Condensation tendency and planar isotropic actin gradient induce radial alignment in confined monolayers

A monolayer of highly motile cells can establish long-range orientational order, which can be explained by hydrodynamic theory of active gels and fluids. However, it is less clear how cell shape changes and rearrangement are governed when the monolayer is in mechanical equilibrium states when cell motility diminishes. In this work, we report that rat embryonic fibroblasts (REF), when confined in circular mesoscale patterns on rigid substrates, can transition from the spindle shapes to more compact morphologies. Cells align radially only at the pattern boundary when they are in the mechanical equilibrium. This radial alignment disappears when cell contractility or cell-cell adhesion is reduced. Unlike monolayers of spindle-like cells such as NIH-3T3 fibroblasts with minimal intercellular interactions or epithelial cells like Madin-Darby canine kidney (MDCK) with strong cortical actin network, confined REF monolayers present an actin gradient with isotropic meshwork, suggesting the existence of a stiffness gradient. In addition, the REF cells tend to condense on soft substrates, a collective cell behavior we refer to as the ‘condensation tendency’. This condensation tendency, together with geometrical confinement, induces tensile prestretch (i.e. an isotropic stretch that causes tissue to contract when released) to the confined monolayer. By developing a Voronoi-cell model, we demonstrate that the combined global tissue prestretch and cell stiffness differential between the inner and boundary cells can sufficiently define the cell radial alignment at the pattern boundary

Biomechanical microenvironment regulates fusogenicity of breast cancer cells

Fusion of cancer cells is thought to contribute to tumor development and drug resistance. The low frequency of cell fusion events and the instability of fused cells have hindered our ability to understand the molecular mechanisms that govern cell fusion. We have demonstrated that several breast cancer cell lines can fuse into multinucleated giant cells in vitro, and the initiation and longevity of fused cells can be regulated solely by biophysical factors. Dynamically tuning the adhesive area of the patterned substrates, reducing cytoskeletal tensions pharmacologically, altering matrix stiffness, and modulating pattern curvature all supported the spontaneous fusion and stability of these multinucleated giant cells. These observations highlight that the biomechanical microenvironment of cancer cells, including the matrix rigidity and interfacial curvature, can directly modulate their fusogenicity, an unexplored mechanism through which biophysical cues regulate tumor progression

Imaging and detecting intercellular tensile forces in spheroids and embryoid bodies using lipid-modified DNA probes

Cells continuously experience and respond to different physical forces that are used to regulate their physiology and functions. Our ability to measure these mechanical cues is essential for understanding the bases of various mechanosensing and mechanotransduction processes. While multiple strategies have been developed to study mechanical forces within two-dimensional (2D) cell culture monolayers, the force measurement at cell-cell junctions in real three-dimensional (3D) cell models is still pretty rare. Considering that in real biological systems, cells are exposed to forces from 3D directions, measuring these molecular forces in their native environment is thus highly critical for the better understanding of different development and disease processes. We have recently developed a type of DNA-based molecular probe for measuring intercellular tensile forces in 2D cell models. Herein, we will report the further development and first-time usage of these molecular tension probes to visualize and detect mechanical forces within 3D spheroids and embryoid bodies (EBs). These probes can spontaneously anchor onto live cell membranes via the attached lipid moieties. By varying the concentrations of these DNA probes and their incubation time, we have first characterized the kinetics and efficiency of probe penetration and loading onto tumor spheroids and stem cell EBs of different sizes. After optimization, we have further imaged and measured E-cadherin-mediated forces in these 3D spheroids and EBs for the first time. Our results indicated that these DNA-based molecular tension probes can be used to study the spatiotemporal distributions of target mechanotransduction processes. These powerful imaging tools may be potentially applied to fill the gap between ongoing research of biomechanics in 2D systems and that in real 3D cell complexes

Biomechanical Regulation of Cell Rearrangement and Fate Patterning Under Geometrical Confinement

Geometrical confinement or micropatterning techniques have been widely used to investigate cell migration, chirality, polarity, epithelial-mesenchymal transition, and stem cell differentiation with a potential for high-throughput screening. In this dissertation, geometrical confinement techniques are employed to study the biomechanical mechanisms in cell rearrangement and spatial patterning of embryonic cell fates. In chapter 2, I find that both cell contractility and actin gradient contributed to the radial alignment of rat embryonic fibroblasts. Combined with a Voronoi-cell model developed by our collaborator, our results demonstrate that the combined global tissue prestretch and differential cell stiffness between the inner and boundary cells can sufficiently lead to radial alignment. In chapter 3, I demonstrate that human pluripotent stem cells can self-organize to concentric rings of all major cell types in human ectoderm when cultured on micropatterned surfaces in a chemically defined condition. I reveal that modulating the dynamics of NODAL, BMP, and WNT signals is sufficient to control the spatial order of different cell types. The mathematical model developed by our collaborator suggests that changes in wavelength and phase of signaling patterns formed via reaction-diffusion may be the mechanism by which temporal information is translated into spatial information. In chapter 4, I generate an early human midbrain and hindbrain tissue with anteroposterior (AP) patterning using human pluripotent stem cells that are induced with BMP, WNT, RA, and SHH signals under fully defined culture conditions. I find that the cells self-organize into spatially patterned midbrain (OTX2+) and hindbrain (HOXB4+) progenitors after 6 days of induction. To investigate the mechanism of AP cell fates patterning, I find that SHH is not required in midbrain and hindbrain patterning while the reaction-diffusion of BMP/Noggin plays a critical role in AP regionalization. Drug treatment experiments show that valproic acid inhibits both midbrain and hindbrain development while isotretinoin disrupts AP patterning of the midbrain and hindbrain. In summary, I have employed geometrical confinement techniques to study various cell behaviors and demonstrated that geometrically confined cell-based models have great potential in fundamental research of various cell behaviors and applications in disease modeling and drug discovery

Optimal Confidence Intervals for the Relative Risk and Odds Ratio

The relative risk and odds ratio are widely used in many fields, including biomedical research, to compare two treatments. Extensive research has been done to infer the two parameters through approximate or exact confidence intervals. However, these intervals may be liberal or conservative. A natural question is whether the intervals can be further improved in maintaining the correct confidence coefficient of an approximate interval or shortening an exact but conservative interval. In this article, when two independent binomials are observed we offer an effort to improve any of the existing intervals by applying the -function method. In particular, if the given interval is approximate, then the improved interval is exact; if the given interval is exact, then the improved interval is a subset of the given interval. This method is also applied multiple times to the improved intervals until the final resultant interval cannot be shortened any further. To demonstrate the effectiveness of the method, we use three real datasets to illustrate in detail how several good intervals in practice are improved. Two exact intervals are then recommended for estimating each of the two parameters in different scenarios

Optimal Confidence Intervals for the Relative Risk and Odds Ratio

The relative risk and odds ratio are widely used in many fields, including biomedical research, to compare two treatments. Extensive research has been done to infer the two parameters through approximate or exact confidence intervals. However, these intervals may be liberal or conservative. A natural question is whether the intervals can be further improved in maintaining the correct confidence coefficient of an approximate interval or shortening an exact but conservative interval. In this article, when two independent binomials are observed we offer an effort to improve any of the existing intervals by applying the -function method. In particular, if the given interval is approximate, then the improved interval is exact; if the given interval is exact, then the improved interval is a subset of the given interval. This method is also applied multiple times to the improved intervals until the final resultant interval cannot be shortened any further. To demonstrate the effectiveness of the method, we use three real datasets to illustrate in detail how several good intervals in practice are improved. Two exact intervals are then recommended for estimating each of the two parameters in different scenarios

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement