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1. The Houston Methodist lung transplant risk model – a validated tool for pre-transplant risk assessment

   https://doi.org/10.1016/j.athoracsur.2019.03.108  

   Chan EY, Nguyen DT (October 2019, The annals of thoracic surgery)

   BACKGROUND: Lung transplantation is the gold standard for a carefully selected patient population with end-stage lung disease. We sought to create a unique risk stratification model using only preoperative recipient data to predict one-year postoperative mortality during our pre-transplant assessment. METHODS: Data of lung transplant recipients at Houston Methodist Hospital (HMH) from 1/2009 to 12/2014 were extracted from the United Network for Organ Sharing (UNOS) database. Patients were randomly divided into development and validation cohorts. Cox proportional-hazards models were conducted. Variables associated with 1-year mortality post-transplant were assigned weights based on the beta coefficients, and risk scores were derived. Patients were stratified into low-, medium- and high-risk categories. Our model was validated using the validation dataset and data from other US transplant centers in the UNOS database RESULTS: We randomized 633 lung recipients from HMH into the development (n=317 patients) and validation cohort (n=316). One-year survival after transplant was significantly different among risk groups: 95% (low-risk), 84% (medium-risk), and 72% (high-risk) (p<0.001) with a C-statistic of 0.74. Patient survival in the validation cohort was also significantly different among risk groups (85%, 77% and 65%, respectively, p<0.001). Validation of the model with the UNOS dataset included 9,920 patients and found 1-year survival to be 91%, 86% and 82%, respectively (p < 0.001). CONCLUSIONS: Using only recipient data collected at the time of pre-listing evaluation, our simple scoring system has good discrimination power and can be a practical tool in the assessment and selection of potential lung transplant recipients. 

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2. Measurement of the inclusive branching fractions for $${B}_{s}^{0}$$ decays into D mesons via hadronic tagging

   https://doi.org/10.1007/JHEP04(2025)114  

   Adachi, I; Aggarwal, L; Ahmed, H; Aihara, H; Akopov, N; Aloisio, A; Al_Said, S; Althubiti, N; Anh_Ky, N; Asner, D M; et al (April 2025, Journal of High Energy Physics)

   A<sc>bstract</sc> We report measurements of the absolute branching fractions$$\mathcal{B}\left({B}_{s}^{0}\to {D}_{s}^{\pm }X\right)$$,$$\mathcal{B}\left({B}_{s}^{0}\to {D}^{0}/{\overline{D} }^{0}X\right)$$, and$$\mathcal{B}\left({B}_{s}^{0}\to {D}^{\pm }X\right)$$, where the latter is measured for the first time. The results are based on a 121.4 fb⁻¹data sample collected at the Υ(10860) resonance by the Belle detector at the KEKB asymmetric-energye⁺e⁻collider. We reconstruct one$${B}_{s}^{0}$$meson in$${e}^{+}{e}^{-}\to \Upsilon\left(10860\right)\to {B}_{s}^{*}{\overline{B} }_{s}^{*}$$events and measure yields of$${D}_{s}^{+}$$,D⁰, andD⁺mesons in the rest of the event. We obtain$$\mathcal{B}\left({B}_{s}^{0}\to {D}_{s}^{\pm }X\right)=\left(68.6\pm 7.2\pm 4.0\right)\%$$,$$\mathcal{B}\left({B}_{s}^{0}\to {D}^{0}/{\overline{D} }^{0}X\right)=\left(21.5\pm 6.1\pm 1.8\right)\%$$, and$$\mathcal{B}\left({B}_{s}^{0}\to {D}^{\pm }X\right)=\left(12.6\pm 4.6\pm 1.3\right)\%$$, where the first uncertainty is statistical and the second is systematic. Averaging with previous Belle measurements gives$$\mathcal{B}\left({B}_{s}^{0}\to {D}_{s}^{\pm }X\right)=\left(63.4\pm 4.5\pm 2.2\right)\%$$and$$\mathcal{B}\left({B}_{s}^{0}\to {D}^{0}/{\overline{D} }^{0}X\right)=\left(23.9\pm 4.1\pm 1.8\right)\%$$. For the$${B}_{s}^{0}$$production fraction at the Υ(10860), we find$${f}_{s}=\left({21.4}_{-1.7}^{+1.5}\right)\%$$. 

