Search

Background: Gut microbiota dysbiosis involved in the pathogenesis of colorectal cancer (CRC). The characteristics of enterotypes in CRC development have not been determined. Objective: To characterize the gut microbiota of healthy, adenoma, and CRC subjects based on enterotype. Methods: The 16 S rRNA sequencing data from 315 newly sequenced individuals and three previously published datasets were collected, providing total data for 367 healthy, 320 adenomas, and 415 CRC subjects. Enterotypes were analyzed for all samples, and differences in microbiota composition across subjects with different disease states in each enterotype were determined. The predictive values of a random forest classifier based on enterotype in distinguishing healthy, adenoma, and CRC subjects were evaluated and validated. Results: Subjects were classified into one of three enterotypes, namely, Bacteroide- (BA_E), Blautia- (BL_E), and Streptococcus- (S_E) dominated clusters. The taxonomic profiles of these three enterotypes differed among the healthy, adenoma, and CRC cohorts. BA_E group was enriched with Bacteroides and Blautia; BL_E group was enriched by Blautia and Coprococcus; S_E was enriched by Streptococcus and Ruminococcus. Relative abundances of these genera varying among the three human cohorts. In training and validation sets, the S_E cluster showed better performance in distinguishing among CRC patients, adenoma patients, and healthy controls, as well as between CRC and non-CRC individuals, than the other two clusters. Conclusion: This study provides the first evidence to indicate that changes in the microbial composition of enterotypes are associated with disease status, thereby highlighting the diagnostic potential of enterotypes in the treatment of adenoma and CRC. Highlights: Three enterotypes (BA_E, BL_E, and S_E) were identified in healthy, adenoma, and CRC subjects. BA_E, BL_E, and S_E clusters were dominated by Bacteroide, Blautia, and Streptococcus, respectively. Differences in gut microbial composition were observed within the control, adenoma, CRC populations for each enterotype. S_E showed better performance in distinguishing three human cohorts than BA_E and BL_E. Disease prediction performance of enterotypes is no better than that of a classification model based on all samples. [ABSTRACT FROM AUTHOR]

Background: Ewing's sarcoma is an extremely aggressive bone sarcoma in teenagers and adolescents. We managed to identify the potential role of ferroptosis-related genes (FRGs) in Ewing's sarcoma and its clinical prognostic value. Results: A total of 59 common differentially expressed FRGs were screened out. GO/KEGG enrichment and PPI network were executed. Based on 16 prognostic-related FRGs identified by univariate Cox regression in GSE17674, 2 molecular clusters were screened out via NMF consensus. Survival rate and immune infiltration were totally different in two clusters. Subsequently, multivariate/step Cox regression was conducted to identify 7 risk signatures (SLC2A1, PCK2, CHAC1, ATG13, PRKAA2, ARNT, and SIRT1). K-M survival (p = 1.785e-06) and ROC curves (with AUC value 0.816, 0877, 0.919 in 1, 3, 5 years) were plotted to assess the good predictive ability of risk model. ICGC dataset with K-M survival (p = 1.558e-02) and AUC value (0.886, 0.750, 0.709 in 1, 3, 5 years) was used to validate the risk model. Risk score and clinical features (gender, age stage status) were incorporated into a nomogram model. Immune microenvironment (IME) ingredients (ESTIMATE score, immune cells, immune-related pathways, and checkpoint genes) between two risk groups were also explored. High-risk group possessed an activated immune status compared to low-risk group. Finally prognostic signatures exhibited perfect diagnostic ability in ES occurrence, and several drugs showed IC50 sensitivity to different risk groups. Conclusions: Our study identified 7 prognostic signatures of FRGs and explored related immune infiltration which provided new aspects for future research in Ewing's sarcoma. [ABSTRACT FROM AUTHOR]

