ACE/ACE2 Ratio and MMP-9 Activity as Potential Biomarkers in Tuberculous Pleural Effusions

Objective: Pleural effusion is common problem, but the rapid and reliable diagnosis for specific pathogenic effusions are lacking. This study aimed to identify the diagnosis based on clinical variables to differentiate pleural tuberculous exudates from other pleural effusions. We also investigated the role of renin-angiotensin system (RAS) and matrix metalloproteinase (MMPs) in the pathogenesis of pleural exudates.Experimental design: The major components in RAS and extracellular matrix metabolism, including angiotensin converting enzyme (ACE), ACE2, MMP-2 and MMP-9 activities, were measured and compared in the patients with transudative (n = 45) and exudative (n = 80) effusions. The exudative effusions were come from the patients with tuberculosis (n = 20), pneumonia (n = 32), and adenocarcinoma (n = 28).Results: Increased ACE and equivalent ACE2 activities, resulting in a significantly increased ACE/ACE2 ratio in exudates, were detected compared to these values in transudates. MMP-9 activity in exudates was significantly higher than that in transudates. The significant correlation between ACE and ACE2 activity that was found in transudates was not found in exudates. Advanced analyses showed significantly increased ACE and MMP-9 activities, and decreased ACE2 activity in tuberculous pleural effusions compared with those in pneumonia and adenocarcinoma effusions. The results indicate that increased ACE and MMP-9 activities found in the exudates were mainly contributed from a higher level of both enzyme activities in the tuberculous pleural effusions.Conclusion: Interplay between ACE and ACE2, essential functions in the RAS, and abnormal regulation of MMP-9 probably play a pivotal role in the development of exudative effusions. Moreover, the ACE/ACE2 ratio combined with MMP-9 activity in pleural fluid may be potential biomarkers for diagnosing tuberculous pleurisy.     

Parathyroid hormone stimulates adenylate cyclase in rat cerebral microvessels

We have studied the effect of parathyroid hormone (PTH) on adenylate cyclase of microvessels isolated from rat cerebral cortex. Native bovine (b) PTH-(1–84), the synthetic amino-terminal fragment bPTH-(1–34) and the synthetic analog [Nle⁸, Nle¹⁸, Tyr³⁴]-bPTH- (1–34) amide stimulated adenylate cyclase in a dose-dependent manner with apparent ED₅₀ values of 16 nM, 6.3 nM and 15 nM respectively. The stimulation by bPTH was greatly enhanced by guanosine triphosphate. The PTH antagonist, [Nle⁸, Nle¹⁸, Tyr³⁴]-bPTH-(3–34) amide inhibited the action of bPTH-(1–84) and bPTH-(1–34). In summary, PTH stimulated adenylate cyclase in rat cerebral microvessels in a very similar manner to its stimulation in the renal cortex.     

Phylogenetics of Tribe Collabieae (Orchidaceae,Epidendroideae) Based on Four Chloroplast Genes with Morphological Appraisal

Collabieae (Orchidaceae) is a long neglected tribe with confusing tribal and generic delimitation and little-understood phylogenetic relationships. Using plastid matK, psaB, rbcL, and trnH-psbA DNA sequences and morphological evidence, the phylogenetic relationships within the tribe Collabieae were assessed as a basis for revising their tribal and generic delimitation. Collabieae (including the previously misplaced mycoheterotrophic Risleya) is supported as monophyletic and nested within a superclade that also includes Epidendreae, Podochileae, Cymbidieae and Vandeae. Risleya is nested in Collabiinae and sister to Chrysoglossum, a relationship which, despite their great vegetative differences, is supported by floral characters. Ania is a distinct genus supported by both morphological and molecular evidence, while redefined Tainia includes Nephelaphyllum and Mischobulbum. Calanthe is paraphyletic and consists four clades; the genera Gastrorchis, Phaius and Cephalantheropsis should be subsumed within Calanthe. Calanthe sect. Ghiesbreghtia is nested within sect. Calanthe, to which the disputed Calanthe delavayi belongs as well. Our results indicate that, in Collabieae, habit evolved from being epiphytic to terrestrial.     

Rapid determination of substrate specificity of Clostridium histolyticum beta-collagenase using an immobilized peptide library.

The molecular basis of the substrate specificity of Clostridium histolyticum beta-collagenase was investigated using a combinatorial method. An immobilized positional peptide library, which contains 24,000 sequences, was constructed with a 7-hydroxycoumarin-4-propanoyl (Cop) fluorescent group attached at the N terminus of each sequence. This immobilized peptide library was incubated with C. histolyticum beta-collagenase, releasing fluorogenic fragments in the solution phase. The relative substrate specificity (k(cat)/K(m)) for each member of the library was determined by measuring fluorescence intensity in the solution phase. Edman sequencing was used to assign structure to subsites of active substrate mixtures. Collectively, the substrate preference for subsites (P(3)-P(4)') of C. histolyticum beta-collagenase was determined. The last position on the C-terminal side in which the identity of the amino acids affects the activity of the enzyme is P(4)', and an aromatic side chain is preferred in this position. The optimal P(1)'-P(3)' extended substrate sequence is P(1)'-Gly/Ala, P(2)'-Pro/Xaa, and P(3)'-Lys/Arg/Pro/Thr/Ser. The Cop group in either the P(2) or P(3) position is required for a high substrate activity with C. histolyticum beta-collagenase. S(2) and S(3) sites of the protease play a dominant role in fixing the substrate specificity. The immobilized peptide library proved to be a powerful approach for assessing the substrate specificity of C. histolyticum beta-collagenase, so it may be applied to the study of other proteases of interest.     

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.     

An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.