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3. Search for dark matter produced in association with a single top quark and an energetic W boson in $$\sqrt{s}=$$ 13 TeV $$pp$$ collisions with the ATLAS detector

   https://doi.org/10.1140/epjc/s10052-023-11582-z  

   Aad, G.; Abbott, B.; Abbott, D. C.; Abeling, K.; Abidi, S. H.; Aboulhorma, A.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Hoffman, A. C.; et al (July 2023, The European Physical Journal C)

   Abstract This paper presents a search for dark matter,$$\chi $$ $\chi$, using events with a single top quark and an energeticWboson. The analysis is based on proton–proton collision data collected with the ATLAS experiment at$$\sqrt{s}=$$ $\sqrt{s}=$13 TeV during LHC Run 2 (2015–2018), corresponding to an integrated luminosity of 139 fb$$^{-1}$$ ${}^{-1}$. The search considers final states with zero or one charged lepton (electron or muon), at least oneb-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended two-Higgs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell production of the charged Higgs boson state,$$H^{\pm }$$ $H^{\pm }$, arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle,a:$$H^{\pm } \rightarrow W^\pm a (\rightarrow \chi \chi )$$ $H^{\pm }\to W^{\pm }a(\to \chi \chi )$. Signal models with$$H^{\pm }$$ $H^{\pm }$masses up to 1.5 TeV andamasses up to 350 GeV are excluded assuming a$$\tan \beta $$ $tan\beta$value of 1. For masses ofaof 150 (250) GeV,$$\tan \beta $$ $tan\beta$values up to 2 are excluded for$$H^{\pm }$$ $H^{\pm }$masses between 200 (400) GeV and 1.5 TeV. Signals with$$\tan \beta $$ $tan\beta$values between 20 and 30 are excluded for$$H^{\pm }$$ $H^{\pm }$masses between 500 and 800 GeV. 

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4. Measurements of Higgs boson production in the decay channel with a pair of $$\uptau $$ leptons in proton–proton collisions at $$\sqrt{s}=13$$ TeV

   https://doi.org/10.1140/epjc/s10052-023-11452-8  

   Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. Escalante; Frühwirth, R.; Jeitler, M.; et al (July 2023, The European Physical Journal C)

   Abstract Measurements of Higgs boson production, where the Higgs boson decays into a pair of$$\uptau $$ $\tau$leptons, are presented, using a sample of proton-proton collisions collected with the CMS experiment at a center-of-mass energy of Equation missing<#comment/>, corresponding to an integrated luminosity of 138$$\,\text {fb}^{-1}$$ ${\text{fb}}^{-1}$. Three analyses are presented. Two are targeting Higgs boson production via gluon fusion and vector boson fusion: a neural network based analysis and an analysis based on an event categorization optimized on the ratio of signal over background events. These are complemented by an analysis targeting vector boson associated Higgs boson production. Results are presented in the form of signal strengths relative to the standard model predictions and products of cross sections and branching fraction to$$\uptau $$ $\tau$leptons, in up to 16 different kinematic regions. For the simultaneous measurements of the neural network based analysis and the analysis targeting vector boson associated Higgs boson production signal strengths are found to be$$0.82\pm 0.11$$ $0.82\pm 0.11$for inclusive Higgs boson production,$$0.67\pm 0.19$$ $0.67\pm 0.19$($$0.81\pm 0.17$$ $0.81\pm 0.17$) for the production mainly via gluon fusion (vector boson fusion), and$$1.79\pm 0.45$$ $1.79\pm 0.45$for vector boson associated Higgs boson production. 

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5. A study of disproportionately affected populations by race/ethnicity during the SARS-CoV-2 pandemic using multi-population SEIR modeling and ensemble data assimilation

   https://doi.org/10.3934/fods.2021022  

   Fleurantin, Emmanuel; Sampson, Christian; Maes, Daniel Paul; Bennett, Justin; Fernandes-Nunez, Tayler; Marx, Sophia; Evensen, Geir (January 2021, Foundations of Data Science)

   null (Ed.)

   The disparity in the impact of COVID-19 on minority populations in the United States has been well established in the available data on deaths, case counts, and adverse outcomes. However, critical metrics used by public health officials and epidemiologists, such as a time dependent viral reproductive number (\begin{document}$$ R_t $$\end{document}), can be hard to calculate from this data especially for individual populations. Furthermore, disparities in the availability of testing, record keeping infrastructure, or government funding in disadvantaged populations can produce incomplete data sets. In this work, we apply ensemble data assimilation techniques which optimally combine model and data to produce a more complete data set providing better estimates of the critical metrics used by public health officials and epidemiologists. We employ a multi-population SEIR (Susceptible, Exposed, Infected and Recovered) model with a time dependent reproductive number and age stratified contact rate matrix for each population. We assimilate the daily death data for populations separated by ethnic/racial groupings using a technique called Ensemble Smoothing with Multiple Data Assimilation (ESMDA) to estimate model parameters and produce an \begin{document}$$R_t(n)$$\end{document} for the \begin{document}$$n^{th}$$\end{document} population. We do this with three distinct approaches, (1) using the same contact matrices and prior \begin{document}$$R_t(n)$$\end{document} for each population, (2) assigning contact matrices with increased contact rates for working age and older adults to populations experiencing disparity and (3) as in (2) but with a time-continuous update to \begin{document}$$R_t(n)$$\end{document}. We make a study of 9 U.S. states and the District of Columbia providing a complete time series of the pandemic in each and, in some cases, identifying disparities not otherwise evident in the aggregate statistics. 

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