Unlocking the potential of blockchain technology in enhancing the fisheries supply chain: an exploration of critical adoption barriers in China.

The application of blockchain technology holds significant potential for improving efficiency, resilience, and transparency within the Fisheries Supply Chain (FSC). This study addresses the critical barriers hindering the adoption of blockchain technology (BT) in the Chinese FSC, recognizing the unique challenges posed by its intricacies. Through a comprehensive literature review, fourteen Critical Barrier Factors (CBFs) were identified, and a grey Delphi method was employed to distill this set. Five pivotal CBFs emerged, including "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network". A subsequent grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis revealed the causal relationships among these factors, categorizing them into effect and cause groups. "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network" were identified as primary influencing factors demanding attention for effective BT integration in the FSC. The findings serve as a valuable resource for FSC stakeholders, assisting in prioritizing efforts to address these barriers. The discerned causal relationships provide guidance for managers in optimizing resource allocation. Ultimately, this research advocates for the adoption of blockchain technology in the fisheries supply chain to enhance overall performance and operational efficiency.

AQI prediction using layer recurrent neural network model: a new approach.

The air quality index (AQI) prediction is important to evaluate the effects of air pollutants on human health. The airborne pollutants have been a major threat in Delhi both in the past and coming years. The air quality index is a figure, based on the cumulative effect of major air pollutant concentrations, used by Government agencies, for air quality assessment. Thus, the main aim of the present study is to predict the daily AQI one year in advance through three different neural network models (FF-NN, CF-NN and LR-NN) for the year 2020 and compare them. The models were trained using AQI values of previous year (2019). In addition to main air pollutants like PM10/PM2.5, O3, SO2, NOx, CO and NH3, the non-criteria pollutants and meteorological data were also included as input parameter in this study. The model performances were assessed using statistical analysis. The key air pollutants contributing to high level of daily AQI were found to be PM2.5/PM10, CO and NO2. The root mean square error (RMSE) values of 31.86 and 28.03 were obtained for the FF-NN and CF-NN models respectively whereas the LR-NN model has the minimum RMSE value of 26.79. LR-NN algorithm predicted the AQI values very closely to the actual values in almost all the seasons of the year. The LR-NN performance was also found to be the best in post-monsoon season i.e., October and November (maximum R2 = 0.94) with respect to other seasons. The study would aid air pollution control authorities to predict AQI more precisely and adopt suitable pollution control measures. Further research studies are recommended to compare the performance of LR-NN model with statistical, numerical and computational models for accurate air quality assessment.

Modelling of compression ignition engine by soft computing techniques (ANFIS-NSGA-II and RSM) to enhance the performance characteristics for leachate blends with nano-additives.

Integrating nanoparticles in waste oil-derived biodiesel can revolutionize its performance in internal combustion engines, making it a promising fuel for the future. Nanoparticles act as combustion catalysts, enhancing combustion efficiency, reducing emissions, and improving fuel economy. This study employed a comprehensive approach, incorporating both quantitative and qualitative analyses, to investigate the influence of selected input parameters on the performance and exhaust characteristics of biodiesel engines. The focus of this study is on the potential of using oils extracted from food waste that ended up in landfills. The study's results are analysed and compared with models created using intelligent hybrid prediction approaches including adaptive neuro-fuzzy inference system, Response surface methodology-Genetic algorithm, and Non sorting genetic algorithm. The analysis takes into account engine load, blend percentage, nano-additive concentration, and injection pressure, and the desired responses are the thermal efficiency and specific energy consumption of the brakes, as well as the concentrations of carbon monoxide, unburned hydrocarbon, and oxides of nitrogen. Root-mean-square error and the coefficient of determination were used to assess the predictive power of the model. Comparatively to Artificial Intelligence and the Response Surface Methodology-Genetic Algorithm model, the results provided by NSGA-II are superior. This is because it achieved a pareto optimum front of 24.45 kW, 2.76, 159.54 ppm, 4.68 ppm, and 0.020243% for Brake Thermal Efficiency, Brake Specific Energy Consumption, Oxides of nitrogen, Unburnt Hydro Carbon, and Carbon monoxide. Combining the precision of ANFIS's prediction with the efficiency of NSGA-optimization II's gives a reliable and thorough evaluation of the engine's settings. The qualitative assessment considered practical aspects and engineering constraints, ensuring the feasibility of applying the parameters in real-world engine applications.

