1-D imaging cytometry: statistical assays for immunotherapy drug screening

Modern cancer immunotherapy involves the conditioning of endogenous T cells to fight cancerous bodies that have managed to resist or avoid detection. Recently approved antibody drugs target the immune checkpoint pathway in T cells to prevent their tolerance to cancer antigens. There exists a compelling need, especially in the drug discovery world, to develop better assays for screening and to study the underlying mechanisms of these new antibody drugs. The core motivation of my work is to develop a primary cell assay for the immune checkpoint pathway using 1-D imaging cytometry. The assay is focused on high throughput and high content screening. It takes advantage of our novel 1-D imaging cytometer platform. The assay is designed to artificially induce anergy in primary human T cells and systemically study their drug response. An automated statistical method quantifies the functional phenotypes of both healthy and anergic T cells into a single descriptive readout. Reducing localization of biomarkers into a single ‘activity score’ readout has many advantages for drug screening and characterization. Additional assays were developed to study T cell activation dynamics and other signaling events during the immune checkpoint pathway. Our 1-D instrument leverages both the high throughput aspects of traditional flow cytometry and the high spatial content of 2-D imaging cytometers. The PMC data analysis emphasizes an unbiased approach to analyze flow cytometry data, which eliminates the subjective manual gating of current cytometric methods. This is crucial to developing more accurate and reliable assays with minimal supervision and need for expert operators. The high-throughput and high-content capabilities presented enable new types of assays previously not possible with human primary T cells. Adoption of physiological relevant primary cell assays has potential to revolutionize large-scale drug screening and future applications in personalized medicine

Macroevolutionary Patterns In The Evolutionary Radiation Of Archosaurs (Tetrapoda: Diapsida)

The rise of archosaurs during the Triassic and Early Jurassic has been treated as a classic example of an evolutionary radiation in the fossil record. This paper reviews published studies and provides new data on archosaur lineage origination, diversity and lineage evolution, morphological disparity, rates of morphological character change, and faunal abundance during the Triassic–Early Jurassic. The fundamental archosaur lineages originated early in the Triassic, in concert with the highest rates of character change. Disparity and diversity peaked later, during the Norian, but the most significant increase in disparity occurred before maximum diversity. Archosaurs were rare components of Early–Middle Triassic faunas, but were more abundant in the Late Triassic and pre-eminent globally by the Early Jurassic. The archosaur radiation was a drawn-out event and major components such as diversity and abundance were discordant from each other. Crurotarsans (crocodile-line archosaurs) were more disparate, diverse, and abundant than avemetatarsalians (bird-line archosaurs, including dinosaurs) during the Late Triassic, but these roles were reversed in the Early Jurassic. There is no strong evidence that dinosaurs outcompeted or gradually eclipsed crurotarsans during the Late Triassic. Instead, crurotarsan diversity decreased precipitously by the end-Triassic extinction, which helped usher in the age of dinosaurian dominance

Can Third-Party Sellers Benefit from a Platform’s Entry to the Market?

Because of the informational advantage of online marketplaces (i.e., platforms), it is a common belief that a platform’s market entry will be detrimental to third-party sellers who sell similar products on the platform. To examine the validity of this belief, we conduct an exploratory analysis using the sales data for a single product category provided by JD.com for the month of March 2018. Our analysis reveals an unexpected result. Upon the platform’s entry, third-party sellers who sell similar products can afford to charge a higher price, obtain a higher demand, and earn a higher profit. To provide a plausible explanation for this unexpected exploratory result, we develop a duopoly model that incorporates the changing competitive dynamic before and after the platform’s entry. Specifically, before entry, the platform earns a commission (based on the seller’s revenue), whereas the seller sets its retail price as a monopoly. After entry, the platform earns a profit generated by its direct sales in addition to the commission from the seller. In addition, the seller and the platform operate in a duopoly and engage in a sequential game. By examining the equilibrium outcomes associated with this sequential game, we identify conditions under which the platform’s entry can create a win-win situation for both parties. Specifically, these conditions hold when the platform’s market potential is moderate and when the platform’s entry creates a sufficiently high spillover effect on the seller, providing a plausible explanation for our empirical finding that the seller can benefit from a platform’s entry

Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters

Ecosystem models are useful tools for evaluating environmental controls on carbon and water cycles under past or future conditions. In this paper we compare annual carbon and water fluxes from nine boreal spruce forest ecosystem models in a series of sensitivity simulations. For each comparison, a single climate driver or forest site parameter was altered in a separate sensitivity run. Driver and parameter changes were prescribed principally to be large enough to identify and isolate any major differences in model responses, while also remaining within the range of variability that the boreal forest biome may be exposed to over a time period of several decades. The models simulated plant production, autotrophic and heterotrophic respiration, and evapotranspiration (ET) for a black spruce site in the boreal forest of central Canada (56°N). Results revealed that there were common model responses in gross primary production, plant respiration, and ET fluxes to prescribed changes in air temperature or surface irradiance and to decreased precipitation amounts. The models were also similar in their responses to variations in canopy leaf area, leaf nitrogen content, and surface organic layer thickness. The models had different sensitivities to certain parameters, namely the net primary production response to increased CO2 levels, and the response of soil microbial respiration to precipitation inputs and soil wetness. These differences can be explained by the type (or absence) of photosynthesis-CO2 response curves in the models and by response algorithms of litter and humus decomposition to drying effects in organic soils of the boreal spruce ecosystem. Differences in the couplings of photosynthesis and soil respiration to nitrogen availability may also explain divergent model responses. Sensitivity comparisons imply that past conditions of the ecosystem represented in the models\u27 initial standing wood and soil carbon pools, including historical climate patterns and the time since the last major disturbance, can be as important as potential climatic changes to prediction of the annual ecosystem carbon balance in this boreal spruce forest

Boreal forest CO2 exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions

Semantically Linking In Silico Cancer Models

Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us better understand and explore combinations of models spanning multiple biological scales. We take the data model encoded by TumorML, an XML-based markup language for storing cancer models in online repositories, and transpose its model description elements into a graph-based representation. By taking such an approach, we can link domain models, such as controlled vocabularies, taxonomic schemes, and ontologies, with cancer model descriptions to better understand and explore relationships between models. The union of these graphs creates a connected property graph that links cancer models by categorizations, by computational compatibility, and by semantic interoperability, yielding a framework in which opportunities for exploration and discovery of combinations of models become possible

Confining Potential when a Biopolymer Filament Reptates

Using single-molecule fluorescence imaging, we track Brownian motion perpendicular to the contour of tightly entangled F-actin filaments and extract the confining potential. The chain localization presents a small-displacement Hookean regime followed by a large amplitude regime where the effective restoring force is independent of displacement. The implied heterogeneity characterized by a distribution of tube width is modeled.open271

Effect of Statistical Fluctuation in Monte Carlo Based Photon Beam Dose Calculation on Gamma Index Evaluation

The gamma-index test has been commonly adopted to quantify the degree of agreement between a reference dose distribution and an evaluation dose distribution. Monte Carlo (MC) simulation has been widely used for the radiotherapy dose calculation for both clinical and research purposes. The goal of this work is to investigate both theoretically and experimentally the impact of the MC statistical fluctuation on the gamma-index test when the fluctuation exists in the reference, the evaluation, or both dose distributions. To the first order approximation, we theoretically demonstrated in a simplified model that the statistical fluctuation tends to overestimate gamma-index values when existing in the reference dose distribution and underestimate gamma-index values when existing in the evaluation dose distribution given the original gamma-index is relatively large for the statistical fluctuation. Our numerical experiments using clinical photon radiation therapy cases have shown that 1) when performing a gamma-index test between an MC reference dose and a non-MC evaluation dose, the average gamma-index is overestimated and the passing rate decreases with the increase of the noise level in the reference dose; 2) when performing a gamma-index test between a non-MC reference dose and an MC evaluation dose, the average gamma-index is underestimated when they are within the clinically relevant range and the passing rate increases with the increase of the noise level in the evaluation dose; 3) when performing a gamma-index test between an MC reference dose and an MC evaluation dose, the passing rate is overestimated due to the noise in the evaluation dose and underestimated due to the noise in the reference dose. We conclude that the gamma-index test should be used with caution when comparing dose distributions computed with Monte Carlo simulation

Detection of the infrared aurora at Uranus with Keck-NIRSPEC

Near infrared (NIR) wavelength observations of Uranus have been unable to locate any infrared aurorae, despite many attempts to do so since the 1990s. While at Jupiter and Saturn, NIR investigations have redefined our understanding of magnetosphere ionosphere thermosphere coupling, the lack of NIR auroral detection at Uranus means that we have lacked a window through which to study these processes at Uranus. Here we present NIR Uranian observations with the Keck II telescope taken on the 5 September 2006 and detect enhanced $\text{H}_{\text{3}}^{\text{+}}$ emissions. Analysing temperatures and column densities, we identify an 88\% increase in localized $\text{H}_{\text{3}}^{\text{+}}$ column density, with no significant temperature increases, consistent with auroral activity generating increased ionization. By comparing these structures against the $\text{Q}_{\text{3}}^{\text{mp}}$ magnetic field model and the Voyager 2 ultraviolet observations, we suggest that these regions make up sections of the northern aurora.Comment: 12 pages, 3 main figures, 2 extended data figures. Nat Astron (2023