The terrestrial reflection or emission spectrum obtained by the remote sensor is recorded in units of pixels. In most cases, a pixel usually contains many types of terrains. This pixel is a mixed pixel, and each of the terrains in the mixed pixels is called "endmember". Estimating the number of endmembers is a significant step in many hyperspectral data mining techniques, such as target classification and endmember extraction. The paper proposes a separative detection method by the use of a weight-sequence geometry to estimate the number of endmembers. This method projects the spectral matrix into the orthogonal subspace by eigenvalue decomposition at first. Then, on the basis of the normalized eigenvalue sequence, the separative detection method innovatively uses a geometric criterion to find the separation point between the main factors and minor factors. Finally, the number of endmembers is determined by the sequence of the "separation point". Validation through a series of simulated and real hyperspectral data, it indicates that the proposed method can accurately and rapidly detect the number of endmembers in the hyperspectral data without any prior information. In addition, the new method is also applicable to the ultra-high resolution remote spectral data in the future. [ABSTRACT FROM AUTHOR]

Combining Fourier transform infrared spectroscopy (FTIR) with endoscopy, it is expected that noninvasive, rapid detection of colorectal cancer can be performed in vivo in the future. In this study, Fourier transform infrared spectra were collected from 88 endoscopic biopsy colorectal tissue samples (41 colitis and 47 cancers). A new method, viz., entropy weight local-hyperplane k-nearest-neighbor (EWHK), which is an improved version of K-local hyperplane distance nearest-neighbor (HKNN), is proposed for tissue classification. In order to avoid limiting high dimensions and small values of the nearest neighbor, the new EWHK method calculates feature weights based on information entropy. The average results of the random classification showed that the EWHK classifier for differentiating cancer from colitis samples produced a sensitivity of 81.38% and a specificity of 92.69%. [ABSTRACT FROM AUTHOR]

Objectives: Tophaceous gout seldom affects the axial skeleton. Symptoms vary according to the differential localization of urate deposits and the diagnosis is often delayed. Here, we report an unusual case of lumbar spinal stenosis caused by extradural tophaceous deposits.Methods: We retrospectively reviewed a case of a patient with tophaceous gout of the lumbar spine and reviewed the relevant literature.Results: A 62-year-old man with a 2-year history of lower back pain and a 3-month history of lower limb radiation pain and intermittent claudication was admitted. After laboratory and imaging investigations he underwent surgical decompression and stabilization. Histological analysis of the extracted specimen confirmed that it was gouty tophus. The patient's symptoms improved progressively after the operation. He recovered very well with no complications.Conclusion: The mechanism associated with axial gout is not yet clear. Obesity, inactivity, and previous degenerative disc disease may be the risk factors for spinal tophus. The clinical symptoms are diverse according to the differential localization of urate deposits. It is not easy to diagnose this disease radiographically by routine radiological examination. Analysis of a biopsy specimen is definitely the only way to confirm diagnosis. Surgical treatment should be considered in patients with spinal gout who are experiencing neurological deterioration. [ABSTRACT FROM AUTHOR]

For achieving the development of a portable, low-cost and in vivo cancer diagnosis instrument, a laser 785 nm miniature Raman spectrometer was used to acquire the Raman spectra for breast cancer detection in this paper. However, because of the low spectral signal-to-noise ratio, it is difficult to achieve high discrimination accuracy by using the miniature Raman spectrometer. Therefore, a pattern recognition method of the adaptive net analyte signal (NAS) weight k-local hyperplane (ANWKH) is proposed to increase the classification accuracy. ANWKH is an extension and improvement of K-local hyperplane distance nearest-neighbor (HKNN), and combines the advantages of the adaptive weight k-local hyperplane (AWKH) and the net analyte signal (NAS). In this algorithm, NAS was first used to eliminate the influence caused by other non-target factors. Then, the distance between the test set samples and hyperplane was calculated with consideration of the feature weights. The HKNN only works well for small values of the nearest-neighbor. However, the accuracy decreases with increasing values of the nearest-neighbor. The method presented in this paper can resolve the basic shortcoming by using the feature weights. The original spectra are projected into the vertical subspace without the objective factors. NAS was employed to obtain the spectra without irrelevant information. NAS can improve the classification accuracy, sensitivity, and specificity of breast cancer early diagnosis. Experimental results of Raman spectra detection in vitro of breast tissues showed that the proposed algorithm can obtain high classification accuracy, sensitivity, and specificity. This paper demonstrates that the ANWKH algorithm is feasible for early clinical diagnosis of breast cancer in the future. [ABSTRACT FROM AUTHOR]

