Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Markov Chains

Score matching is an approach to learning probability distributions parametrized up to a constant of proportionality (e.g. Energy-Based Models). The idea is to fit the score of the distribution, rather than the likelihood, thus avoiding the need to evaluate the constant of proportionality. While there's a clear algorithmic benefit, the statistical "cost'' can be steep: recent work by Koehler et al. 2022 showed that for distributions that have poor isoperimetric properties (a large Poincar\'e or log-Sobolev constant), score matching is substantially statistically less efficient than maximum likelihood. However, many natural realistic distributions, e.g. multimodal distributions as simple as a mixture of two Gaussians in one dimension -- have a poor Poincar\'e constant. In this paper, we show a close connection between the mixing time of an arbitrary Markov process with generator $\mathcal{L}$ and an appropriately chosen generalized score matching loss that tries to fit $\frac{\mathcal{O} p}{p}$. If $\mathcal{L}$ corresponds to a Markov process corresponding to a continuous version of simulated tempering, we show the corresponding generalized score matching loss is a Gaussian-convolution annealed score matching loss, akin to the one proposed in Song and Ermon 2019. Moreover, we show that if the distribution being learned is a finite mixture of Gaussians in $d$ dimensions with a shared covariance, the sample complexity of annealed score matching is polynomial in the ambient dimension, the diameter the means, and the smallest and largest eigenvalues of the covariance -- obviating the Poincar\'e constant-based lower bounds of the basic score matching loss shown in Koehler et al. 2022. This is the first result characterizing the benefits of annealing for score matching -- a crucial component in more sophisticated score-based approaches like Song and Ermon 2019.Comment: 39 page

Reliability of mantle tomography models assessed by spectral element simulation

Global tomographic models collected in the Seismic wave Propagation and Imaging in Complex (SPICE media: a European network) model library (http://www.spicertn.org/research/planetaryscale/tomography/) share a similar pattern of long, spatial wavelength heterogeneity, but are not consistent at shorter spatial wavelengths. Here, we assess the performance of global tomographic models by comparing how well they fit seismic waveform observations, in particular Love and Rayleigh wave overtones and fundamental modes. We first used the coupled spectral element method (CSEM) to calculate long-period (>100 s) synthetic seismograms for different global tomography models. The CSEM can incorporate the effect of three-dimensional (3-D) variations in velocity, anisotropy, density and attenuation with very little numerical dispersion. We then compared quantitatively synthetic seismograms and real data. To restrict ourselves to high-quality overtone data, and to minimize the effects of the finite extent of seismic sources and of crustal heterogeneity, we favour deep (>500 km) earthquakes of intermediate magnitude (Mw ∼ 7). Our comparisons reveal that: (1) The 3-D global tomographic models explain the data much better than the one-dimensional (1-D) anisotropic Preliminary Reference Earth Model (PREM). The current 3-D tomographic models have captured the large-scale features of upper-mantle heterogeneities, but there is still some room for the improvement of large-scale features of global tomographic models. (2) The average correlation coefficients for deep events are higher than those for shallow events, because crustal structure is too complex to be completely incorporated into CSEM simulations. (3) The average correlation coefficient (or the time lag) for the major-arc wave trains is lower (or higher) than that for the minor-arc wave trains. Therefore, the current tomographic models could be much improved by including the major-arc wave trains in the inversion. (4) The shallow-layer crustal correction has more effects on the fundamental surface waves than on the overtone

Characterizing Out-of-Distribution Error via Optimal Transport

Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models, so methods of predicting a model's performance on OOD data without labels are important for machine learning safety. While a number of methods have been proposed by prior work, they often underestimate the actual error, sometimes by a large margin, which greatly impacts their applicability to real tasks. In this work, we identify pseudo-label shift, or the difference between the predicted and true OOD label distributions, as a key indicator to this underestimation. Based on this observation, we introduce a novel method for estimating model performance by leveraging optimal transport theory, Confidence Optimal Transport (COT), and show that it provably provides more robust error estimates in the presence of pseudo-label shift. Additionally, we introduce an empirically-motivated variant of COT, Confidence Optimal Transport with Thresholding (COTT), which applies thresholding to the individual transport costs and further improves the accuracy of COT's error estimates. We evaluate COT and COTT on a variety of standard benchmarks that induce various types of distribution shift -- synthetic, novel subpopulation, and natural -- and show that our approaches significantly outperform existing state-of-the-art methods with an up to 3x lower prediction error