Influence of fly ash on thermo-mechanical and mechanical behavior of injection molded polypropylene matrix composites.

Polypropylene composites find widespread application in industries, including packaging, plastic parts, automotive, textiles, and specialized devices like living hinges known for their remarkable flexibility. This study focuses on the manufacturing of polypropylene composite specimens by incorporating varying weight percentages of fly ash particles with polypropylene using a twin-screw extruder and injection molding machine. The composites were comprehensively tested, evaluating tensile, compressive, and flexural strength, solid-state and polymer melt properties, modulus, damping, and thermal response. The findings reveal that the compressive strength of polypropylene increases up to 2 wt% of added fly ash particles and subsequently exhibits a slight decline. Tensile strength demonstrates an increase up to 1 wt% of fly ash, followed by a decrease with a 2 wt% addition, and then a subsequent increase. Flexural strength shows improvement up to 3 wt% fly ash addition before declining. The storage modulus curve is categorized into three regions: the glassy region (up to 0 °C), the glass transition region (0-50 °C), and the glass transition region of polypropylene (>50 °C), each corresponding to different molecular motions. Weight loss curves exhibit similar trends, indicating uniform pyrolysis behavior attributed to consistent chemical bonds. Plastic degradation commences around 440 °C and concludes near 550 °C. Additionally, elemental mapping of fly ash composition identified various elements such as O, Si, K, Mg, Ca, Cl, Na, P, Al, Fe, S, Cu, Ti, and Ni. These findings offer valuable insights into the mechanical and thermal properties of polypropylene composites reinforced with fly ash, rendering them suitable for a wide range of industrial applications necessitating strength and durability across temperature variations.

NOD1 activation in 3T3-L1 adipocytes confers lipid accumulation in HepG2 cells.

AIMS: Activation of specific innate immune receptors has been characterized to modulate nutrient metabolism in individual metabolic tissue directly or indirectly via secretory molecules. Activation of the nucleotide-binding oligomerization domain-containing protein 1 (NOD1) in adipocytes has been reported to induce lipolysis linked with insulin resistance and inflammatory response. These cues are positioned to modulate metabolic action in distal organs through paracrine/endocrine signaling. Here, we assessed the role of NOD1-mediated lipolysis and inflammatory response in adipocytes to affect lipid metabolism in hepatocytes. MAIN METHODS: Human hepatoma cells (HepG2) were exposed to conditioned medium obtained from 3 T3-L1 adipocytes pretreated with NOD1 ligand (iE-DAP) and the effects on lipid accumulation, inflammation and insulin response were assessed. Activation of mechanisms leading to hepatic lipid accumulation was investigated by gene expression analysis. KEY FINDINGS: The conditioned medium from NOD1-activated 3 T3-L1 adipocytes (CM-DAP) induced lipid accumulation in HepG2 cells, driven by both lipolysis and inflammatory responses. The CM-DAP-induced lipid accumulation was independent to de novo lipogenesis and resulted from the enhanced transport of fatty acids inside and consequent increase in rate of triglycerides synthesis in hepatocytes. Moreover, CM-DAP-induced lipid accumulation instigated the expression of the markers of fatty acid oxidation and VLDL assembly for the export of triglycerides from hepatocyte. Furthermore, CM-DAP-induced lipid accumulation was associated with induction of inflammatory response and impairment of insulin signaling in HepG2 cells. SIGNIFICANCE: Beyond showing liver-specific mechanisms to adipocytes-derived factors, our findings support the involvement of adipose tissue as a mediator in NOD1-mediated biological responses to modulate hepatic metabolism.