Background: A number of meta-analyses have been carried out to evaluate the effects of minimally invasive surgery (MIS) versus open surgery (OS) for acute Achilles tendon rupture. However, discordant findings were seen in these meta-analyses. The present study, performing a systematic review of overlapping meta-analyses regarding MIS versus OS of acute Achilles tendon rupture, aimed to assist decision-makers interpret and choose among conflicting meta-analyses, as well as to offer treatment recommendations based on current best evidence. Methods: The literature search was performed to identify systematic reviews comparing MIS with OS for Achilles tendon rupture. Meta-analyses only comprising randomized controlled trials (RCTs) were included. Two authors individually evaluated the quality of meta-analysis and extracted data. The Jadad decision algorithm was conducted to ascertain which meta-analysis offered the best evidence. Results: A total of four meta-analyses was included. All these meta-analyses comprised RCTs or quasi-RCTs and were determined as Level-II evidence. The scores of the Assessment of Multiple Systematic Reviews (AMSTAR) ranged from 7 to 10 (median 9.5). The Jadad algorithm indicated that the best meta-analysis should be chosen according to the search strategies and application of selection. A high-quality meta-analysis with more RCTs was chosen, which suggested that there was no statistically significant difference between MIS and OS regarding rerupture rate, tissue adhesion, sural nerve injury, deep infection, and deep vein thrombosis. However, MIS could decrease superficial infection rate, and had a better patient satisfaction for good to excellent outcomes in comparison to OS. Conclusions: Based on the best available evidence, MIS may be superior to OS for treating acute Achilles tendon rupture. However, due to some limitations, this should be cautiously interpreted, and further high-quality studies are needed. [ABSTRACT FROM AUTHOR]

Early diagnosis and early medical treatments are the keys to save the patients' lives and improve the living quality. Fourier transform infrared (FT-IR) spectroscopy can distinguish malignant from normal tissues at the molecular level. In this paper, programs were made with pattern recognition method to classify unknown samples. Spectral data were pretreated by using smoothing and standard normal variate (SNV) methods. Leave-one-out cross validation was used to evaluate the discrimination result of support vector machine (SVM) method. A total of 54 gastric tissue samples were employed in this study, including 24 cases of normal tissue samples and 30 cases of cancerous tissue samples. The discrimination results of SVM method showed the sensitivity with 100%, specificity with 83.3%, and total discrimination accuracy with 92.2%. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive control strategy for a class of nonholonomic systems in chained form with virtual control coefficients, nonlinear uncertainties, and unknown time delays. State scaling technique and backstepping recursive approach are applied to design a nonlinear state feedback controller, which can guarantee the stabilization of the closed-loop systems. The simulation results are provided to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

When sample replicates are limited in a label-free proteomics experiment, selecting differentially regulated proteins with an assignment of statistical significance remains difficult for proteins with a single-peptide hit or a small fold-change. This paper aims to address this issue. An important component of the approach employed here is to utilize the rule of Minimum number of Permuted Significant Pairings (MPSP) to reduce false positives. The MPSP rule generates permuted sample pairings from limited analytical replicates and simply requires that a differentially regulated protein can be selected only when it is found significant in designated number of permuted sample pairings. Both a power law global error model with a signal-to-noise ratio statistic (PLGEM-STN) and a constant fold-change threshold were initially used to select differentially regulated proteins. But both methods were found not stringent enough to control the false discovery rate to 5% in this study. On the other hand, the combination of the MPSP rule with either of these two methods significantly reduces false positives with little effect on the sensitivity to select differentially regulated proteins including those with a single-peptide hit or with a <2-fold change. [ABSTRACT FROM AUTHOR]

