The Usefulness of DNA Sequencing After Extraction by Whatman FTA Filter Matrix Technology and Phenotypic Tests for Differentiation of Candida albicans and Candida dubliniensis

Since C. dubliniensis is similar to C. albicans phenotypically, it can be misidentified as C. albicans. We aimed to investigate the prevalence of C. dubliniensis among isolates previously identified as C. albicans in our stocks and to compare the phenotypic methods and DNA sequencing of D1/D2 region on the ribosomal large subunit (rLSU) gene. A total of 850 isolates included in this study. Phenotypic identification was performed based on germ tube formation, chlamydospore production, colony colors on chromogenic agar, inability of growth at 45 °C and growth on hypertonic Sabouraud dextrose agar. Eighty isolates compatible with C. dubliniensis by at least one phenotypic test were included in the sequence analysis. Nested PCR amplification of D1/D2 region of the rLSU gene was performed after the fungal DNA extraction by Whatman FTA filter paper technology. The sequencing analysis of PCR products carried out by an automated capillary gel electrophoresis device. The rate of C. dubliniensis was 2.35 % (n = 20) among isolates previously described as C. albicans. Consequently, none of the phenotypic tests provided satisfactory performance alone in our study, and molecular methods required special equipment and high cost. Thus, at least two phenotypic methods can be used for identification of C. dubliniensis, and molecular methods can be used for confirmation.     

Calorie restriction modulates hippocampal NMDA receptors in diet-induced obese rats

Calorie restriction (CR) has attracted increased interest since CR enhances lifespan and alters age-related decline in hippocampal-dependent cognitive functions. Obesity is associated with poor neurocognitive outcome including impaired hippocampal synaptic plasticity and cognitive abilities such as learning and memory. N-Methyl-D-aspartate receptors (NMDARs) are linked to hippocampal-dependent learning and memory, which may be stabilized by CR. In the present study, we aimed to establish the effects of CR on NMDARs in CA1 region of hippocampus in obese and non-obese rats. In addition, malondialdehyde (MDA) levels were determined as a marker for lipid peroxidation (LPO) in hippocampus. Four groups were constituted as control group (C, n?=?9), obese group (OB, n?=?10), obese calorie-restricted group (OCR, n?=?9), and non-obese calorie-restricted group (NCR, n?=?10). OCR and NCR were fed with a 60% CR diet for 10 weeks. After 10 weeks of CR, the MDA levels significantly decreased in the calorie-restricted groups. Obesity caused significant decreases in NR2A and NR2B subunit expressions in the hippocampus. The hippocampal NR2A and NR2B levels significantly increased in the OCR group compared with the OB group (P?相似文献   

Autophagy and mTOR pathways in mouse embryonic stem cell,lung cancer and somatic fibroblast cell lines

Embryonic developmental stages and regulations have always been one of the most intriguing aspects of science. Since the cancer stem cell discovery, striking for cancer development and recurrence, embryonic stem cells and control mechanisms, as well as cancer cells and cancer stem cell control mechanisms become important research materials. It is necessary to reveal the similarities and differences between somatic and cancer cells which are formed of embryonic stem cells divisions and determinations. For this purpose, mouse embryonic stem cells (mESCs), mouse skin fibroblast cells (MSFs) and mouse lung squamous cancer cells (SqLCCs) were grown in vitro and the differences between these three cell lines signalling regulations of mechanistic target of rapamycin (mTOR) and autophagic pathways were demonstrated by immunofluorescence and real-time polymerase chain reaction. Expressional differences were clearly shown between embryonic, cancer and somatic cells that mESCs displayed higher expressional level of Atg10, Hdac1 and Cln3 which are related with autophagic regulation and Hsp4, Prkca, Rhoa and ribosomal S6 genes related with mTOR activity. LC3 and mTOR protein levels were lower in mESCs than MSFs. Thus, the mechanisms of embryonic stem cell regulation results in the formation of somatic tissues whereas that these cells may be the causative agents of cancer in any deterioration.     

A tractable revenue management model for capacity allocation and overbooking over an airline network

In this paper, we develop a revenue management model to jointly make the capacity allocation and overbooking decisions over an airline network. The crucial observation behind our model is that if the penalty cost of denying boarding to the reservations were given by a separable function, then the optimality equation for the joint capacity allocation and overbooking problem would decompose by the itineraries. We exploit this observation by building an approximation to the penalty cost that is separable by the numbers of reservations for different itineraries. In this case, we can obtain an approximate solution to the optimality equation by plugging the separable approximation into the boundary condition of the optimality equation. Our computational experiments compare our approach with a standard deterministic linear programming formulation, as well as a recent joint capacity allocation and overbooking model. When compared with the standard deterministic linear programming formulation, our approach can provide significant profit improvements. On the other hand, when compared with the recent joint capacity allocation and overbooking model, our approach can provide similar profit performance with substantially shorter runtimes.     

