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Purpose Admission infarct core lesion size is an important determinant of management and outcome in acute (<9 hrs) stroke. Our purpose was to: (1) determine the optimal CT perfusion (CTP) parameter to define infarct core using various post-processing platforms, and (2) establish the degree of variability in threshold values between these different platforms. Methods We evaluated 48 consecutive cases with vessel occlusion and admission CTP and DWI within 3 hours of each other. CTP was acquired with a “second-generation” 66-second biphasic cine protocol, and post-processed using “standard” (from two vendors, “A-std” and “B-std”) and “delay-corrected” (from one vendor, “A-dc”) commercial software. ROC curve analysis was performed comparing each CTP parameter - both absolute and normalized to the contralateral uninvolved hemisphere - between infarcted and non-infarcted regions, as defined by co-registered DWI. Results Cerebral blood flow (CBF) had the highest accuracy (ROC “area under curve”, AUC), for all three platforms (p<0.01). The maximal AUC's for each parameter were: absolute CBF 0.88, CBV 0.81, and MTT 0.82, and relative CBF 0.88, CBV 0.83, and MTT 0.82. Optimal ROC operating point thresholds varied significantly between different platforms (Friedman test, p<0.01). Conclusion Admission absolute and normalized “second-generation” cine acquired CT-CBF lesion volumes correlate more closely with DWI defined infarct core than do those of CT-CBV or MTT. Although limited availability of DWI for some patients creates impetus to develop alternative methods of estimating core, the marked variability in quantification amongst different post-processing software limits generalizability of parameter map thresholds between platforms.

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Climate change contributes to drought stress and subsequently affects crop growth, development, and yield. The microbial community, such as fungi and bacteria in the rhizosphere, is of special importance to plant productivity. In this study, soil collected from a cotton research field was used to grow cotton plants (Gossypium hirsutum cv. Jin668) under controlled environment conditions. Drought stress was applied at flowering stage, while control plants were regularly watered. At the same time, the soil without plants was also subjected to drought, while control pots were regularly watered. The soil was collected in sterilized tubes and microbial DNA was isolated and high-throughput sequencing of 16S rRNA genes was carried out. The alpha diversity of bacteria community significantly increased in the soil with cotton plants compared to the soil without cotton plants. Taxonomic analysis revealed that the bacterial community structure of the cotton rhizosphere predominantly consisted of the phyla Proteobacteria (31.7%), Actinobacteria (29.6%), Gemmatimonadetes (9.8%), Chloroflexi (9%), Cyanobacteria (5.6%), and Acidobacteria. In the drought-treated rhizosphere, Chloroflexi and Gemmatimonadetes were the dominant phyla. This study reveals that the cotton rhizosphere has a rich pool of bacterial communities even under drought stress, and which may improve drought tolerance in plants. These data will underpin future improvement of drought tolerance of cotton via the soil microbial community.