It appears that patients with low back pain likely to respond to manipulation can be accurately identified before treatment.

runt is one of the genes required for establishment of the segmented body pattern of the Drosophila embryo. We have isolated DNA sequences containing this gene using P-element transposon tagging. Southern blot analyses of six different DNA rearrangements that are associated with runt mutations revealed a minimal region of 8.5-kb of DNA that was important for function. In germ line transformation experiments, a 14.5-kb segment of DNA that spanned this minimal region provided significant, although not full, levels of runt activity. The runt gene encoded a 2.6-kb poly(A)+ RNA that underwent a series of dynamic changes in its spatial and temporal patterns of accumulation during embryogenesis. The runt RNA was most abundant at the blastoderm stage when it showed the seven stripes of expression characteristic of other Drosophila pair-rule genes.

The segmented body pattern of the Drosophila embryo is established through a hierarchical network of interacting genes. At each successive step in this pathway, transcriptional regulation is used to convert coarse positional information into finer patterns of gene expression. Central to this process are the cis-regulatory regions that drive the dynamic spatial expression of the different segmentation genes. Here we describe the cis-regulatory region of the runt gene. As found for both other primary pair-rule genes, hairy and even-skipped, there are stripe-specific elements which mediate the initial regulation of runt stripes by gap genes. We did not find autoregulatory elements as described for even-skipped and fushi tarazu. The regulation of runt by other pair-rule genes is mediated by a large region, extending over 5 kb upstream and downstream of the transcription start site. This "disperse" element cannot be subdivided into functionally independent subelements or minimal elements. Such disperse elements mediating pair-rule gene interactions may have escaped detection in other segmentation genes and may involve molecular mechanisms different from those mediating regulation by gap genes.

Objective The aim of this study is to determine when during hematopoiesis Siglec-8 gets expressed, whether it is expressed on hematologic malignancies, and if there are other non-human species that express Siglec-8. Methods Siglec-8 mRNA and cell surface expression was monitored during in vitro maturation of human eosinophils and mast cells. Flow cytometry was performed on human blood and bone marrow samples, and on blood samples from dogs, baboons, and rhesus and cynomolgus monkeys. Results Siglec-8 is a late maturation marker. It is detectable on eosinophils and basophils from subjects with chronic eosinophilic leukemia, chronic myelogenous leukemia, and on malignant and non-malignant bone marrow mast cells, as well as the HMC-1.2 cell line. None of the Siglec-8 monoclonal antibodies tested recognized leukocytes from dogs, baboons, and rhesus and cynomolgus monkeys. Conclusions Siglec-8-based therapies should not target immature human leukocytes but should recognize mature and malignant eosinophils, mast cells, and basophils. So far, there is no suitable species for preclinical testing of Siglec-8 monoclonal antibodies.

Measurement of total suspended solids (TSS) and total dissolved solids (TDS) loadings in streams is often used to assess potential impacts from mining on surface water quality within a drainage basin. It has been suggested that TSS could be used as an indicator to estimate TDS loading through the use of a TDS/TSS ratio. The reliability of this approach was tested by examining empirical linear relationships between TSS and TDS loads at three locations within a mining-influenced watershed in Colorado. Predictive accuracy of the relationships was assessed using an independent source of data for the same locations, with comparisons between estimated and observed TDS loads for periods within and outside the years used to develop relationships. Evaluations were conducted over the entire flow regime and for separate periods of low- and high-flow. Improved representation of the data was achieved by incorporation of a regressed average baseflow contribution, indicating the relationship between TDS and TSS loads is not accurately represented by a simple ratio. High variability in data between locations prevents application of a basin scale relationship to all locations within that basin. Local-scale relationships developed under specific flow regimes resulted in more accurate predictions, but results suggest that factors additional to flow may need to be considered to improve predictability. Usefulness of linear empirical relationships to predict TDS load from TSS load will depend on the magnitude of uncertainty that is tolerable for a given situation.