Serum adipokine and ghrelin levels in nonalcoholic steatohepatitis

Adipokines and ghrelin play role in insulin resistance, the key pathophysiological abnormality in patients with nonalcoholic fatty liver diseases. In the present study, relationship between nonalcoholic steatohepatitis (NASH) and serum adipokine and ghrelin levels was investigated. Thirty seven patients with biopsy-proven NASH and 25 age- and sex-matched controls were enrolled. Ten of NASH patients (27%) had diabetes mellitus (n = 5) or impaired glucose tolerance (n = 5). Body mass index (BMI) was less than 30 kg/m(2) in 67.6% of patients, while in the remaining 32.4% it was more than 30 kg/m(2). Serum adiponectin, leptin, TNF-alpha, and ghrelin were determined. Serum leptin (15.49 +/- 4.84 vs 10.31 +/- 2.53) and TNF-alpha (12.1 +/- 2.7 vs 10.31 +/- 2.56) levels were significantly higher in the NASH group compared to in the control group (P < .001 for each). Nevertheless, adiponectin (11.1 +/- 2.1 vs 17.3 +/- 2.8) and ghrelin (6.46 +/- 1.1 vs 7.8 +/- 1.1) levels were lower in the NASH group than in the control group (P < .001 for each). Serum levels of the adipokines and ghrelin, however, were comparable in the subgroups of patients regardless of whether BMI was < 30 or > 30 or glucose tolerance was impaired or not (P > .05). Additionally, neither adipokines nor ghrelin was correlated with histopathological grade and stage (P > .05). In conclusion; there is a significant relationship between NASH and adipokines and ghrelin independent from BMI and status of the glucose metabolism. These cytokines that appear to have role in the pathogenesis of NASH, however, do not have any effect upon the severity of the histopathology.     

Iron metabolism and drug resistance in cancer

Iron is an essential inorganic element for various cellular events. It is directly associated with cell proliferation and growth; therefore, it is expected that iron metabolism is altered in tumor cells which usually have rapid growth rates. The studies on iron metabolism of tumor cells have shown that tumor cells necessitated higher concentrations of iron and the genes of iron uptake proteins were highly over-expressed. However, there are limited number of studies on overall iron metabolism in drug-resistant tumor cells. In this article, we evaluated the studies reporting the relationship between drug resistance and iron metabolism and the utilization of this knowledge for the reversal of drug resistance. Also, the studies on iron-related cell death mechanism, ferroptosis, and its relation to drug resistance were reviewed. We focus on the importance of iron metabolism in drug-resistant cancer cells and how alterations in iron metabolism participate in drug-resistant phenotype.     

Construction of efficient bioelectrochemical devices: Improved electricity production from cyanobacteria (Leptolyngbia sp.) based on π-conjugated conducting polymer/gold nanoparticle composite interfaces

In this study, gold electrodes (GE) were coated with conducting polymers to obtain a high photocurrent using cyanobacteria from a novel bioelectrochemical fuel cell. For this purpose, 4-(4H-ditiheno[3,2-b:2',3'-d]pyrol-4-yl) aniline and 5-(4H-dithieno[3,2-b:2',3'-d]pyrol-4-yl) napthtalane-1-amine monomers were coated on GE by performing an electropolymerization process. After that, gold nanoparticles (AuNP) were specifically modified by 2-mercaptoethane sulfonic acid and p-aminothiophenol to attach to the electrode surface. The conducting polymers GE coat was modified with functionalized AuNP using a cross-linker. The resulting electrode structures were characterized by cyclic voltammetry and chronoamperometry under on-off illumination using a fiber optic light source. Cyanobacteria Leptolyngbia sp. was added to the GE/conducting polymer/AuNP electrode surface and stabilized by using a cellulose membrane. During the illumination, water was oxidized by the photosynthesis, and oxygen was released. The released oxygen was electrocatalytically reduced at the cathode surface and a 25 nA/cm ² photocurrent was observed in GE/ Leptolyngbia sp. After the electrode modifications, a significant improvement in the photocurrent up to 630 nA/cm ² was achieved.     

Takayasu's arteritis is associated with HLA-B*52, but not with HLA-B*51, in Turkey

Introduction

HLA-B*51 and HLA-B*52 are two close human leukocyte antigen (HLA) allele groups with minor amino acid differences. However, they are associated with two different vasculitides (HLA-B*51 in Behçet's disease and HLA-B*52 in Takayasu's arteritis (TAK)) and with major clinical and immunological differences. In this study, we aimed to screen a large cohort of TAK patients from Turkey for the presence of HLA-B*51 and HLA-B*52 as susceptibility and severity factors.

Methods

TAK patients (n = 330) followed at a total of 15 centers were included in the study. The mean age of the patients was 37.8 years, and 86% were women. DNA samples from the patients and healthy controls (HC; n = 210) were isolated, and the presence of HLA-B*51 or HLA-B*52 was screened for by using PCR with sequence-specific primers.

Results

We found a significant association of HLA-B*52 with TAK (20.9% vs HC = 6.7%, P = 0.000, OR = 3.7, 95% CI = 2.02 to 6.77). The distribution of HLA-B*51 did not differ between TAK patients and HCs (22.7% vs 24.8%, OR = 0.9, 95% CI = 0.60 to 1.34). The presence of HLA-B*52 decreased in late-onset patients (> 40 years of age; 12.0%, P = 0.024, OR = 0.43, 95% CI = 0.20 to 0.91). Patients with angiographic type I disease with limited aortic involvement also had a lower presence of HLA-B*52 compared to those with all other disease subtypes (13.1% vs 26%, P = 0.005, OR = 0.43, 95% CI = 0.23 to 0.78).

Conclusions

In this study, the previously reported association of TAK with HLA-B*52 in other populations was confirmed in patients from Turkey. The functional relevance of HLA-B*52 in TAK pathogenesis needs to be explored further.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.