Rapid microbial growth in a pH auxostat

Summary Feeding nutrient to meet demand dilutes slow-growing organisms from continuous culture and greatly favors rapid growth. Doubling times of roughly 10 minutes have been verified in a pH auxostat by viable cell counts and by direct counting with a Petroff-Hausser chamber. Effects of wall attachment were negligible because a fresh reactor was substituted frequently before wall growth could become established.     

Trend of Urban-Rural Disparities in Hospice Utilization in Taiwan

Aims

The palliative care has spread rapidly worldwide in the recent two decades. The development of hospice services in rural areas usually lags behind that in urban areas. The aim of our study was to investigate whether the urban-rural disparity widens in a country with a hospital-based hospice system.

Methods

From the nationwide claims database within the National Health Insurance in Taiwan, admissions to hospices from 2000 to 2006 were identified. Hospices and patients in each year were analyzed according to geographic location and residence.

Results

A total of 26,292 cancer patients had been admitted to hospices. The proportion of rural patients to all patients increased with time from 17.8% in 2000 to 25.7% in 2006. Although the numbers of beds and the utilizations in both urban and rural hospices expanded rapidly, the increasing trend in rural areas was more marked than that in urban areas. However, still two-thirds (898/1,357) of rural patients were admitted to urban hospices in 2006.

Conclusions

The gap of hospice utilizations between urban and rural areas in Taiwan did not widen with time. There was room for improvement in sufficient supply of rural hospices or efficient referral of rural patients.     

Histopathology,Molecular Identification and Antifungal Susceptibility Testing of Nannizziopsis arthrosporioides from a Captive Cuban Rock Iguana (Cyclura nubila)

Mycopathologia - Chrysosporium-related fungi, the cause of superficial and deep mycoses, are an emerging infectious disease affecting not only reptiles but also immunocompromized humans. However,...     

Redox potential control and applications in microaerobic and anaerobic fermentations

Many fermentation products are produced under microaerobic or anaerobic conditions, in which oxygen is undetectable by dissolved oxygen probe, presenting a challenge for process monitoring and control. Extracellular redox potentials that can be detected conveniently affect intracellular redox homeostasis and metabolism, and consequently control profiles of fermentation products, which provide an alternative for monitoring and control of these fermentation processes. This article reviews updated progress in the impact of redox potentials on gene expression, protein biosynthesis and metabolism as well as redox potential control strategies for more efficient production of fermentation products, taking ethanol fermentation by the yeast Saccharomyces under microaerobic conditions and butanol production by the bacterium Clostridium under anaerobic conditions as examples.     

Prediction of Protein-Protein Interactions Using Protein Signature Profiling

Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain inter- actions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis ele- gans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area un- der the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs in- creased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on aver- age 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.     

Prediction of protein-protein interactions using protein signature profiling

Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain interactions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis elegans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area under the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs increased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on average 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.     

The effect of specific growth rates on the recovery of amino acids

Three specific growth rates, 0.23, 0.45 and 0.51 h^–1, were used to cultivate Corynebacterium glutamicum in a pH-auxostat. The specific formation rates of most amino acids increased by raising the specific growth rates. The highest specific growth rate, 0.51 h^–1, favors the production of LEU; whereas the highest production yield for ALA and GLU were at = 0.23 h^–1. A correlation among specific growth rates, glucose consumption rate, and production yields of amino acids was obtained.     

Development of redox potential-controlled schemes for very-high-gravity ethanol fermentation

Fermentation redox potential reflects the momentary physiological status of organisms. Controlling redox potential can modulate the redistribution of intracellular metabolic flux to favor the formation of the desired metabolite. Accordingly, we have developed three redox potential-controlled schemes to maximize their effects on the very-high-gravity (VHG) ethanol fermentation. They are aeration-controlled scheme (ACS), glucose-controlled feeding scheme (GCFS), and combined chemostat and aeration-controlled scheme (CCACS). These schemes can maintain fermentation redox potential at a prescribed level (i.e., -50, -100, and -150 mV) by supplementing sterile air, fresh glucose media, or a combination of sterile air and fresh glucose media into a fermenter to counteract the decline of redox potential due to yeast growth. When ACS was employed, the fermentation efficiency at -150 mV is superior to the other two redox potential levels especially when the initial glucose concentration is higher than 250 g/l. The redox potential-controlled period for ACS, GCFS, and CCACS at -150 mV under the same 200 g glucose/l condition was 2.5, 21.7 and 64.6h and the corresponding fermentation efficiency was 85.9,89.3 and 92.7%, respectively.     

False positive reduction in protein-protein interaction predictions using gene ontology annotations

Background  

Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated.