Estimating the Thickness of Sea Ice Snow Cover in the Weddell Sea from Passive Microwave Brightness Temperatures

Passive microwave satellite observations have frequently been used to observe changes in sea ice cover and concentration. Comiso et al. showed that there may also be a direct relationship between the thickness of snow cover (h(sub s)) on ice and microwave emissivity at 90 GHz. Because the in situ experiment of experiment of Comiso et al. was limited to a single station, the relationship is re-examined in this paper in a more general context and using more extensive in situ microwave observations and measurements of h from the Weddell Sea 1986 and 1989 winter cruises. Good relationships were found to exist between h(sub s) sand the emissivity at 90 GHz - 10 GHz and the emissivity at 90 GHz - 18.7 GHz when the standard deviation of h(sub s) was less than 50% of the mean and when h(sub s) was less than 0.25 m. The reliance of these relationships on h(sub s) is most likely caused by the limited penetration through the snow of radiation at 90 GHz. When the algorithm was applied to the Special Sensor Microwave/Imager (SSM/I) satellite data from the Weddell Sea, the resulting mean h(sub s) agreed within 5% of the mean calculated from greater than 1400 in situ observations

Microfluidic Chips for Detecting the t(4;14) Translocation and Monitoring Disease during Treatment Using Reverse Transcriptase-Polymerase Chain Reaction Analysis of IgH-MMSET Hybrid Transcripts

Diagnosis platforms incorporating low-cost microfluidic chips enable sensitive, rapid, and accurate genetic analysis that could facilitate customized therapies tailored to match the vulnerabilities of any types of cancer. Using ex vivo cancer cells, we have detected the unique molecular signature and a chromosomal translocation in multiple myeloma. Multiple myeloma is characterized by IgH rearrangements and translocations that enable unequivocal identification of malignant cells, detected here with integrated microfluidic chips incorporating genetic amplification via reverse transcriptase-polymerase chain reaction and capillary electrophoresis. On microfluidic chips, we demonstrated accurate and versatile detection of molecular signatures in individual cancer cells, with value for monitoring response to therapy, detecting residual cancer cells that mediate relapse, and evaluating prognosis. Thus, testing for two clinically important molecular biomarkers, the IgH VDJ signature and hybrid transcripts signaling the t(4;14) chro-mosomal translocation, with predictive value in diagnosis, treatment decisions, and monitoring has been efficiently implemented on a miniaturized microfluidic system

Genome wide analysis of protein production load in Trichoderma reesei

Background: The filamentous fungus Trichoderma reesei (teleomorph Hypocrea jecorina) is a widely used industrial host organism for protein production. In industrial cultivations, it can produce over 100 g/l of extracellular protein, mostly constituting of cellulases and hemicellulases. In order to improve protein production of T. reesei the transcriptional regulation of cellulases and secretory pathway factors have been extensively studied. However, the metabolism of T. reesei under protein production conditions has not received much attention. Results: To understand the physiology and metabolism of T. reesei under protein production conditions we carried out a well-controlled bioreactor experiment with extensive analysis. We used minimal media to make the data amenable for modelling and three strain pairs to cover different protein production levels. With RNA-sequencing transcriptomics we detected the concentration of the carbon source as the most important determinant of the transcriptome. As the major transcriptional response concomitant to protein production we detected the induction of selected genes that were putatively regulated by xyr1 and were related to protein transport, amino acid metabolism and transcriptional regulation. We found novel metabolic responses such as production of glycerol and a cellotriose-like compound. We then used this cultivation data for flux balance analysis of T. reesei metabolism and demonstrate for the first time the use of genome wide stoichiometric metabolic modelling for T. reesei. We show that our model can predict protein production rate and provides novel insight into the metabolism of protein production. We also provide this unprecedented cultivation and transcriptomics data set for future modelling efforts. Conclusions: The use of stoichiometric modelling can open a novel path for the improvement of protein production in T. reesei. Based on this we propose sulphur assimilation as a major limiting factor of protein production. As an organism with exceptional protein production capabilities modelling of T. reesei can provide novel insight also to other less productive organisms.Peer reviewe