Moringa oleifera impedes protein glycation and exerts reno-protective effects in streptozotocin-induced diabetic rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Moringa oleifera is a valued plant with wide distribution in tropical and subtropical regions of the world. It is traditionally used for the treatment of fever, infections, rheumatism, cancer, improving cardiac, renal and hepatic functions, and regulating blood glucose level. The plant has been scientifically reported for the anti-inflammatory, antioxidant, renoprotective, and anti-diabetic properties. Diabetic patients are prone to develop end-stage renal diseases due to incidence of diabetes-induced renal dysfunctions. Given that, increased production and accumulation of advanced glycation end-products (AGEs) play a conspicuous role in the development of diabetes-linked renal dysfunctions, nature-based interventions with AGEs inhibitory activity can prevent renal dysfunctions leading to renoprotection. AIM OF THE STUDY: The study aimed to demonstrate the preventive effects of the ethanolic extract of the leaves of Moringa oleifera (EEMO) on protein glycation and its further assessment for the renoprotective effect in diabetic rats. MATERIALS AND METHODS: Antiglycation activity of EEMO was assessed in vitro using bovine serum albumin. For reno-protective activity assessment, streptozotocin (STZ)-induced diabetic rats were orally treated with EEMO (100 mg/kg) or standard antiglycation agent aminoguanidine (100 mg/kg) for consecutive 8 weeks. The effects on glucose homeostasis, renal functions, and renal morphology were assessed by clinical biochemistry, molecular and histological examination. RESULTS: Presence of EEMO efficiently prevented glucose-, fructose- or methylglyoxal-mediated glycation of protein. Under in vivo set-up, compared to diabetic control rats, EEMO treatment effectively improved the glucose tolerance and body weight, and reduced the serum levels of triglycerides and total cholesterol. Additionally, EEMO administration significantly ameliorated renal dysfunctions in diabetic rats characterized by improved levels of creatinine, urea nitrogen, and uric acid in serum, and total protein level in urine, accompanied by improved kidney morphology. The diabetes-associated pro-inflammatory response characterized by upregulated expression of the inducible nitric oxide synthase (iNos), activation of nuclear factor kappa B (NF-κB) and the raised levels of inflammatory factors, interleukin-1 beta (IL-1ß) and interleukin-6 (IL-6) in renal tissue was significantly attenuated in EEMO-treated rats. Moreover, EEMO treatment diminished renal reactive oxygen species (ROS) levels in diabetic animals. CONCLUSIONS: Our study demonstrated that EEMO prevented AGEs formation and ameliorated renal dysfunctions in diabetic rats by blocking inflammatory/oxidative pathways. Our observations justify M. oleifera as a potential source of therapeutic interventions for diabetic nephropathy management.

Convergence of Fructose-Induced NLRP3 Activation with Oxidative Stress and ER Stress Leading to Hepatic Steatosis.

High fructose flux enhances hepatocellular triglyceride accumulation (hepatic steatosis), which is a prime trigger in the emergence of hepatic ailments. Nevertheless, the pathophysiology underlying the process is not completely understood. Emerging evidences have revealed the inputs from multiple cues including inflammation, oxidative stress, and endoplasmic reticulum (ER) stress in the development of hepatic steatosis. Here, we substantiated the role of NLRP3 inflammasome and its convergence with oxidative and ER stress leading to hepatic steatosis under high fructose diet feeding. Male SD rats were fed on 60% high fructose diet (HFrD) for 10 weeks and treated with antioxidant quercetin or NLRP3 inflammasome inhibitor glyburide during the last 6 weeks, followed by metabolic characterization and analysis of hepatic parameters. HFrD-induced hepatic steatosis was associated with the activation of NLRP3 inflammasome, pro-inflammatory response, oxidative, and ER stress in liver. Treatment with quercetin abrogated HFrD-induced oxidative stress, along with attenuation of NLRP3 activation in the liver. On the other hand, inhibition of NLRP3 signaling by glyburide suppressed HFrD-induced oxidative and ER stress. Both glyburide or quercetin treatment significantly attenuated hepatic steatosis, associated with mitigated expression of the lipogenic markers in liver. Our findings verified the association of NLRP3 inflammasome with oxidative and ER stress in fructose-induced lipogenic response and indicate that in addition to be a target of oxidative/ER stress, NLRP3 can act as a trigger for oxidative/ER stress to activate a vicious cycle where these cues act in a complex manner to propagate inflammatory response, leading to hepatic steatosis.

Fructose-mediated NLRP3 activation induces inflammation and lipogenesis in adipose tissue.

