Ammonium release by zooplankton in suspensions of heat-killed algae and an evaluation of the flow-cell method

The maximum excretion rate of NH₄ (39 nmol mg dry wt^–1h^–1) was directly measured for Daphnia pulex by measuringNH₄ accumulation in bottles containing D. pulex and dense, satiatingsuspensions of heat-killed algae. Ammonium release rates inthe algal suspensions were compared to those of individual animalsremoved from the suspension and placed in flow cells. Ammoniumrelease rate, R (nmol mg dry wt^–1 h^–1). in the flowcell decreased very rapidly with time, t (min), after removalaccording to the relation R = 26 + 25e^–0.16t. Ammoniumexcretion obtained by the flow cell method after extrapolationto time zero was not significantly different from that obtainedin the bottles. The considerable experiment-to-experiment variationin NH₄ excretion was in large part correlated (r² = 0.73) withthe feeding rate on the algae.     

Design, synthesis, and testing of an 6-O-linked series of benzimidazole based inhibitors of CDK5/p25

Alzheimer’s disease (AD) is a progressive neurodegenerative disease resulting in cognitive and behavioral impairment. The two classic pathological hallmarks of AD include extraneuronal deposition of amyloid ?? (A??) and intraneuronal formation of neurofibrillary tangles (NFTs). NFTs contain hyperphosphorylated tau. Tau is the major microtubule-associated protein in neurons and stabilizes microtubules (MTs). Cyclin dependent kinase 5 (CDK5), when activated by the regulatory binding protein p25, phosphorylates tau at a number of proline-directed serine/threonine residues, resulting in formation of phosphorylated tau as paired helical filaments (PHFs) then in subsequent deposition of PHFs as NFTs. Beginning with the structure of Roscovitine, a moderately selective CDK5 inhibitor, we sought to conduct structural modifications to increase inhibitory potency of CDK5 and increase selectivity over a similar enzyme, cyclin dependent kinase 2 (CDK2). The design, synthesis, and testing of a series of 1-isopropyl-4-aminobenzyl-6-ether-linked benzimidazoles is presented.     

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples

Objectives

There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.

Methods

This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit^™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.

Results

Results are presented at family and genus level. The Kullback-Leibler divergence (D_KL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average D_KL while the V4 gave the lowest (best) average D_KL. In addition to having a high D_KL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.

Conclusions

The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.     

Validating English- and Spanish-language patient-reported outcome measures in underserved patients with rheumatic disease

Introduction  

Rheumatic diseases are among the most common and debilitating health problems in the United States. These diseases are chronic, can result in severe decrements of physical and psychosocial functioning and affect patients' overall quality of life. A consensus regarding the best patient outcomes to be measured in randomized, controlled trials and prospective natural history studies is essential to provide best estimates of efficacy and safety of interventions across diverse patient populations.     

A dengue outbreak in a rural community in Northern Coastal Ecuador: An analysis using unmanned aerial vehicle mapping

Dengue is recognized as a major health issue in large urban tropical cities but is also observed in rural areas. In these environments, physical characteristics of the landscape and sociodemographic factors may influence vector populations at small geographic scales, while prior immunity to the four dengue virus serotypes affects incidence. In 2019, a rural northwestern Ecuadorian community, only accessible by river, experienced a dengue outbreak. The village is 2–3 hours by boat away from the nearest population center and comprises both Afro-Ecuadorian and Indigenous Chachi households. We used multiple data streams to examine spatial risk factors associated with this outbreak, combining maps collected with an unmanned aerial vehicle (UAV), an entomological survey, a community census, and active surveillance of febrile cases. We mapped visible water containers seen in UAV images and calculated both the green-red vegetation index (GRVI) and household proximity to public spaces like schools and meeting areas. To identify risk factors for symptomatic dengue infection, we used mixed-effect logistic regression models to account for the clustering of symptomatic cases within households. We identified 55 dengue cases (9.5% of the population) from 37 households. Cases peaked in June and continued through October. Rural spatial organization helped to explain disease risk. Afro-Ecuadorian (versus Indigenous) households experience more symptomatic dengue (OR = 3.0, 95%CI: 1.3, 6.9). This association was explained by differences in vegetation (measured by GRVI) near the household (OR: 11.3 95% 0.38, 38.0) and proximity to the football field (OR: 13.9, 95% 4.0, 48.4). The integration of UAV mapping with other data streams adds to our understanding of these dynamics.