A Robust and Accurate Traveltime Calculation from

We improve the accuracy and stability of traveltime calculation method using frequency-domain modeling algorithm. We perform a parameter analysis to obtain the optimum combination of frequency and damping factor and thus improve the accuracy of traveltime. Then we obtain the empirical formula for our numerical algorithm. Lastly, we propose the adaptive frequency and the adaptive damping factor for an inhomogeneous model to eliminate the distortion in the traveltime contour. Twodimensional numerical examples verify that the proposed algorithm gives a much smaller traveltime error and a better traveltime contour for the complex model. Compared to the other two methods, this algorithm computes traveltime that is close to a directly transmitted wave. We demonstrated our algorithm on 2D IFP Marmousi models, and the numerical results show that our algorithm is a faster traveltime calculation method of a directly transmitted wave for imaging the subsurface and transmission tomography.This study is sponsored by the Chinese State Natural Science Foundation (49825108), the Chinese Academy of Sciences (KZCX2-109 and KZ951-B1-407-02), and the Korea Foundation for Advanced Studies. This work was also financially supported by the National Laboratory Project of the Ministry of Science and Technology and the Brain Korea 21 project of the Ministry of Education

Infiltrated IL-17A-producing gamma delta T cells play a protective role in sepsis-induced liver injury and are regulated by CCR6 and gut commensal microbes

IntroductionSepsis is a common but serious disease in intensive care units, which may induce multiple organ dysfunctions such as liver injury. Previous studies have demonstrated that gamma delta (γδ) T cells play a protective role in sepsis. However, the function and mechanism of γδ T cells in sepsis-induced liver injury have not been fully elucidated. IL-17A-producing γδ T cells are a newly identified cell subtype.MethodsWe utilized IL-17A-deficient mice to investigate the role of IL-17A-producing γδ T cells in sepsis using the cecum ligation and puncture (CLP) model.ResultsOur findings suggested that these cells were the major source of IL-17A and protected against sepsis-induced liver injury. Flow cytometry analysis revealed that these γδ T cells expressed Vγ4 TCR and migrated into liver from peripheral post CLP, in a CCR6-dependent manner. When CLP mice were treated with anti-CCR6 antibody to block CCR6-CCL20 axis, the recruitment of Vγ4+ γδ T cells was abolished, indicating a CCR6-dependent manner of migration. Interestingly, pseudo germ-free CLP mice treated with antibiotics showed that hepatic IL-17A+ γδ T cells were regulated by gut commensal microbes. E. coli alone were able to restore the protective effect in pseudo germ-free mice by rescuing hepatic IL-17A+ γδ T cell population.ConclusionOur research has shown that Vγ4+ IL-17A+ γδ T cells infiltrating into the liver play a crucial role in protecting against sepsis-induced liver injury. This protection was contingent upon the recruitment of CCR6 and regulated by gut commensal microbes

Functional Promoter -31G>C Variant in Survivin Gene Is Associated with Risk and Progression of Renal Cell Cancer in a Chinese Population

