Predictive Factors of Late Venous Aortocoronary Graft Failure: Ultrastructural Studies

Background

Venous aortocoronary graft arterialization may precede a preterm occlusion in some coronary artery bypass grafting (CABG) patients. The aim of the present study was to identify ultrastructural variations in the saphenous vein wall that may have an impact on the development of venous graft disease in CABG patients.

Methods

The study involved 365 consecutive patients with a mean age of 62.9±9.4 years who underwent isolated CABG. The thickness and area of the whole venous wall, the tunica intima, the tunica media and the adventitia and the number and shape (length, thickness and length/thickness ratio) of the nuclei in the medial smooth muscle cells nuclei in the distal saphenous vein segments were evaluated by ultrastructural studies. Patients were followed up for 41 to 50 months (mean 45.1±5.1). Saphenous vein graft patency was assessed by follow-up coronary angiography. Logistic regression models were used to identify independent risk factors for late graft failure.

Results

In 71 patients significant lesions in the saphenous vein grafts were observed. The whole venous wall thickness (437.5 µm vs. 405.5 µm), tunica media thickness (257.2 µm vs. 211.5 µm), whole venous wall area (2.23 mm² vs. 2.02 mm²) and tunica media area (1.09 mm² vs. 0.93 mm²) were significantly larger for this group of patients than for those without graft disease. In the latter group more elongated smooth muscle cell nuclei (higher length/thickness ratio) were found in the tunica media of the saphenous vein segments. Thickening of the saphenous vein tunica media and chunky smooth muscle cell nuclei were identified as independent risk factors for graft disease development.

Conclusions

Saphenous vein tunica media hypertrophy (resulting in wall thickening) and chunky smooth muscle cell nuclei might predict the development of venous graft disease.     

Detoxification of Lignocellulose Hydrolysates: Biochemical and Metabolic Engineering Toward White Biotechnology

Chemical hydrolysis of lignocellulosic biomass (LB) produces a number of inhibitors in addition to sugars. These inhibitors include lignin-derived phenolics, carbohydrate-derived furans, and weak acids that have shown a marked effect on the productivities of various metabolites and the growth of biocatalysts in the fermentative reaction. In the past, a number of physicochemical and biological approaches have been proposed to overcome these fermentation inhibitors, including modified fermentative strategies. Additionally, the timely intervention of genetic engineering has provided an impetus to develop suitable technologies for the detoxification of lignocellulosics in biorefineries. However, the improvements in detoxification strategies for lignocellulose hydrolysates have resulted in significant loss of sugars after detoxification. Hydrolysis of myco-LB (LB after fungal pretreatment) has been recognized as a promising approach to avoid fermentation inhibitors and improve total sugar recovery. Biotechnological inventions have also made it possible to widen the range of suitable biocatalysts for biorefineries by microbial-routed induction of enzymatic expression for the elimination of inhibitors, eventually improving ethanol production from acid hydrolysates. This article aims to highlight the strategies that have been adopted to detoxify lignocellulosic hydrolysates and their effects on the chemical composition of the hydrolysates to improve the fermentability of lignocellulosics. In addition, genetic manipulation could widen the availability and variety of substrates and modify the metabolic routes to produce bioethanol or other value-added compounds in an efficient manner.     

The Embedding Problem for Markov Models of Nucleotide Substitution

Continuous-time Markov processes are often used to model the complex natural phenomenon of sequence evolution. To make the process of sequence evolution tractable, simplifying assumptions are often made about the sequence properties and the underlying process. The validity of one such assumption, time-homogeneity, has never been explored. Violations of this assumption can be found by identifying non-embeddability. A process is non-embeddable if it can not be embedded in a continuous time-homogeneous Markov process. In this study, non-embeddability was demonstrated to exist when modelling sequence evolution with Markov models. Evidence of non-embeddability was found primarily at the third codon position, possibly resulting from changes in mutation rate over time. Outgroup edges and those with a deeper time depth were found to have an increased probability of the underlying process being non-embeddable. Overall, low levels of non-embeddability were detected when examining individual edges of triads across a diverse set of alignments. Subsequent phylogenetic reconstruction analyses demonstrated that non-embeddability could impact on the correct prediction of phylogenies, but at extremely low levels. Despite the existence of non-embeddability, there is minimal evidence of violations of the local time homogeneity assumption and consequently the impact is likely to be minor.     