Understanding the biology of Mycobacterium tuberculosis is one of the primary challenges in current tuberculosis research. Investigation of mycobacterial biology using the systems biology approach has deciphered much information with regard to the bacilli and tuberculosis pathogenesis. The modulation of its environment and the ability to enter a dormant phase are the hallmarks of M. tuberculosis. Until now, proteome studies have been able to understand much about the role of various proteins, mostly in growing M. tuberculosis cells. It has been difficult to study dormant M. tuberculosis by conventional proteomic techniques with very few proteins being found to be differentially expressed. Discrepancy between proteome and transcriptome studies lead to the conclusion that a certain aspect of the mycobacterial proteome is not being explored. Analysis of protein turnover may be the answer to this dilemma. This review, while giving a gist of the proteome response of mycobacteria to various stresses, analyzes the data obtained from abundance studies versus data from protein turnover studies in M. tuberculosis. This review brings forth the point that protein turnover analysis is capable of discerning more subtle changes in protein synthesis, degradation, and secretion activities. Thus, turnover studies could be incorporated to provide a more in-depth view into the proteome, especially in dormant or persistent cells. Turnover analysis might prove helpful in drug discovery and a better understanding of the dynamic nature of the proteome of mycobacteria. [ABSTRACT FROM AUTHOR]

Background: Many studies have provided algorithms or methods to assess a statistical significance in quantitative proteomics when multiple replicates for a protein sample and a LC/MS analysis are available. But, confidence is still lacking in using datasets for a biological interpretation without protein sample replicates. Although a fold-change is a conventional threshold that can be used when there are no sample replicates, it does not provide an assessment of statistical significance such as a false discovery rate (FDR) which is an important indicator of the reliability to identify differentially expressed proteins. In this work, we investigate whether differentially expressed proteins can be detected with a statistical significance from a pair of unlabeled protein samples without replicates and with only duplicate LC/MS injections per sample. A FDR is used to gauge the statistical significance of the differentially expressed proteins. Results: We have experimented to operate on several parameters to control a FDR, including a fold-change, a statistical test, and a minimum number of permuted significant pairings. Although none of these parameters alone gives a satisfactory control of a FDR, we find that a combination of these parameters provides a very effective means to control a FDR without compromising the sensitivity. The results suggest that it is possible to perform a significance analysis without protein sample replicates. Only duplicate LC/MS injections per sample are needed. We illustrate that differentially expressed proteins can be detected with a FDR between 0 and 15% at a positive rate of 4-16%. The method is evaluated for its sensitivity and specificity by a ROC analysis, and is further validated with a [15N]-labeled internal-standard protein sample and additional unlabeled protein sample replicates. Conclusion: We demonstrate that a statistical significance can be inferred without protein sample replicates in label-free quantitative proteomics. The approach described in this study would be useful in many exploratory experiments where a sample amount or instrument time is limited. Naturally, this method is also suitable for proteomics experiments where multiple sample replicates are available. It is simple, and is complementary to other more sophisticated algorithms that are not designed for dealing with a small number of sample replicates. [ABSTRACT FROM AUTHOR]

