-fold by both BMP2/4, including three cytoskeleton-associated proteins (i.e. lysyl oxidase (LOX), translationally controlled tumor protein 1 (TPT1), and αB-crystallin). Western blotting further confirmed the induction of the expression of these cytoskeleton-associated proteins in the committed C3H10T1/2 induced by BMP2/4. Importantly, knockdown of LOX expression totally prevented the commitment, whereas knockdown of TPT1 and αB-crystallin expression partially inhibited the commitment. Several published reports suggest that cell shape can influence the differentiation of partially committed precursors of adipocytes, osteoblasts, and chondrocytes. We observed a dramatic change of cell shape during the commitment process, and we showed that knockdown of these cytoskeleton-associated proteins prevented the cell shape change and restored F-actin organization into stress fibers and inhibited the commitment to the adipocyte lineage. Our studies indicate that these differentially expressed cytoskeleton-associate proteins might determine the fate of mesenchymal stem cells to commit to the adipocyte lineage through cell shape regulation.

Nsun2 coupling with RoRγt shapes the fate of Th17 cells and promotes colitis.

T helper 17 (Th17) cells are a subset of CD4+ T helper cells involved in the inflammatory response in autoimmunity. Th17 cells secrete Th17 specific cytokines, such as IL-17A and IL17-F, which are governed by the master transcription factor RoRγt. However, the epigenetic mechanism regulating Th17 cell function is still not fully understood. Here, we reveal that deletion of RNA 5-methylcytosine (m5C) methyltransferase Nsun2 in mouse CD4+ T cells specifically inhibits Th17 cell differentiation and alleviates Th17 cell-induced colitis pathogenesis. Mechanistically, RoRγt can recruit Nsun2 to chromatin regions of their targets, including Il17a and Il17f, leading to the transcription-coupled m5C formation and consequently enhanced mRNA stability. Our study demonstrates a m5C mediated cell intrinsic function in Th17 cells and suggests Nsun2 as a potential therapeutic target for autoimmune disease.

Comparative proteomic analysis of drug sodium iron chlorophyllin addition to Hep 3B cell line.

The human hepatoma 3B cell line was chosen as an experimental model for in vitro test of drug screening. The drugs included chlorophyllin and its derivatives such as fluo-chlorophyllin, sodium copper chlorophyllin, and sodium iron chlorophyllin. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) method was used in this study to obtain the primary screening results. The results showed that sodium iron chlorophyllin had the best LC(50) value. Proteomic analysis was then performed for further investigation of the effect of sodium iron chlorophyllin addition to the Hep 3B cell line. The proteins identified from a total protein extract of Hep 3B before and after the drug addition were compared by two-dimensional-gel-electrophoresis. Then 32 three-fold differentially expressed proteins were successfully identified by MALDI-TOF-TOF-MS. There are 29 unique proteins among those identified proteins. These proteins include proliferating cell nuclear antigen (PCNA), T-complex protein, heterogeneous nuclear protein, nucleophosmin, heat shock protein A5 (HspA5) and peroxiredoxin. HspA5 is one of the proteins which are involved in protecting cancer cells against stress-induced apoptosis in cultured cells, protecting them against apoptosis through various mechanisms. Peroxiredoxin has anti-oxidant function and is related to cell proliferation, and signal transduction. It can protect the oxidation of other proteins. Peroxiredoxin has a close relationship with cancer and can eventually become a disease biomarker. This might help to develop a novel treatment method for carcinoma cancer.

Proteome-centric cross-omics characterization and integrated network analyses of triple-negative breast cancer.

We report a comprehensive proteomic study of a 90-case cohort of paired samples of triple-negative breast cancer (TNBC) in quantification, phosphorylation, and DNA-binding capacity. Four integrative subtypes (iP-1-4) are stratified on the basis of global proteome and phosphoproteome, each of which exhibits distinct molecular and pathway features. Scaffold and co-expression network analyses of three proteomic datasets, integrated with those from genome and transcriptome of the same cohort, reveal key pathways and master regulators that, characteristic of TNBC subtypes, play important regulatory roles within and between scaffold sub-structures and co-expression communities. We find that NAE1 is a potential drug target for subtype iP-1, and a series of key molecules in fatty acid metabolism, such as AKT1/FASN, are plausible targets for subtype iP-2. Libraries of proteins, pathways and networks of TNBC provide a valuable molecular infrastructure for further clinical exploration and in-depth studies of the molecular mechanisms of the disease.

iTRAQ-2DLC-ESI-MS/MS based identification of a new set of immunohistochemical biomarkers for classification of dysplastic nodules and small hepatocellular carcinoma.

