Cell size, density, and nutrient dependency of unicellular algal gravitational sinking velocities.

Eukaryotic phytoplankton, also known as algae, form the basis of marine food webs and drive marine carbon sequestration. Algae must regulate their motility and gravitational sinking to balance access to light at the surface and nutrients in deeper layers. However, the regulation of gravitational sinking remains largely unknown, especially in motile species. Here, we quantify gravitational sinking velocities according to Stokes' law in diverse clades of unicellular marine microalgae to reveal the cell size, density, and nutrient dependency of sinking velocities. We identify a motile algal species, Tetraselmis sp., that sinks faster when starved due to a photosynthesis-driven accumulation of carbohydrates and a loss of intracellular water, both of which increase cell density. Moreover, the regulation of cell sinking velocities is connected to proliferation and can respond to multiple nutrients. Overall, our work elucidates how cell size and density respond to environmental conditions to drive the vertical migration of motile algae.

A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior.

Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.

A microfluidic platform for high-purity cell free DNA extraction from plasma for non-invasive prenatal testing.

OBJECTIVES: Increase the yield and purity of cell-free DNA (cfDNA) extracted from plasma for non-invasive prenatal testing (NIPT) as inefficiencies in this extraction and purification can dramatically affect the sensitivity and specificity of the test. METHODS: This work integrates cfDNA extraction from plasma with a microfluidic chip platform by combining magnetic bead-based extraction and electroosmotic flow on the microfluidic chip. Various wash buffers and voltage conditions were simulated using COMSOL Multiphysics Modeling and tested experimentally. RESULTS: When performing the first wash step of this assay on the microfluidic chip with 300 V applied across the channel there was a six-fold increase in the A260 /A230 ratio showing a significant improvement (p value 0.0005) in the purity of the extracted sample all while maintaining a yield of 68.19%. These values are critical as a high yield results in more sample to analyze and an increase in A260 /A230 ratio corresponds to a decrease in salt contaminants such as guanidinium thiocyanate which can interfere with downstream processes during DNA library preparation and potentially hinder the NIPT screening results. CONCLUSIONS: This technique has the potential to improve NIPT outcomes and other clinically relevant workflows that use cfDNA as an analyte such as cancer detection.

A model and predictions for COVID-19 considering population behavior and vaccination.

The effect of vaccination coupled with the behavioral response of the population is not well understood. Our model incorporates two important dynamically varying population behaviors: level of caution and sense of safety. Level of caution increases with infectious cases, while an increasing sense of safety with increased vaccination lowers precautions. Our model accurately reproduces the complete time history of COVID-19 infections for various regions of the United States. We propose a parameter [Formula: see text] as a direct measure of a population's caution against an infectious disease that can be obtained from the infectious cases. The model provides quantitative measures of highest disease transmission rate, effective transmission rate, and cautionary behavior. We predict future COVID-19 trends in the United States accounting for vaccine rollout and behavior. Although a high rate of vaccination is critical to quickly ending the pandemic, a return towards pre-pandemic social behavior due to increased sense of safety during vaccine deployment can cause an alarming surge in infections. Our results predict that at the current rate of vaccination, the new infection cases for COVID-19 in the United States will approach zero by August 2021. This model can be used for other regions and for future epidemics and pandemics.

Microfluidic continuous flow synthesis of functional hollow spherical silica with hierarchical sponge-like large porous shell.

Microfluidics brings unique opportunities for engineering micro-/nanomaterials with well-controlled physicochemical properties. Herein, using a miniaturized multi-run spiral-shaped microreactor, we develop a flow synthesis strategy to continuously produce hollow spherical silica (HSS) with hierarchical sponge-like pore sizes ranging from several nanometers to over one hundred nanometers. The formation of HSS is realized by mixing two reactant flows, one containing cetyltrimethylammonium bromide (CTAB) and diluted ammonia and the other 1,3,5-trimethylbenzene (TMB) and diluted tetraethyl orthosilicate (TEOS), at a flow rate as high as 5 mL/min. The effect of the reactant concentration and the flow rate on the structural change of the resultant materials is examined. Functional small-sized nanoparticles (magnetic nanoparticle, quantum dot, and silver nanoparticle) can be separately assembled into HSS and high molecular weight protein (bovine serum albumin) can be successfully loaded into HSS and delivered into cancer cells afterward, making them promising in the fields of separation and purification, bioimaging, catalysis, and theranostics.