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Ulcerative colitis (UC) is an inflammatory intestinal disorder driven by mucosal immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin monoclonal antibody that is effective for treating UC. VDZ is thought to primarily inhibit lymphocyte trafficking to the intestine, but its effect on other cell subsets is less well characterized. To identify the inflammatory cells that contribute to colitis and respond to VDZ, we performed a single-cell transcriptomic and proteomic analysis of peripheral blood and colonic biopsies in healthy controls (HC) and patients with UC on either aminosalicylates or VDZ. We identified mononuclear phagocytes (MNPs) as a primary target of VDZ, with comparatively modest effects on lymphocytes. Spatial proteomics and transcriptomics demonstrated increased density and proximity of MNP and fibroblast subsets in UC biopsies when compared to HC, with inhibition by VDZ. VDZ non-responders were enriched for activated fibroblast and MNP signatures in a validation cohort.

A challenge in quantitative biology is to predict output patterns of gene expression from knowledge of input transcription factor patterns and from the arrangement of binding sites for these transcription factors on regulatory DNA. We tested whether widespread thermodynamic models could be used to infer parameters describing simple regulatory architectures that inform parameter-free predictions of more complex enhancers in the context of transcriptional repression by Runt in the early fruit 2y embryo. By modulating the number and placement of Runt binding sites within an enhancer, and quantifying the resulting transcriptional activity using live imaging, we discovered that thermodynamic models call for higher-order cooperativity between multiple molecular players. This higher-order cooperativity capture the combinatorial complexity underlying eukaryotic transcriptional regulation and cannot be determined from simpler regulatory architectures, highlighting the challenges in reaching a predictive understanding of transcriptional regulation in eukaryotes and calling for approaches that quantitatively dissect their molecular nature.

Transcriptional control is fundamental to cellular function. However, despite knowing that transcription factors can repress or activate specific genes, how these functions are implemented at the molecular level has remained elusive. Here we combine optogenetics, single-cell live-imaging, and mathematical modeling to study how a zinc-finger repressor, Knirps, induces switch-like transitions into long-lived quiescent states. Using optogenetics, we demonstrate that repression is rapidly reversible (∼1 minute) and memoryless. Furthermore, we show that the repressor acts by decreasing the frequency of transcriptional bursts in a manner consistent with an equilibrium binding model. Our results provide a quantitative framework for dissecting thein vivobiochemistry of eukaryotic transcriptional regulation.

Spatial transcriptomics extends single cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH) can achieve single-cell resolution, directly mapping single cell identities to spatial positions. MERFISH produces an intrinsically different data type than scRNA-seq and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas as well as from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that compared to scRNA-seq, MERFISH provides a quantitatively comparable method for measuring single-cell gene expression and can robustly identify cell types without the need for computational integration with scRNA-seq reference atlases.

The eukaryotic transcription cycle consists of three main steps: initiation, elongation, and cleavage of the nascent RNA transcript. Although each of these steps can be regulated as well as coupled with each other, their in vivo dissection has remained challenging because available experimental readouts lack sufficient spatiotemporal resolution to separate the contributions from each of these steps. Here, we describe a novel application of Bayesian inference techniques to simultaneously infer the effective parameters of the transcription cycle in real time and at the single-cell level using a two-color MS2/PP7 reporter gene and the developing fruit fly embryo as a case study. Our method enables detailed investigations into cell-to-cell variability in transcription-cycle parameters as well as single-cell correlations between these parameters. These measurements, combined with theoretical modeling, suggest a substantial variability in the elongation rate of individual RNA polymerase molecules. We further illustrate the power of this technique by uncovering a novel mechanistic connection between RNA polymerase density and nascent RNA cleavage efficiency. Thus, our approach makes it possible to shed light on the regulatory mechanisms in play during each step of the transcription cycle in individual, living cells at high spatiotemporal resolution., Author summary Live cell imaging using fluorescence microscopy provides an exciting way to visualize the transcription cycle in living organisms with great amounts of precision. However, the output of these technologies is often complex and can be hard to interpret. We have developed a computational framework for analyzing the transcription cycle that quantifies rates of RNA initiation, elongation, and cleavage, given input datasets from live cell imaging. Using the developing fruit fly embryo as a case study, we demonstrate that our methodology can quantitatively describe the whole transcription cycle at single-cell resolution. These results allow us to investigate a plethora of avenues, from couplings between different aspects of the transcription cycle at the single-cell level to comparisons with theoretical predictions of distributions of elongation rates across cells. We envision our methodology to provide a unified computational framework for the analysis of transcriptional data obtained from live cell imaging.

Eukaryotic transcription generally occurs in bursts of activity lasting minutes to hours; however, state-of-the-art measurements have revealed that many of the molecular processes that underlie bursting, such as transcription factor binding to DNA, unfold on timescales of seconds. This temporal disconnect lies at the heart of a broader challenge in physical biology of predicting transcriptional outcomes and cellular decision-making from the dynamics of underlying molecular processes. Here, we review how new dynamical information about the processes underlying transcriptional control can be combined with theoretical models that predict not only averaged transcriptional dynamics, but also their variability, to formulate testable hypotheses about the molecular mechanisms underlying transcriptional bursting and control., 41 pages, 4 figures, review article

Although the last 30years have witnessed the mapping of the wiring diagrams of the gene regulatory networks that dictate cell fate and animal body plans, specific understanding building on such network diagrams that shows how DNA regulatory regions control gene expression lags far behind. These networks have yet to yield the predictive power necessary to, for example, calculate how the concentration dynamics of input transcription factors and DNA regulatory sequence prescribes output patterns of gene expression that, in turn, determine body plans themselves. Here, we argue that reaching a predictive understanding of developmental decision-making calls for an interplay between theory and experiment aimed at revealing how the regulation of the processes of the central dogma dictate network connections and how network topology guides cells toward their ultimate developmental fate. To make this possible, it is crucial to break free from the snapshot-based understanding of embryonic development facilitated by fixed-tissue approaches and embrace new technologies that capture the dynamics of developmental decision-making at the single cell level, in living embryos.

Kevin J. Cao and Richard H. Kramer, who developed extended release with beta cyclodextrin, were inadvertently omitted from the author list and author contributions section of this Article. These errors have now been corrected in both the PDF and HTML versions of the Article.

Airfoils with improved longitudinal static stability were designed for a WIG craft through aerodynamic design optimization. The response surface method is coupled with NURBS-based shape functions and Navier-Stokes flow analysis. The procedure runs in the network-distributed design framework of commercial-code based automated design capability to enhance computational efficiency and robustness.Lift maximization design maintaining similar static margin to a DHMTU airfoil successfully produced a new airfoil shape characterized by pronounced front-loading and the well-known reflexed aft-camber line. Another airfoil design of lower variation in pitching moment during take-off showed weakened front-loaded characteristics and hence decreased lift slightly. Investigations using the present design methodology on an existing optimization result based on potential flow analysis and NACA-type geometry generation demonstrated significance of carrying various geometry generations and more realistic flow analysis with optimization.

Several notes on ground effects drawn from Navier-Stokes analyses and their aerodynamic interpretations were addressed here; For two-dimensional ground effect, the change of surface pressure due to image vortex, the venturi effect due to thickness and the primary inviscid flow phenomena of ground effect, and for three-dimensional ground effect, strengthened wing tip vortices, increased effective span and the outward drift of trailing vortices. Irodov`s criteria were evaluated to investigate the static longitudinal stability of conventional NACA 6409 and DHMTU 8-30 airfoils. The analysis results demonstrated superior static longitudinal stability of DHMTU 8-30 airfoil. The DHMTU airfoil has quite lower value of lrodov`s criterion than the conventional NACA airfoil, which require much smaller tail volume to stabilize the whole WIG-craft at its design stage.

Oxidation of sulfide 4 gave a mixture of cis and trans monosulfoxides 5 and 6 as major and minor products, respectively, plus a small amount of disulfoxides 7. The structural assignments of cis and trans sulfoxides 5 and 6 were based on 1H NMR spectroscopy and the regiospecific deuterations of the two isomers . Under neutral conditions cis sulfoxides 5 underwent a sigmatropic rearrangement with 2-methylene hydrogens to give sulfenic acids 18, followed by cyclization to dihydro-1,4-dithiins 2. The trans sulfoxides 6 rearranged involving 2-methyl hydrogens to form isomeric dihydrodithiins 3 via sulfenic acids 19. In the reactions of both the sulfoxides, sulfoxides 4 and disulfides 11 were also formed as minor side products. In the presence of acid catalyst cis sulfoxides 5 produced 2 in quantitative yields plus a small amount of 3 , while the trans sulfoxides 6 gave 2 as major product and 3 as minor. The mechanisms of formation of 2, 3, 4 and 11 are discussed.