THE EFFECT OF CHRONIC DORSAL ROOT SECTION ON THE CONCENTRATION OF FREE AMINO ACIDS IN THE RABBIT SPINAL CORD

Abstract— Amino acids may be involved in primary afferent excitatory neurotransmission in the spinal cord. To test this possibility the effect of chronic dorsal root section on amino acid levels of the rabbit spinal cord has been investigated. Dorsal roots L6-S2 were sectioned under anaesthesia. Control animals were subjected to similar surgical procedures but the dorsal roots were left intact. Electromyogram recordings taken 6 days after surgery confirmed the absence of sensory input to the lower lumbosacral cord of dorsal root sectioned animals although motor function was retained. In contrast to this control animals exhibited normal reflex activity. The spinal cord was removed from each animal and extracted in trichloracetic acid for subsequent analysts of amino acids on an autoanalyser. Sections of cord were retained for histological determination of neuronal degeneration. Comparison of amino acid levels in dorsal root sectioned and control animals revealed that the only excitatory amino acid to be significantly reduced by dorsal root section wasaspartic acid (–50 percent X although glutamic acid was also reduced (– 30 per cent). Two inhibitory amino acids, cystathionine and GABA, were also significantly depleted (– 50 and - 35 per cent). The possible involvement of these amino acids in spinal cord neurotransmission is discussed.     

Multiple independent evolutionary solutions to core histone gene regulation

Background  

Core histone genes are periodically expressed along the cell cycle and peak during S phase. Core histone gene expression is deeply evolutionarily conserved from the yeast Saccharomyces cerevisiae to human.     

Metabolic network reconstruction and flux variability analysis of storage synthesis in developing oilseed rape (Brassica napus L.) embryos

Computational simulation of large‐scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganic nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10–11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one‐third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty‐seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.     

Bayesian spatial modeling of moose count data: increasing estimator efficiency and exploring ecological hypotheses

Moose management throughout much of Alaska and Canada relies on aerial count data, which are commonly collected using the geospatial population estimator (GSPE) protocol. The GSPE uses a model-based analytical approach and finite-population block kriging to estimate abundance from a collection of sampled survey units. Widespread implementation and well-documented analytical software have resulted in reliable estimates of moose abundance, density, and composition across a large proportion of their range. Analysis is conducted almost exclusively using the GSPE software, which fits a fixed model structure to data collected within a single year. The downside of this approach to analysis is that the fixed model structure is inefficient for estimation, leading to more field effort than would otherwise be necessary to achieve a desired level of estimator precision. We developed a more easily modified and flexible Bayesian spatial general additive model approach (BSG) that accommodates spatial and temporal covariates (e.g., habitat characteristics, trend), multiple survey events, prior information, and incomplete detection. Using a series of 6 GSPE surveys conducted in Yukon-Charley Rivers National Preserve, Alaska, USA, from 2003–2019, we established the equivalence of the 2 approaches under similar model structures. We then extended the BSG to demonstrate how a more comprehensive approach to analysis can affect estimator precision and be used to assess ecological relationships. The precision of annual abundance estimators from the BSG were improved by an average of 43% over those based on the standard GSPE analysis, highlighting the very real costs of assuming a fixed (i.e., suboptimal) model structure. The population increased at a rate of 2.3%/year (95% CrI = 0.8–3.8%), and the increase was largely explained by a parallel increase in wildfire extent (i.e., high quality moose habitat). These results suggest that our approach could be used to increase estimator efficiency or decrease future survey costs without any modifications to the basic protocol. While modification of the GSPE software is possible, practitioners may find the BSG approach more convenient for quickly developing model structures for a particular application, thereby allowing them to extract more information from existing and future datasets.     

Localization of the human NCAM gene to band q23 of chromosome 11: the third gene coding for a cell interaction molecule mapped to the distal portion of the long arm of chromosome 11

cDNA clones containing sequences coding for the murine neural cell adhesion molecule (N-CAM) were used in Southern hybridizations on human genomic DNA and demonstrated approximately 90% homology between human and murine NCAM genes. In situ hybridization with one of these clones was performed on human metaphase chromosomes and allowed the localization of the human NCAM gene to band q23 of chromosome 11. The genes for two other cell surface molecules believed to be involved in cell-cell interactions, Thy-1 and the delta chain of the T3-T cell receptor complex, have recently been localized to the same region of chromosome 11 in man. Moreover, this region of the human chromosome 11 appears to be syntenic to a region of murine chromosome 9 that also contains the staggerer locus: staggerer mice show abnormal neurological features which may be related to abnormalities in the conversion of the embryonic to the adult forms of the N-CAM molecule.