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Abstract We present a theory that explains the resonance effect of the vibrational strong coupling (VSC) modified reaction rate constant at the normal incidence of a Fabry–Pérot (FP) cavity. This analytic theory is based on a mechanistic hypothesis that cavity modes promote the transition from the ground state to the vibrational excited state of the reactant, which is the rate-limiting step of the reaction. This mechanism for a single molecule coupled to a single-mode cavity has been confirmed by numerically exact simulations in our recent work in [J. Chem. Phys. 159, 084104 (2023)]. Using Fermi’s golden rule (FGR), we formulate this rate constant for many molecules coupled to many cavity modes inside a FP microcavity. The theory provides a possible explanation for the resonance condition of the observed VSC effect and a plausible explanation of why only at the normal incident angle there is the resonance effect, whereas, for an oblique incidence, there is no apparent VSC effect for the rate constant even though both cases generate Rabi splitting and forming polariton states. On the other hand, the current theory cannot explain the collective effect when a large number of molecules are collectively coupled to the cavity, and future work is required to build a complete microscopic theory to explain all observed phenomena in VSC. 

We investigate rifting during continental collision in southern Tibet by testing kinematic models for two classes of rifts: Tibetan rifts are defined as >150 km in length and crosscut the Lhasa Terrane, and Gangdese rifts are <150 km long and isolated within the high topography of the Gangdese Range. Discerning rift kinematics is a crucial step towards understanding rift behavior and evolution that has been historically limited. We evaluate spatiotemporal trends in fault displacement and extension onset in the Tangra Yumco (TYC) rift and several nearby Gangdese rifts and examine how contraction and rift exhumation relate to evolution of the Gangdese drainage divide. Igneous U-Pb and zircon (U-Th)/He (ZHe) results indicate rift footwall crystallization between ~59-49 Ma and cooling between ~60-4 Ma, respectively, with ZHe ages correlating with sample latitude. Samples from Gangdese latitudes (~29.4-29.8°N) yield predominantly Oligocene-early Miocene ages, whereas samples north of ~29.8°N yield both late Miocene-Pliocene ages and Paleocene-Eocene ages. Thermal history models indicate two-stage cooling, with initially slow cooling followed by accelerated cooling during late Miocene-Pliocene time. From spatial distributions of ZHe ages we interpret: (1) ~28-16 Ma ages from Gangdese latitudes reflect exhumation along contractional structures, (2) ~8-4 Ma ages reflect rift-related exhumation, and (3) ~60-48 Ma ages indicate these samples experienced lesser rift exhumation. Our data are consistent with a segment linkage evolution model for the TYC rift, with interactions between rifts and contractional structures likely influencing the evolution of topography and location of the Gangdese drainage divide since Miocene time 

The diverse T cell receptor (TCR) repertoire confers the ability to recognize an almost unlimited array of antigens. Characterization of antigen specificity of tumor-infiltrating lymphocytes (TILs) is key for understanding antitumor immunity and for guiding the development of effective immunotherapies. Here, we report a large-scale comprehensive examination of the TCR landscape of TILs across the spectrum of pediatric brain tumors, the leading cause of cancer-related mortality in children. We show that a T cell clonality index can inform patient prognosis, where more clonality is associated with more favorable outcomes. Moreover, TCR similarity groups’ assessment revealed patient clusters with defined human leukocyte antigen associations. Computational analysis of these clusters identified putative tumor antigens and peptides as targets for antitumor T cell immunity, which were functionally validated by T cell stimulation assays in vitro. Together, this study presents a framework for tumor antigen prediction based on in situ and in silico TIL TCR analyses. We propose that TCR-based investigations should inform tumor classification and precision immunotherapy development.