Background: Although fold change is a commonly used criterion in quantitative proteomics for differentiating regulated proteins, it does not provide an estimation of false positive and false negative rates that is often desirable in a large-scale quantitative proteomic analysis. We explore the possibility of applying the Significance Analysis of Microarray (SAM) method (PNAS 98:5116-5121) to a differential proteomics problem of two samples with replicates. The quantitative proteomic analysis was carried out with nanoliquid chromatography/linear iron trap-Fourier transform mass spectrometry. The biological sample model included two Mycobacterium smegmatis unlabeled cell cultures grown at pH 5 and pH 7. The objective was to compare the protein relative abundance between the two unlabeled cell cultures, with an emphasis on significance analysis of protein differential expression using the SAM method. Results using the SAM method are compared with those obtained by fold change and the conventional t-test. Results: We have applied the SAM method to solve the two-sample significance analysis problem in liquid chromatography/mass spectrometry (LC/MS) based quantitative proteomics. We grew the pH5 and pH7 unlabelled cell cultures in triplicate resulting in 6 biological replicates. Each biological replicate was mixed with a common 15N-labeled reference culture cells for normalization prior to SDS/PAGE fractionation and LC/MS analysis. For each biological replicate, one center SDS/PAGE gel fraction was selected for triplicate LC/MS analysis. There were 121 proteins quantified in at least 5 of the 6 biological replicates. Of these 121 proteins, 106 were significant in differential expression by the t-test (p < 0.05) based on peptide-level replicates, 54 were significant in differential expression by SAM with Δ = 0.68 cutoff and false positive rate at 5%, and 29 were significant in differential expression by the t-test (p < 0.05) based on protein-level replicates. The results indicate that SAM appears to overcome the false positives one encounters using the peptide-based t-test while allowing for identification of a greater number of differentially expressed proteins than the protein-based t-test. Conclusion: We demonstrate that the SAM method can be adapted for effective significance analysis of proteomic data. It provides much richer information about the protein differential expression profiles and is particularly useful in the estimation of false discovery rates and miss rates. [ABSTRACT FROM AUTHOR]

Organochlorine pesticides were used extensively in the Yangtze River Delta, China. However, knowledge about their residual levels and environmental fates in soils of this area is limited. This paper presents the residue isomers and spatial pattern of dichlorodiphenyltrichloroethane (DDT) in soils across 17 main cities in the Yangtze River Delta. Forty-three soil surface (0-15 cm) samples were collected during a field campaign conducted in October 2003 in the Delta. Six DDT isomers (1-[2-chlorophenyl]- 1-[4-chlorophenyl]-2,2-dichloroethane [o,p'-DDD], 1-[2-chlorophenyl]-1-[4-chlorophenyl]-2,2-dichloroethylene [o,p-'DDE], 1,1,1- trichloro-2-[p-chlorophenyl]-2-[o-chlorophenyl]ethane [o,p'-DDT], p,p'-dichlorodiphenyldichloroethane [p,p'-DDD], p,p'-dichlorodiphenyldichloroethylene [p,p'-DDE], p,p'-dichlorodiphenyltrichloroethane [p,p'-DDT]) were detected using gas chromatography. The results show that p,p'-DDE was the dominant isomer in the soil samples. The levels of DDT are generally low in soils of this area and are comparable to DDT levels in other cities in China and in soils from developed countries such as the United States and Germany. The isomer ratios of o,p'-DDT to p,p'-DDT and DDT to (DDD + DDE) were employed to identify the source of DDT. The computed ratios implied that the source of DDT might be related to the application of dicofol, an acaricide manufactured from technical DDTs and mainly used on cotton fields to treat mites. [ABSTRACT FROM AUTHOR]

We determined the global protein turnover profiles for Mycobacterium smegmatis under acid shock and iron starvation conditions using a simple 15N isotope doping technique and a complete medium replacement method for chasing. We used a high-resolution hybrid-linear ion trap-Fourier transform mass spectrometer coupled with nanoliquid chromatography separation to measure protein turnover values for 151 proteins over a dynamic range of 3 orders of magnitude ranging from about 0.2 to 500. Of these 151 proteins, 31 had significant protein turnover changes (p <0.05) at both stress conditions and had protein turnover values increased or decreased by more than 2-fold under at least one stress condition. Protein turnover increased under acid shock for 28 of the 31 proteins but decreased under iron starvation for all the 31 proteins. Only two proteins had protein turnover lowered by more than 2-fold (p <0.05) under both stress conditions, including an ATP synthase F1 β subunit (MSMEG4921; AtpD) and a catalase/peroxidase (MSMEG6346; KatG). KatG is required for in vivo activation of isoniazid to be bacterialcidal. Decrease of KatG protein turnover under both stress conditions supports the view that isoniazid may induce a dormancy program in mycobacteria, which in turn limits the efficacy of this drug against dormant subpopulation of mycobacteria. Thus, measuring protein turnover in stressed Mycobacterium cells has implications in understanding drug action and resistance mechanisms. [ABSTRACT FROM AUTHOR]