Adipose tissue plays a crucial role in energy intake and regulation of metabolic homeostasis. Fructose consumption implicates in development and progression of metabolic dysfunctions. Fructose is a lipogenic sugar known to induce inflammatory response. However, the role of specific inflammatory signal such as nucleotide-binding and oligomerization domain-like receptor, leucine-rich repeat and pyrin domain containing protein 3 (NLRP3) in fructose-induced inflammatory response and its relevance to lipogenesis in adipose tissue are elusive. We assessed NLRP3 activation and its significance in inflammatory response and lipogenesis in epididymal adipose tissue of 60% fructose diet (HFrD)-fed rats. The long-term consumption of HFrD led to impairment of glucose metabolism, development of visceral adiposity, insulin resistance, and elevation of serum triglycerides level, accompanied by activation of NLRP3 in adipose tissue. NLRP3 inflammasome activation in adipose tissue was associated with up-regulated expression of Nlrp3, Asc, and Caspase-1, and raised caspase-1 activity, which resulted in increased expression of IL-1ß and IL-18 and secretion of IL-1ß. Moreover, lipid accumulation and expression of transcription factors exacerbating accumulation of lipids were augmented in adipose tissue of HFrD-fed rats. Treatment with glyburide, quercetin or allopurinol corrected HFrD-induced dyslipidemia or hyperuricemia, and blocked NLRP3 activation, leading to mitigated inflammatory signaling and lipid accumulation in adipose tissue, improved glucose tolerance and insulin sensitivity in HFrD-fed rats. These data suggest the role of NLRP3 inflammasome to establish linkage among inflammation, lipid accumulation and insulin resistance in adipose tissue, and targeting NLRP3 inflammasome may be a plausible approach for prevention and management for fructose-induced metabolic impairments.

Furostanol saponins from Asparagus racemosus as potential hypoglycemic agents.

Bioactivity guided phytochemical investigation led to isolation of six undescribed furostanol saponins, furoasparoside A-F along with five known compounds, gallic acid, methyl gallate, quercetin-3-O-ß-glucopyranoside, liquiritigenin 4׳-O-ß-apiofuranosyl-(1 â†’ 2)-ß-glucopyranoside and ß-glucogallin for the first time from the roots of Asparagus racemosus. Isolated saponins were screened for their antidiabetic potential in L6-GLUT4myc myotubes in vitro followed by an in vivo evaluation in streptozocin-induced diabetic rats and db/db mice. Furoasparoside E produced a notable decrease in the postprandial blood glucose profile, in leptin receptor-deficient db/db mice, type 2 diabetes model. The effect of furoasparoside E on GLUT4 translocation was found to be mediated by the AMPK-dependent signaling pathway in L6-GLUT4myc myotubes. Moreover, it emerged as a stable plant metabolite with higher bioavailability and efficacy in in vivo pharmacokinetic studies. Therefore, these studies indicated that furoasparoside E may serve as a propitious lead for the management of type 2 diabetes and its secondary complications from natural source.

Insulin resistance corresponds with a progressive increase in NOD1 in high fat diet-fed mice.

PURPOSE: Innate immune components participate in obesity-induced inflammation, which can contribute to endocrine dysfunction during metabolic diseases. However, the chronological activation of specific immune proteins such as Nucleotide-binding oligomerization domain-containing protein 1 (NOD1) and relevance to cellular crosstalk during the progression of obesity-associated insulin resistance (IR) is not known. METHODS: The NOD1 signaling in various insulin-sensitive metabolic tissues during the progression of diet-insulin resistance was assessed in C57BL/6J mice fed with 60% high-fat diet (HFD) for 4, 8, 12, and 16 weeks. Intestinal permeability was measured using FITC-dextran. NOD1 activating potential was analyzed using HEK-Blue mNOD1 cells. RESULTS: HFD-fed mice showed progressive induction of glucose intolerance and impairment of insulin signaling in key metabolic tissues. We found a time-dependent increase in intestinal permeability coupled with transport and accumulation of NOD1 activating ligand in the serum of HFD-fed mice. We also observed a progressive accumulation of γ-D-glutamyl-meso-diaminopimelic acid (DAP), a microbial peptidoglycan ligand known to activate NOD1, in serum samples of the HFD-fed mice. There was also a progressive increase in transcripts levels of NOD1 in bone marrow-derived macrophages during HFD-feeding. In addition, skeletal muscle, adipose and liver, the key insulin sensitive metabolic tissues also had a time-dependent increase in transcripts of NOD1 and Rip2 and a corresponding activation of pro-inflammatory responses in these tissues. CONCLUSION: These data highlight the correlation of inflammation and insulin resistance to NOD1 activation in the bone marrow derived macrophages and insulin responsive metabolic tissues during high fat diet feeding in mice.

Antiglycation activity of ß-glucogallin from Asparagus racemosus.