The study aims to develop novel clinical immunohistochemical biomarkers for distinguishing small hepatocellular carcinoma (sHCC) from dysplastic nodules (DN). iTRAQ-2DLC-ESI-MS/MS technique was used to screen immunohistochemical biomarkers between precancerous lesions (liver cirrhosis and DN) and sHCC. A total of 1951 proteins were quantified, including 52 proteins upregulated in sHCC and 95 proteins downregulated in sHCC by at least 1.25- or 0.8-fold at p < 0.05. The selected biomarker candidates were further verified using Western blotting and immunohistochemistry. Furthermore, receiver operation characteristics (ROC) curves and logistic regression model were carried out to evaluate the diagnostic values of the biomarkers. Finally, aminoacylase-1 (ACY1) and sequestosome-1 (SQSTM1) were chosen as novel candidate biomarkers for distinction of sHCC from DN. A constructed logistic regression model included ACY1, SQSTM1, and CD34. The sensitivity and specificity of this model for distinguishing sHCC from DN was 96.1% and 96.7%. In conclusion, ACY1 and SQSTM1 were identified as novel immunohistochemical biomarkers distinguishing sHCC from DN. In conclusion, expression levels of CD34, ACY1, and SQSTM1 can be used to establish an accurate diagnostic model for distinction of sHCC from DN.

In vivo termini amino acid labeling for quantitative proteomics.

Quantitative proteomics is one of the research hotspots in the proteomics field and presently maturing rapidly into an important branch. The two most typical quantitative methods, stable isotope labeling with amino acids in cell culture (SILAC) and isobaric tags for relative and absolute quantification (iTRAQ), have been widely and effectively applied in solving various biological and medical problems. Here, we describe a novel quantitative strategy, termed "IVTAL", for in vivo termini amino acid labeling, which combines some advantages of the two methods above. The core of this strategy is a set of heavy amino acid (13)C(6)-arginine and (13)C(6)-lysine and specific endoproteinase Lys-N and Arg-C that yield some labeled isobaric peptides by cell culture and enzymatic digestion, which are indistinguishable in the MS scan but exhibit multiple MS/MS reporter b, y ion pairs in a full mass range that support quantitation. Relative quantification of cell states can be achieved by calculating the intensity ratio of the corresponding reporter b, y ions in the MS/MS scan. The experimental analysis for various proportions of mixed HeLa cell samples indicated that the novel strategy showed an abundance of reliable quantitative information, a high sensitivity, and a good dynamic range of nearly 2 orders of magnitude. IVTAL, as a highly accurate and reliable quantitative proteomic approach, is expected to be compatible with any cell culture system and to be especially effective for the analysis of multiple post-translational modificational sites in one peptide.

Differential protein expression level identification by knockout of 14-3-3τ with siRNA technique and 2DE followed MALDI-TOF-TOF-MS.

Cytotrophoblast cell differentiation into syncytiotrophoblast cells is a complex and delicate process, and the mechanism needs a large number of further studies. Knockout of 14-3-3τ expression and some further investigations were performed in the syncytiotrophoblast cell formation with RNA interference (RNAi) technology. The study found that the 14-3-3τ expression level with the formation of syncytiotrophoblast cells increased. Hypoxia inhibited the formation of syncytiotrophoblast cells where 14-3-3τ expression level decreased. RNAi reduced 14-3-3τ expression, and reduced the formation of syncytiotrophoblast cells. So that 14-3-3τ is not only involved in the cell regulation, but also in the formation of syncytiotrophoblast cells. 14-3-3τ is an important regulatory factor which inhibits the formation of hypoxia.