Based on the datum line survey in August 2005 and June and August of 2006, water samples were collected in 30 sites to examine the trend of spatial distribution and temporal change of dissolved metals in seawater of Jinzhou Bay, China. The results showed that copper (Cu), lead (Pb), zinc (Zn), and cadmium (Cd) concentrations ranged from 1.71 to 3.49, 0.38 to 1.19, 21.77 to 39.16, and 1.65 to 2.01 μg/L, respectively. Except for Zn, the dissolved metal concentrations in August 2006 were much higher than those in August 2005. The concentrations in June 2006 were also higher than those in August 2006. The highest concentrations of dissolved metal were determined in samples collected from southwest of the Bay near sewage outfalls of Huludao Zinc Plant and Bohai Shipyard and the mouths of Wuli and Cishan rivers. The concentrations of dissolved metals increased inshore as compared with offshore. The principal contaminated factors were Zn, Cd, and Pb in the Jinzhou Bay. Significant positive correlations existed between the concentrations of Cu and Cd (0.016), as well as Zn and Cd (0.000). The overall results revealed that the Bohai Sea was one of the most contaminated areas by dissolved metals compared to other coastal areas in China. [ABSTRACT FROM AUTHOR]

Methanosarcina acetivorans produces acetate, formate, and methane when cultured with CO as the growth substrate [Rother M, Metcalf WW (2004) Proc Natl Acad sci USA 101:16929–16934], which suggests novel features of CO metabolism. Here we present a genome-wide proteomic approach to identify and quantify proteins differentially abundant in response to growth on CO versus methanol or acetate. The results indicate that oxidation of CO to CO2 supplies electrons for reduction of CO2 to a methyl group by steps and enzymes of the pathway for CO2 reduction determined for other methane-producing species. However, proteomic and quantitative RT-PCR results suggest that reduction of the methyl group to methane involves novel methyltransferases and a coenzyme F420H2:heterodisulfide oxidoreductase system that generates a proton gradient for ATP synthesis not previously described for pathways reducing CO2 to methane. Biochemical assays support a role for the oxidoreductase, and transcriptional mapping identified an unusual operon structure encoding the oxidoreductase. The proteomic results further indicate that acetate is synthesized from the methyl group and CO by a reversal of initial steps in the pathway for conversion of acetate to methane that yields ATP by substrate level phosphorylation. The results indicate that M. acetivorans utilizes a pathway distinct from all known CO2 reduction pathways for methane formation that reflects an adaptation to the marine environment. Finally, the pathway supports the basis for a recently proposed primitive CO-dependent energy-conservation cycle that drove and directed the early evolution of life on Earth. [ABSTRACT FROM AUTHOR]

The paper summarizes the excavation methodology, based on analysis of the characteristics of the surrounding rock mass, which has been involved in Xiaolangdi multipurpose dam project. Some special support and excavation methods, such as twin side drift and lattice girder, moderate blasting and double-layer mesh to collapsed tunnel and fault zone, are presented. [Copyright &y& Elsevier]