Studies on seed-borne fungi of wheat in seed health testing programme

Seed mycoflora associated with wheat was studied on different media with a particular reference to Blotter and potato dextrose agar (PDA) procedures of ISTA. Seed-borne fungi, viz. Fusarium moniliforme, Rhizopus spp., Mucor spp., Alternaria alternata, Aspergillus niger, Aspergillus flavus, Curvularia lunata, Drechslera spp, Alternaria spp. and Penicillium spp., were isolated from the variety HD264. Blotter method was found to be the best media for the isolation of mycoflora whether borne externally or internally. Total number and frequency of occurrence of fungi were recorded. The effect of seed treatment with different chemicals and eco-friendly botanicals was analysed on germination, and growth, better percentage of seed germination and reduction in fungal pathogen were due to biochemical seed treatment.     

Comparing vector–host and SIR models for dengue transmission

Various simple mathematical models have been used to investigate dengue transmission. Some of these models explicitly model the mosquito population, while others model the mosquitoes implicitly in the transmission term. We study the impact of modeling assumptions on the dynamics of dengue in Thailand by fitting dengue hemorrhagic fever (DHF) data to simple vector–host and SIR models using Bayesian Markov chain Monte Carlo estimation. The parameter estimates obtained for both models were consistent with previous studies. Most importantly, model selection found that the SIR model was substantially better than the vector–host model for the DHF data from Thailand. Therefore, explicitly incorporating the mosquito population may not be necessary in modeling dengue transmission for some populations.     

Divergent Sequence Tunes Ligand Sensitivity in Phospholipid-regulated Hormone Receptors

The members of the NR5A subfamily of nuclear receptors (NRs) are important regulators of pluripotency, lipid and glucose homeostasis, and steroidogenesis. Liver receptor homologue 1 (LRH-1; NR5A2) and steroidogenic factor 1 (SF-1; NR5A1) have therapeutic potential for the treatment of metabolic and neoplastic disease; however, a poor understanding of their ligand regulation has hampered the pursuit of these proteins as pharmaceutical targets. In this study, we dissect how sequence variation among LRH-1 orthologs affects phospholipid (PL) binding and regulation. Both human LRH-1 (hLRH-1) and mouse LRH-1 (mLRH-1) respond to newly discovered medium chain PL agonists to modulate lipid and glucose homeostasis. These PLs activate hLRH-1 by altering receptor dynamics in a newly identified alternate activation function region. Mouse and Drosophila orthologs contain divergent sequences in this region potentially altering PL-driven activation. Structural evidence suggests that these sequence differences in mLRH-1 and Drosophila FTZ-f1 (dmFTZ-f1) confer at least partial ligand independence, making them poor models for hLRH-1 studies; however, the mechanisms of ligand independence remain untested. We show using structural and biochemical methods that the recent evolutionary divergence of the mLRH-1 stabilizes the active conformation in the absence of ligand, yet does not abrogate PL-dependent activation. We also show by mass spectrometry and biochemical assays that FTZ-f1 is incapable of PL binding. This work provides a structural mechanism for the differential tuning of PL sensitivity in NR5A orthologs and supports the use of mice as viable therapeutic models for LRH-1-dependent diseases.     

