Mechanism of the binding of 2-(4'-hydroxyphenylazo)benzoic acid to bovine serum albumin

The mechanism of the binding of 2-(4'-hydroxyphenylazo)benzoic acid (HABA) to bovine serum albumin was studied by relaxation methods as well as the binding isotherm using gel chromatography. A single relaxation was observed over a wide range of HABA concentration except at the extremes of high concentration where another slow process was observed. The concentration dependence of the reciprocal relaxation time of the fast process decreased monotonically with increase in concentration of HABA at constant polymer concentration. The data were analyzed on the basis of Brown's domain structure model and were found to be consistent with a sequential binding mechanism. The azohydrazon tautomerism of HABA was identified with the intramolecular step of the complex. The activation parameters of the step, determined from the temperature dependence of the relaxation time of the fast process, showed that this step is rate limited by an enthalpy barrier in both forward and backward directions. Comparison of the activation parameters with those of other serum albumin-ligand systems suggests that there is an enthalpy-entropy compensation in the activation process of the intramolecular step with the compensation temperature at about 270 K; the enthalpy-entropy compensation is thought to be related to the hydrophobic nature of the ligand.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

Selective increase in cytokeratin synthesis in cultured rat hepatocytes in response to hormonal stimulation

Addition of a combination of insulin, dexamethasone and EGF at seeding time to cultured rat hepatocytes in serum-free medium caused a selective increase in the biosynthesis of particular cytokeratin components. This increase was prominent during the first day in culture. No significant increases were detected in the absence of hormones or in the presence of either hormones added alone or in pairs, except in the case of insulin plus dexamethasone, which yielded an effect close to that obtained with the three factors. Interestingly, the latter condition also maintained a high level of albumin production over a 6-day period in culture.     

Fluorescent analysis of alpha-keto acids in serum and urine by high-performance liquid chromatography

A selective procedure using synthetic substrates for determination of exo-1,4,-beta-glucanases in a mixture of exoglucanases , endoglucanases , and beta-glucosidases is formulated. The heterobiosides , p- nithrophenyl -beta-D- cellobioside ( pNPC ) or p-nitrophenyl-beta-D-lactoside ( pNPL ), were used as selective substrates for the measurement of exoglucanase activity. The exoglucanases (especially cellobiohydrolases , which split off cellobiose units from the nonreducing end of the cellulose chain) specifically act on the agluconic bond (between p-nitrophenyl and the disaccharide moiety) and not on the holosidic bond (between the two glucose units of cellobiose). The interfering effect of beta-glucosidase, which acts on both agluconic and holosidic bonds, is overcome by the addition of D-glucono-1,5-delta-lactone, a specific inhibitor of beta-glucosidases. The interference of endoglucanases , which also act on both agluconic and holosidic bonds, can be compensated for by prior standardization of the assay procedure with a purified endoglucanase from the studied mixture of cellulases.     

Sexual dimorphism in the pyrgomorphid grasshopper Phymateus morbillosus: from wing morphometry and flight behaviour to flight physiology and endocrinology

Abstract In the field, adult males of the grasshopper Phymateus morbillosus are able to fly for up to 1 min and cover up to c. 100 m, whereas females, although fully winged, are apparently unable to get airborne. Morphometric data indicate that the males are lighter, have longer wings, a higher ratio of flight muscles to body mass, and a lower wing load value than females. It was investigated whether this inability of females to fly is related to fuel storage, flight muscle enzymatic design and/or the presence and quantitative capacity of the endocrine system to mobilize fuels. In both sexes, readily available potential energy substrates are present in the haemolymph in similar concentrations, and the amount of glycogen in flight muscles and fat bodies does not differ significantly between males and females. Mass-specific activities of the enzymes GAPDH (glycolysis), HOAD (fatty acid oxidation) and MDH (citric acid cycle) in flight muscles are significantly lower in females compared with males, and mitochondria are less abundant in the flight muscles of females. There is no significant difference between the ability of the two sexes to oxidize various important substrates. Both sexes contain three adipokinetic peptides in their corpora cardiaca; the amount of each peptide in female grasshoppers is higher than in males.
Thus, despite some differences listed above, both sexes appear to have sufficient substrates and the necessary endocrine complement to engage in flight. It seems more likely, from the morphometric data above, that the chief reason for flightlessness is that P. morbillosus females cannot produce sufficient lift for flight; alternatively, the neuronal functioning associated with the flight muscles may be impaired in females.     

Sequences of cDNAs for human salivary and pancreatic α-amylases

The nucleotide sequences of the cloned human salivary and pancreatic α-amylase cDNAs correspond to the continuous mRNA sequences of 1768 and 1566 nucleotides, respectively. These include all of the amino acid coding regions. Salivary cDNA contains 200 bp in the 5′-noncoding region and 32 in the 3′-noncoding region. Pancreatic cDNA contains 3 and 27 bp of 5′- and 3′-noncoding regions, respectively. The nucleotide sequence humology of the two cDNAs is 96% in the coding region, and the predicted amino acid sequences are 94% homologous.Comparison of the sequences of human α-amylase cDNAs with those previously obtained for mouse α-amylase genes (Hagenbuchle et al., 1980; Schibler et al., 1982) showed the possibility of gene conversion between the two genes of human α-amylase.