In vitro stimulation of alkaline phosphatase activity in immature embryonic chick pelvic cartilage by adenosine

Cyclic AMP content in embryonic chick pelvic cartilage increases significantly as the embryo ages from 8 to 10 d. This in ovo elevation in cyclic AMP content precedes maximal cartilage alkaline phosphatase activity by some 24 h. We studied whether this temporal relationship may be causally related, using an in vitro organ culture. Incubation of pelvic cartilage from 9- and 10-d embryos in medium containing monobutyryl cyclic AMP (BtcAMP) resulted in significant increases in alkaline phosphatase activity (220 and 66 percent, respectively) as compared to that of cartilages incubated in medium alone. This stimulation was both concentration- and time-dependent with maximal response at 0.5 mM BtcAMP and 4-h incubation, respectively. Similar incubations of cartilage in medium containing 1-methyl-3-isobutyl xanthine (MIX), 0.25 mM, also resulted in increased alkaline phosphatase activity (114 percent). However, pelvic cartilage from 11-d embryos incubated in medium containing BtcAMP or MIX showed no increase in alkaline phosphatase activity. We postulated that developmental age was the factor responsible for this difference in response and that immature cartilage (that with little or no alkaline phosphatase activity) would respond to BtcAMP whereas mature cartilage (that with significant alkaline phosphatase activity) would not. This was tested by incubating end sections of 11-d cartilage, which have little alkaline phosphatase activity, and center sections, which have significantly alkaline phosphatase activity, with both BtcAMP and MIX. Alkaline phosphatase activity in end sections (immature cartilage) was stimulated by BtcAMP and MIX, whereas it was not stimulated in the center sections. Actinomycin D and cycloheximide inhibited BtcAMP and MIX stimulation of alkaline phosphatase activity. Thus, the in vitro data suggest that cyclic AMP is a mediator for the stimulation of alkaline phosphatase activity in embryonic cartilage.     

Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration

Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site‐years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two‐stream albedo submodel provided accurate predictions of boreal needle‐leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two‐stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r²=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r²=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two‐stream albedo model and foliage nitrogen concentration. These nitrogen‐based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.     

Edelfosine-induced metabolic changes in cancer cells that precede the overproduction of reactive oxygen species and apoptosis

Background  

Metabolic flux profiling based on the analysis of distribution of stable isotope tracer in metabolites is an important method widely used in cancer research to understand the regulation of cell metabolism and elaborate new therapeutic strategies. Recently, we developed software Isodyn, which extends the methodology of kinetic modeling to the analysis of isotopic isomer distribution for the evaluation of cellular metabolic flux profile under relevant conditions. This tool can be applied to reveal the metabolic effect of proapoptotic drug edelfosine in leukemia Jurkat cell line, uncovering the mechanisms of induction of apoptosis in cancer cells.     

Effects of aerobic exercise therapy and cognitive behavioural therapy on functioning and quality of life in amyotrophic lateral sclerosis: protocol of the FACTS-2-ALS trial

Background

Neuropathic pain must be correctly diagnosed for optimal treatment. The questionnaire named Neuropathic Pain Symptom Inventory (NPSI) was developed in its original French version to evaluate the different symptoms of neuropathic pain. We hypothesized that the NPSI might also be used to differentiate neuropathic from non-neuropathic pain.

Methods

We translated the NPSI into German using a standard forward-backward translation and administered it in a case-control design to patients with neuropathic (n = 68) and non-neuropathic pain (headache and osteoarthritis, n = 169) to validate it and to analyze its discriminant properties, its sensitivity to change, and to detect neuropathic pain subgroups with distinct profiles.

Results

Using a sum score (the NPSI-G score), we found sensitivity to change (r between 0.37 and 0.5 for pain items of the graded chronic pain scale) and could distinguish between neuropathic and other pain on a group basis, but not for individual patients. Post hoc development of a discriminant score with optimized diagnostic properties to distinguish neuropathic pain from non-neuropathic pain resulted in an instrument with high sensitivity (91%) and acceptable specificity (70%). We detected six different pain profiles in the patient group with neuropathic pain; three profiles were found to be distinct.

Conclusions

The NPSI-G potentially combines the properties of a diagnostic tool and an instrument to identify subtypes of neuropathic pain.     

Comparative analysis of multiple protein-sequence alignment methods [published erratum appears in Mol Biol Evol 1994 Sep;11(5):811]

We have analyzed a total of 12 different global and local multiple protein-sequence alignment methods. The purpose of this study is to evaluate each method's ability to correctly identify the ordered series of motifs found among all members of a given protein family. Four phylogenetically distributed sets of sequences from the hemoglobin, kinase, aspartic acid protease, and ribonuclease H protein families were used to test the methods. The performance of all 12 methods was affected by (1) the number of sequences in the test sets, (2) the degree of similarity among the sequences, and (3) the number of indels required to produce a multiple alignment. Global methods generally performed better than local methods in the detection of motif patterns.      

From microbial gene essentiality to novel antimicrobial drug targets

Background

Bacterial respiratory tract infections, mainly caused by Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis are among the leading causes of global mortality and morbidity. Increased resistance of these pathogens to existing antibiotics necessitates the search for novel targets to develop potent antimicrobials.

Result

Here, we report a proof of concept study for the reliable identification of potential drug targets in these human respiratory pathogens by combining high-density transposon mutagenesis, high-throughput sequencing, and integrative genomics. Approximately 20% of all genes in these three species were essential for growth and viability, including 128 essential and conserved genes, part of 47 metabolic pathways. By comparing these essential genes to the human genome, and a database of genes from commensal human gut microbiota, we identified and excluded potential drug targets in respiratory tract pathogens that will have off-target effects in the host, or disrupt the natural host microbiota. We propose 249 potential drug targets, 67 of which are targets for 75 FDA-approved antimicrobials and 35 other researched small molecule inhibitors. Two out of four selected novel targets were experimentally validated, proofing the concept.

Conclusion

Here we have pioneered an attempt in systematically combining the power of high-density transposon mutagenesis, high-throughput sequencing, and integrative genomics to discover potential drug targets at genome-scale. By circumventing the time-consuming and expensive laboratory screens traditionally used to select potential drug targets, our approach provides an attractive alternative that could accelerate the much needed discovery of novel antimicrobials.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-958) contains supplementary material, which is available to authorized users.