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Efficient delivery of oxygen and nutrients to tissues requires an intricate balance of blood, lymphatic, and interstitial fluid pressures (IFPs), and gradients in fluid pressure drive the flow of blood, lymph, and interstitial fluid through tissues. While specific fluid mechanical stimuli, such as wall shear stress, have been shown to modulate cellular signaling pathways along with gene and protein expression patterns, an understanding of the key signals imparted by flowing fluid and how these signals are integrated across multiple cells and cell types in native tissues is incomplete due to limitations with current assays. Here, we introduce a multi-layer microfluidic platform (MμLTI-Flow) that enables the culture of engineered blood and lymphatic microvessels and independent control of blood, lymphatic, and IFPs. Using optical microscopy methods to measure fluid velocity for applied input pressures, we demonstrate varying rates of interstitial fluid flow as a function of blood, lymphatic, and interstitial pressure, consistent with computational fluid dynamics (CFD) models. The resulting microfluidic and computational platforms will provide for analysis of key fluid mechanical parameters and cellular mechanisms that contribute to diseases in which fluid imbalances play a role in progression, including lymphedema and solid cancer.

A bstract A search is presented for a heavy W′ boson resonance decaying to a B or T vector-like quark and a t or a b quark, respectively. The analysis is performed using proton-proton collisions collected with the CMS detector at the LHC. The data correspond to an integrated luminosity of 138 fb − 1 at a center-of-mass energy of 13 TeV. Both decay channels result in a signature with a t quark, a Higgs or Z boson, and a b quark, each produced with a significant Lorentz boost. The all-hadronic decays of the Higgs or Z boson and of the t quark are selected using jet substructure techniques to reduce standard model backgrounds, resulting in a distinct three-jet W′ boson decay signature. No significant deviation in data with respect to the standard model background prediction is observed. Upper limits are set at 95% confidence level on the product of the W′ boson cross section and the final state branching fraction. A W′ boson with a mass below 3.1 TeV is excluded, given the benchmark model assumption of democratic branching fractions. In addition, limits are set based on generalizations of these assumptions. These are the most sensitive limits to datemore »for this final state.« less

Abstract A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons ( τ h ) that originate from genuine tau leptons in the CMS detector against τ h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a τ h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine τ h to pass the discriminator against jets increases by 10–30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient τ h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved τ h reconstruction method are validated with LHC proton-proton collision data at √ s = 13 TeV.