The increased formation and accumulation of advanced glycation end products (AGEs) has been implicated in pathogenesis of various chronic ailments, including diabetes-associated secondary complications, atherosclerosis, aging, inflammatory and neurodegenerative diseases. Therefore, inhibition of AGEs formation is an imperative strategy for alleviating diverse pathologies. Here, we have demonstrated the AGEs inhibitory activity of ß-glucogallin, isolated for the first time from the roots of Asparagus racemosus. ß-glucogallin significantly mitigated fructose-, glucose- and methylglyoxal-induced glycation of bovine serum albumin (BSA). Also, the presence of ß-glucogallin decreased fructosamine and protein carbonyls content, and increased thiol group content in the fructose-BSA system. These activities of ß-glucogallin from Asparagus racemosus underscore its likely pharmacological potential for impeding AGEs-related metabolic disorders.

Harnessing the power of electrophoresis and chromatography: Offline coupling of reverse phase liquid chromatography-capillary zone electrophoresis-tandem mass spectrometry for analysis of host cell proteins in monoclonal antibody producing CHO cell line.

Host cell proteins (HCPs) are widely regarded as a critical quality attribute for a biotherapeutic product. Bottom up MS is the present gold standard for HCP analysis but suffers from incomplete protein identification due to complex nature of the HCP mixture and limited separation efficiency of the preceding LC-based systems. In this paper, we present for the first time an application involving use of LC-CE-MS/MS platform for analysis of HCPs. It has been demonstrated that the proposed platform has been able to successfully identify 397 HCPs from the supernatants of recombinant Chinese hamster ovary cells, twice and thrice the number of proteins identified by the state-of-the-art LC-MS/MS (189 HCPs) and CE-MS/MS (128 HCPs) analyses, respectively. Of these, 225 HCPs were unique to the LC-CE-MS/MS approach and were not identified by either LC-MS/MS or CE-MS/MS. It is observed that the LC-CE-MS/MS platform combines the benefits of LC-MS/MS and CE-MS/MS techniques and identifies peptides in a wider range of size, pI, and hydrophobicity. Additionally, LC-CE-MS/MS also identified more HCPs associated with cellular components, molecular functions, biological processes, peptidases, and secretory proteins. The proposed approach would thus be a useful addition in HCP analysis and secretome studies of mAb-producing Chinese hamster ovary cells.

Flavonoids from Polyalthia longifolia prevents advanced glycation end products formation and protein oxidation aligned with fructose-induced protein glycation.

Advanced glycation end products (AGEs) are reactive chemical entities formed by non-enzymatic reaction between reducing sugars and amino group of proteins. Enhanced accumulation of AGEs and associated protein oxidation contribute to pathogenesis of diabetes-associated complications. Here, we evaluated the inhibitory activity of flavonoid compounds isolated from the leaves of Polyalthia longifolia on formation of AGEs and protein oxidation. Antiglycation activity was determined by measuring the formation of AGE fluorescence intensity, Nε-(carboxymethyl) lysine, and level of fructosamine. Protein oxidation was examined using levels of protein carbonyls and thiol group. Compounds significantly (p < 0.001) restricted the formation of fluorescent AGEs in fructose- BSA and methylglyoxal-BSA systems. Furthermore, there was a decrease in levels of fructosamine and protein carbonyls, and elevation in level of thiol group in fructose-BSA in presence of flavonoids. In summary, flavonoids from Polyalthia longifolia inhibit fructose-mediated protein glycation and oxidation, and can be potential agent for preventing AGE-mediated diabetic complications.

Lead and zinc interactions - An influence of zinc over lead related toxic manifestations.

BACKGROUND: Interaction between metals is known from earlier studies, in which one metal influences the absorption and functional role of other. Lead is known to cause debilitating effects in living organisms and also prevents several essential trace metals from functioning normally. METHODS: The relevant literature using the key words lead toxicity, lead zinc interaction, zinc nutrition and the ability of zinc to act against lead has been reviewed. RESULTS: Role of several nutrients in reducing the manifestations of toxic metals have been elucidated recently. Lead damages bio-membranes, causes cognitive disabilities and disturbs the normal process of DNA replication and transcription. Zinc on the other hand helps in proper maintenance of the cellular membranes and plays an important role as a metal cofactor in most of the proteins vital for membrane integrity. Zinc has essential role in cognitive functioning, zinc finger proteins and significantly neutralizes most toxic effects of lead. CONCLUSION: Increased lead exposure and limited resources for tackling lead poisoning may cause an increased possibility of future environmental emergencies. Interactions between essential nutrient metals and non-essential toxic metals may act as important factor which can be used to target the metal toxicities. An assumption is made that the lead toxicity can be reduced by maintaining the status of essential trace metals like zinc.

NOD1 activation induces oxidative stress via NOX1/4 in adipocytes.

Activation of innate immune components promotes cell autonomous inflammation in adipocytes. Oxidative stress links pattern recognition receptor-mediated detection of inflammatory ligands and the immune response. Reactive oxygen species (ROS) may mediate the effect of nucleotide-binding oligomerization domain protein-1 (NOD1) activation on inflammation in adipocytes. Here, we define the potential role of NADPH oxidase (NOX)-derived ROS in NOD1-mediated inflammatory response in adipocytes. Differentiated 3T3-L1 adipocytes were treated with NOD1 activating ligand D-gamma-Glu-meso-diaminopimelic acid (iE-DAP) to evaluate the oxidative stress and contribution of NOX as source of intracellular ROS. NOD1 activation potently induced ROS generation in 3T3-L1 adipocytes. Of the NOX family members, expression of NOX1 and NOX4 was increased upon NOD1 activation, in a PKCδ-dependent manner. siRNA-mediated down-regulation of NOX1 or NOX4 inhibited NOD1-mediated ROS production and increased the expression of antioxidant defense enzyme catalase and superoxide dismutase (SOD). siRNA-mediated lowering of NOX1 or NOX4 also suppressed NOD1-mediated activation of JNK1/2 and NF-κB, and consequent activation of inflammatory response in 3T3-L1 adipocytes. In summary, our findings demonstrate that NOD1 activation provokes oxidative stress in adipocytes via NOX1/4 and that oxidative stress, at least in part, contributes to induction of inflammatory response. Defining the source of ROS after immune response engagement may lead to new therapeutic strategies for adipose tissue inflammation.

Bolt: a New Age Peptide Search Engine for Comprehensive MS/MS Sequencing Through Vast Protein Databases in Minutes.

Recent increases in mass spectrometry speed, sensitivity, and resolution now permit comprehensive proteomics coverage. However, the results are often hindered by sub-optimal data processing pipelines. In almost all MS/MS peptide search engines, users must limit their search space to a canonical database due to time constraints and q value considerations, but this typically does not reflect the individual genetic variations of the organism being studied. In addition, engines will nearly always assume the presence of only fully tryptic peptides and limit PTMs to a handful. Even on high-performance servers, these search engines are computationally expensive, and most users decide to dial back their search parameters. We present Bolt, a new cloud-based search engine that can search more than 900,000 protein sequences (canonical, isoform, mutations, and contaminants) with 41 post-translation modifications and N-terminal and C-terminal partial tryptic search in minutes on a standard configuration laptop. Along with increases in speed, Bolt provides an additional benefit of improvement in high-confidence identifications. Sixty-one percent of peptides uniquely identified by Bolt may be validated by strong fragmentation patterns, compared with 13% of peptides uniquely identified by SEQUEST and 6% of peptides uniquely identified by Mascot. Furthermore, 30% of unique Bolt identifications were verified by all three software on the longer gradient analysis, compared with only 20% and 27% for SEQUEST and Mascot identifications respectively. Bolt represents, to the best of our knowledge, the first fully scalable, cloud-based quantitative proteomic solution that can be operated within a user-friendly GUI interface. Data are available via ProteomeXchange with identifier PXD012700.

Detection and verification of 2.3 million cancer mutations in NCI60 cancer cell lines with a cloud search engine.

Today we have unprecedented access to human genomic and proteomic data that appear to be rapidly approaching our current understanding of comprehensive coverage. Combining genomic information with shotgun proteomics remains challenging due to the large increase in proteomics search space. However, making this connection between genomic and proteomic information is critical for cancer studies to vaccine development. Furthermore, as we progress towards personalized medicine, it will be essential for proteomics analysis to identify individual mutations and variants in order to fully understand protein networks and to develop personalized therapies. While these advantages are well-established, only a few studies have demonstrated the successful integration of proteomic data with large genomic input. We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. We use previously published proteomics data sets and identify mutations that are verified using genomic studies as well as previous proteomics efforts. Our results also emphasize the need to search for mutations in a comprehensive manner while still searching for both common and rare PTMs. SIGNIFICANCE: We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. No other proteomics search software can do so.

Fructose-induced AGEs-RAGE signaling in skeletal muscle contributes to impairment of glucose homeostasis.

Increased fructose intake has been linked to the development of dyslipidemia, obesity and impaired glucose tolerance. Due to its specific metabolic fate, fructose impairs normal lipid and carbohydrate metabolism and facilitates the non-enzymatic glycation reaction leading to enhanced accumulation of advanced glycation end products (AGEs). However, the formation of fructose-AGEs under in vivo setup and its tissue specific accumulation is less explored. Here, we investigated the impact of high fructose on AGEs accumulation in skeletal muscle and its causal role in impaired glucose homeostasis. In L6 rat skeletal muscle cells, chronic exposure to fructose induced AGEs accumulation and the cellular level of the receptor for AGEs (RAGE) and the effect was prevented by pharmacological inhibition of glycation. Under in vivo settings, Sprague Dawley rats exposed to 20% fructose in drinking water for 16 weeks, displayed increased fasting glycemia, impaired glucose tolerance, decreased skeletal muscle Akt (Ser-473) phosphorylation, and enhanced triglyceride levels in serum, liver and gastrocnemius muscle. We also observed a high level of AGEs in serum and gastrocnemius muscle of fructose-supplemented animals, associated with methylglyoxal accumulation and up regulated expression of RAGE in gastrocnemius muscle. Treatment with aminoguanidine inhibited fructose-induced AGEs accumulation and normalized the expression of RAGE and Dolichyl-Diphosphooligosaccharide-Protein Glycosyltransferase (DDOST) in gastrocnemius muscle. Inhibition of AGEs-RAGE axis counteracted fructose-mediated glucose intolerance without affecting energy metabolism. These data reveal diet-derived AGEs accumulation in skeletal muscle and the implication of tissue specific AGEs in metabolic derangement, that may open new perspectives in pathogenic mechanisms and management of metabolic diseases.

PeMtb: A Database of MHC Antigenic Peptide of Mycobacterium tuberculosis.

BACKGROUND: For design of a subunit vaccine for tuberculosis, identification of antigenic Tcell epitope is of utmost importance. Several MHC prediction server are available that can accurately predict antigenic peptide of variable lengths. However, peptides predicted from one server not necessarily are predicted form another server, thus creating a confusing situation for scientists to choose a best epitope. METHOD: Keeping the above problem in mind, we developed a comprehensive database of peptides of Mycobacterial proteins. Each protein was taken from PubMed and was run through different MHC prediction servers, with the results being compiled into one database. RESULTS: For each protein, PeMtb generates a set of three different mers of variable lengths (12 mer or 13-mer) based on their ranking; with each mer being predicted for a plethora of MHC alleles. Researcher can choose the peptide (mers) that gives best binding affinity from most of the servers. CONCLUSION: The database relieves the investigators of the painstaking task of searching various MHC prediction servers for the right epitope (T-cell epitope) for a particular Mycobacterial antigen. We trust and anticipate that PeMtb will be a practical platform for trial and computational analyses of antigenic peptides for Mycobacterium tuberculosis. All the resources and information can be accessed by PeMtb home page www.pemtb-amu.org.

Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway.

Coronary artery disease (CAD) is one of the largest causes of death worldwide yet the traditional risk factors, although useful in identifying people at high risk, lack the desired predictive accuracy. Techniques like quantitative plasma proteomics holds immense potential to identify newer markers and this study (conducted in three phases) was aimed to identify differentially expressed proteins in stable CAD patients. In the first (discovery) phase, plasma from CAD cases (angiographically proven) and controls were subjected to iTRAQ based proteomic analysis. Proteins found to be differentially expressed were then validated in the second and third (verification and validation) phases in larger number of (n = 546) samples. After multivariate logistic regression adjusting for confounding factors (age, diet, etc.), four proteins involved in the reverse cholesterol pathway (Apo A1, ApoA4, Apo C1 and albumin) along with diabetes and hypertension were found to be significantly associated with CAD and could account for approximately 88% of the cases as revealed by ROC analysis. The maximum odds ratio was found to be 6.70 for albumin (p < 0.0001), followed by Apo AI (5.07, p < 0.0001), Apo CI (4.03, p = 0.001), and Apo AIV (2.63, p = 0.003). Down-regulation of apolipoproteins and albumin implicates the impairment of reverse cholesterol pathway in CAD.