Background: The mutations of KCNMA1 BK-type K + channel have been identified in patients with various movement disorders. The underlying pathophysiology and corresponding therapeutics are lacking. Objectives: To report our clinical and biophysical characterizations of a novel de novo KCNMA1 variant, as well as an effective therapy for the patient's dystonia-atonia spells. Methods: Combination of phenotypic characterization, therapy, and biophysical characterization of the patient and her mutation. Results: The patient had >100 dystonia-atonia spells per day with mild cerebellar atrophy. She also had autism spectrum disorder, intellectual disability, and attention deficit hyperactivity disorder. Whole-exome sequencing identified a heterozygous de novo BK N536H mutation. Our biophysical characterization demonstrates that N536H is a gain-of-function mutation with markedly enhanced voltage-dependent activation.

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Green roofs have been utilized for urban stormwater management due to their ability to capture rainwater locally. Studies of the most common type, extensive green roofs, have demonstrated that green roofs can retain significant amounts of stormwater, but have also shown variation in seasonal performance. The purpose of this study is to determine how time of year impacts the hydrologic performance of extensive green roofs considering the covariates of antecedent dry weather period (ADWP), potential evapotranspiration (ET 0 ) and storm event size. To do this, nearly four years of monitoring data from two full-scale extensive green roofs (with differing substrate depths of 100 mm and 31 mm) are analyzed. The annual performance is then modeled using a common empirical relationship between rainfall and green roof runoff, with the addition of Julian day in one approach, ET 0 in another, and both ADWP and ET 0 in a third approach. Together the monitoring and modeling results confirm that stormwater retention is highest in warmer months, the green roofs retain more rainfall with longer ADWPs, and the seasonal variations in behavior are more pronounced for the roof with the thinner media than the roof with the deeper media. Overall, the ability of seasonal accounting to improve stormwater retention modeling is demonstrated; modification of the empirical model to include ADWP, and ET 0 improves the model R 2 from 0.944 to 0.975 for the thinner roof, and from 0.866 to 0.870 for the deeper roof. Furthermore, estimating the runoff with the empirical approach was shown to be more accurate then using a water balance model, with model R 2 of 0.944 and 0.866 compared to 0.975 and 0.866 for the thinner and deeper roof, respectively. This finding is attributed to the difficulty of accurately parameterizing the water balance model.

To protect recreational water users from waterborne pathogen exposure, it is crucial that waterways are monitored for the presence of harmful bacteria. In NYC, a citizen science campaign is monitoring waterways impacted by inputs of storm water and untreated sewage during periods of rainfall. However, the spatial and temporal scales over which the monitoring program can sample are constrained by cost and time, thus hindering the construction of databases that benefit both scientists and citizens. In this study, we first illustrate the scientific value of a citizen scientist monitoring campaign by using the data collected through the campaign to characterize the seasonal variability of sampled bacterial concentration as well as its response to antecedent rainfall. Second, we examine the efficacy of the HyServe Compact Dry ETC method, a lower cost and time-efficient alternative to the EPA-approved IDEXX Enterolert method for fecal indicator monitoring, through a paired sample comparison of IDEXX and HyServe (total of 424 paired samples). The HyServe and IDEXX methods return the same result for over 80% of the samples with regard to whether a water sample is above or below the EPA's recreational water quality criteria for a single sample of 110 enterococci per 100mL. The HyServe method classified as unsafe 90% of the 119 water samples that were classified as having unsafe enterococci concentrations by the more established IDEXX method. This study seeks to encourage other scientists to engage with citizen scientist communities and to also pursue the development of cost- and time-efficient methodologies to sample environmental variables that are not easily collected or analyzed in an automated manner.

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