The Limitations of an Exclusively Colloidal View of Protein Solution Hydrodynamics and Rheology

Proteins are complex macromolecules with dynamic conformations. They are charged like colloids, but unlike colloids, charge is heterogeneously distributed on their surfaces. Here we overturn entrenched doctrine that uncritically treats bovine serum albumin (BSA) as a colloidal hard sphere by elucidating the complex pH and surface hydration-dependence of solution viscosity. We measure the infinite shear viscosity of buffered BSA solutions in a parameter space chosen to tune competing long-range repulsions and short-range attractions (2 mg/mL ≤ [BSA] ≤ 500 mg/mL and 3.0 ≤ pH ≤ 7.4). We account for surface hydration through partial specific volume to define volume fraction and determine that the pH-dependent BSA intrinsic viscosity never equals the classical hard sphere result (2.5). We attempt to fit our data to the colloidal rheology models of Russel, Saville, and Schowalter (RSS) and Krieger-Dougherty (KD), which are each routinely and successfully applied to uniformly charged suspensions and to hard-sphere suspensions, respectively. We discover that the RSS model accurately describes our data at pH 3.0, 4.0, and 5.0, but fails at pH 6.0 and 7.4, due to steeply rising solution viscosity at high concentration. When we implement the KD model with the maximum packing volume fraction as the sole floating parameter while holding the intrinsic viscosity constant, we conclude that the model only succeeds at pH 6.0 and 7.4. These findings lead us to define a minimal framework for models of crowded protein solution viscosity wherein critical protein-specific attributes (namely, conformation, surface hydration, and surface charge distribution) are addressed.     

The Limitations of an Exclusively Colloidal View of Protein Solution Hydrodynamics and Rheology

Proteins are complex macromolecules with dynamic conformations. They are charged like colloids, but unlike colloids, charge is heterogeneously distributed on their surfaces. Here we overturn entrenched doctrine that uncritically treats bovine serum albumin (BSA) as a colloidal hard sphere by elucidating the complex pH and surface hydration-dependence of solution viscosity. We measure the infinite shear viscosity of buffered BSA solutions in a parameter space chosen to tune competing long-range repulsions and short-range attractions (2 mg/mL ≤ [BSA] ≤ 500 mg/mL and 3.0 ≤ pH ≤ 7.4). We account for surface hydration through partial specific volume to define volume fraction and determine that the pH-dependent BSA intrinsic viscosity never equals the classical hard sphere result (2.5). We attempt to fit our data to the colloidal rheology models of Russel, Saville, and Schowalter (RSS) and Krieger-Dougherty (KD), which are each routinely and successfully applied to uniformly charged suspensions and to hard-sphere suspensions, respectively. We discover that the RSS model accurately describes our data at pH 3.0, 4.0, and 5.0, but fails at pH 6.0 and 7.4, due to steeply rising solution viscosity at high concentration. When we implement the KD model with the maximum packing volume fraction as the sole floating parameter while holding the intrinsic viscosity constant, we conclude that the model only succeeds at pH 6.0 and 7.4. These findings lead us to define a minimal framework for models of crowded protein solution viscosity wherein critical protein-specific attributes (namely, conformation, surface hydration, and surface charge distribution) are addressed.     

LOV‐domain photoreceptor,encoded in a genomic island,attenuates the virulence of Pseudomonas syringae in light‐exposed Arabidopsis leaves

In Arabidopsis thaliana, light signals modulate the defences against bacteria. Here we show that light perceived by the LOV domain‐regulated two‐component system (Pst–Lov) of Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) modulates virulence against A. thaliana. Bioinformatic analysis and the existence of an episomal circular intermediate indicate that the locus encoding Pst–Lov is present in an active genomic island acquired by horizontal transfer. Strains mutated at Pst–Lov showed enhanced growth on minimal medium and in leaves of A. thaliana exposed to light, but not in leaves incubated in darkness or buried in the soil. Pst–Lov repressed the expression of principal and alternative sigma factor genes and their downstream targets linked to bacterial growth, virulence and quorum sensing, in a strictly light‐dependent manner. We propose that the function of Pst–Lov is to distinguish between soil (dark) and leaf (light) environments, attenuating the damage caused to host tissues while releasing growth out of the host. Therefore, in addition to its direct actions via photosynthesis and plant sensory receptors, light may affect plants indirectly via the sensory receptors of bacterial pathogens.