Predicting Seasonal and Spatial Onset of cHABs in Polymictic Reservoirs

Cyanobacterial Harmful Algal Blooms (cHABS) are a naturally occurring but increasingly common phenomenon due to anthropogenic activities and climate change. cHABs reduce water quality by forming unsightly surface scums and sometimes producing algal matts on the surface of water bodies, reduce water quality, and in high densities can produce cyanotoxins that can harm humans, pets, and wildlife. Ecological forecasting of cHABs has proved elusive in part because the in-situ fluorometric methods currently employed for detecting cyanobacteria cells are subject to varied interference as water quality and the biotic community changes. In this study we seek to develop an ecological forecasting capability that overcomes both temporally and spatially derived in-situ fluorometric interferences. We obtained water samples at 26 polymictic reservoirs over a two-day period and at five polymictic reservoirs weekly during the summer of 2019. Collected water samples are being used for quantitative analysis of cyanobacterial cell densities by means of qPCR. We plan a data reduction technique (e.g. PCA, VIF screening, elastic-net regression as appropriate) followed by multivariate predictive model (e.g. multiple regression, ordination, discriminant analysis as appropriate)

An automated image analysis method for the measurement of neutrophil alkaline phosphatase in the prenatal screening of Down syndrome

Objectives: (1) To develop an image analysis method for the measurement of neutrophil alkaline phosphatase (NAP); (2) To establish a correlation of urea-resistant fraction of NAP (URNAP)/NAP scoring between the manual and automated methods, and (3) to assess the value of URNAP/NAP in the prenatal screening of Down syndrome. Study Design: Slides from 15 unaffected controls were blindly scored by both methods. The Pearson test was used for correlation analysis. Slides from 15 Down syndrome pregnancies and 25 unaffected controls were scored manually. Results: A coefficient r = 0.93 was obtained comparing the URNAP/NAP scores generated by the two methods, Average time for scoring by the automated method was 8 min. The median URNAP/NAP values for Down syndrome and unaffected controls were 112/86.1 and 51/51.5, respectively. Conclusions: Scores obtained by both methods highly correlate. Automated scoring is threefold faster, Down syndrome cases have higher URNAP/NAP scores compared to unaffected controls, which suggests that URNAP/NAP is an extremely useful marker for mid-trimester prenatal screening