Nowadays FinFETs integrated into complex applications can fulfill the demand of new technology and make chips that can compute faster. Simultaneously various novel FinFETs structures come up constantly. In this brief, the impact of significant geometry parameters variations to device performance has been studied, such as fin height (Hfin), fin width (Wfin), fin spacing (Sfin), aspect ratio (Wfin/Hfin), and so on. In the result, we are able to determine the optimum device parameters for Multi-fin FinFETs. Meanwhile we analyze the parasitic gate capacitance and resistance of the multi-fin FinFETs using a conformal mapping method. To minimize the number of model fitting parameters, nondimensionalization technique is used. An effective lumped resistance model derived from distributed RC network is in use. Also, an analytical parasitic gate capacitance model is proposed, combined with parasitic capacitive couplings between source/drain fins and gates. Those analytical model can be applied for accurate circuit simulations of multi-fin FinFETs devices. The results presented in this paper can be of great help to device designers in designing 3-D devices as per their requirement. [ABSTRACT FROM AUTHOR]

In this paper, an efficient three-dimensional finite-element method (FEM) is introduced to study the scattering from complex three-dimensional objects in the layered media. The proposed method is valid to targets which are located either close to or far away from the media interface. Furthermore, the interface can be either a planar or rough surface in the computational domain. To improve efficiency, the preconditioned conjugate gradient method for normal equations (CGN) are proposed to solve the FEM linear system. Numerical examples are presented to demonstrate the accuracy and efficiency of the presented method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of output feedback adaptive stabilization control design for a class of nonholonomic chained systems with uncertainties, involving virtual control coefficients, unknown nonlinear parameters, and unknown time delays. The objective is to design a robust nonlinear output-feedback switching controller, which can guarantee the stabilization of the closed loop systems. An observer and an estimator are employed for states and parameters estimates, respectively . A constructive controller design procedure is proposed by applying input-state scaling transformation, parameter separation technique, and back stepping recursive approach. Simulation results are provided to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

To study the proteome response of Mycobacterium tuberculosis H37Rv to a change in iron level, iron-starved late-log-phase cells were diluted in fresh low- and high-iron media containing [15N] -labeled asparagine as the sole nitrogen source for labeling the proteins synthesized upon dilution. We determined the relative protein abundance and protein turnover in M. tuberculosis H37Rv under these two conditions. For measurements, we used a high-resolution hybrid-linear ion trap-Fourier transform mass spectrometer coupled with nanoliquid chromatography separation. While relative protein abundance analysis shows that only 5 proteins were upregulated by high iron, 24 proteins had elevated protein turnover for the cells in the high-iron medium. This suggests that protein turnover is a sensitive parameter to assess the proteome dynamics. Cluster analysis was used to explore the interconnection of protein abundance and turnover, revealing coordination of the cellular processes of protein synthesis, degradation, and secretion that determine the abundance and allocation of a protein in the cytosol and the extracellular matrix of the cells. Further potential utility of the approach is discussed. [ABSTRACT FROM AUTHOR]

We have used the new high-throughput mutation-scanning technique temperature-gradient capillary electrophoresis (TGCE) for the identification of point mutations induced by N-ethyl- N-nitrosourea (ENU) in the mouse genome. TGCE detects the presence of heteroduplex molecules formed between a wild-type gene segment and the corresponding homologous segment containing an induced mutation or a naturally occurring single nucleotide polymorphism (SNP). Partially denatured heteroduplex molecules are resolved from homoduplexes by virtue of their differential mobilities during capillary electrophoresis conducted in a finely controlled temperature gradient. Simultaneous heteroduplex analysis of 96 amplicons ranging from 150 to 600 bp in size is achieved in approximately 45 min without the need for predetermining the melting profile of each fragment. Initially, we exploited known mouse mutations to develop TGCE protocols for analyzing unpurified PCR samples amplified from crude tail-DNA preparations. TGCE was then applied to the rapid identification of three new ENU-induced mutations recovered from regional mutagenesis screens of a segment of mouse Chromosome 7. Enzyme assays and quantitative reverse transcription-PCR (qRT-PCR) methods validated these new mutations. Our data demonstrate that rapid mutation scanning with TGCE, followed by sequence verification only of detected positives, is an efficient approach to the identification of point mutations in the mouse genome. [ABSTRACT FROM AUTHOR]