BACKGROUND: Survivin is an inhibitor of apoptosis protein and is involved in the occurrence and progression of human malignancies. Recently, a functional polymorphism (-31G>C, rs9904341) in the promoter of survivin has been shown to influence its expression and confer susceptibility to different types of cancer. The present study was aimed to investigate whether the polymorphism also influences susceptibility and progression of renal cell cancer (RCC) in a Chinese population. METHODS: We genotyped this polymorphism using the TaqMan assay in a case-control study comprised of 710 RCC patients and 760 controls. The logistic regression was used to assess the genetic association with occurrence and progression of RCC. RESULTS: Compared with the genotypes containing G allele (GG and GC), we found a statistically significant increased occurrence of RCC associated with the CC genotype [P = 0.006, adjusted odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08-1.76]. The polymorphism was associated with risk of developing advanced stage (OR = 2.02, 95%CI = 1.34-3.07) and moderately differentiated (OR = 1.75; 95%CI = 1.20-2.54) RCC. Furthermore, the patients carrying the CC genotype had a significantly greater prevalence of high clinical stage disease (P(trend) = 0.003). Similar results were also observed when we restricted the analysis to clear cell RCC, a major histological type of RCC. CONCLUSIONS: Our results suggest that the functional -31G>C polymorphism in the promoter of survivin may influence the susceptibility and progression of RCC in the Chinese population. Large population-based prospective studies are required to validate our findings

Association of CYP2C19 Loss-of-Function Metabolizer Status With Stroke Risk Among Chinese Patients Treated With Ticagrelor-Aspirin vs Clopidogrel-Aspirin: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

Importance: The Clopidogrel With Aspirin in High-Risk Patients With Acute Nondisabling Cerebrovascular Events II (CHANCE-2) trial showed that ticagrelor-aspirin combination therapy reduced the risk of stroke compared with a clopidogrel-aspirin combination among carriers of CYP2C19 loss-of-function (LOF) alleles after a transient ischemic attack (TIA) or minor ischemic stroke. However, the association between the degree of CYP2C19 LOF and ideal treatment allocation remains unknown.Objective: To investigate whether the efficacy and safety of ticagrelor-aspirin vs clopidogrel-aspirin are consistent with the expected degree of CYP2C19 LOF after TIA or minor stroke.Design, Setting, and Participants: CHANCE-2 was a multicenter, double-blind, double-dummy, placebo-controlled randomized clinical trial. Patients were enrolled at 202 centers in China from September 23, 2019, through March 22, 2021. Patients with at least two *2 or *3 alleles (*2/*2, *2/*3, or *3/*3) according to point-of-care genotyping were classified as “poor metabolizers,” and those with one *2 or *3 allele (*1/*2 or *1/*3) were classified as “intermediate metabolizers.”Interventions: Patients were randomly assigned in a 1:1 ratio to receive ticagrelor (180-mg loading dose on day 1 followed by 90 mg twice daily for days 2-90) or clopidogrel (300-mg loading dose on day 1 followed by 75 mg/d for days 2-90). All patients received aspirin (75- to 300-mg loading dose followed by 75 mg/d for 21 days).Main Outcomes and Measures: The primary efficacy outcome was a new ischemic or hemorrhagic stroke. The secondary efficacy outcome was a composite of new clinical vascular events and individual ischemic stroke events within 3 months. The primary safety outcome was severe or moderate bleeding. Analyses were performed according to the intention-to-treat principle.Results: Of the 6412 patients enrolled, the median age was 64.8 years (IQR, 57.0-71.4 years), and 4242 patients (66.2%) were men. Of the 6412 patients, 5001 (78.0%) were intermediate metabolizers, and 1411 (22.0%) were poor metabolizers. The primary outcome occurred less often with ticagrelor-aspirin vs clopidogrel-aspirin, irrespective of metabolizer status (6.0% [150 of 2486] vs 7.6% [191 of 2515]; hazard ratio [HR], 0.78 [95% CI, 0.63-0.97] among intermediate metabolizers and 5.7% [41 of 719] vs 7.5% [52 of 692]; HR, 0.77 [95% CI, 0.50-1.18] among poor metabolizers; P = .88 for interaction). Patients taking ticagrelor-aspirin had a higher risk of any bleeding event compared with those taking clopidogrel-aspirin, irrespective of metabolizer status: 5.4% (134 of 2486) vs 2.6% (66 of 2512) (HR, 2.14 [95% CI, 1.59-2.89]) among intermediate metabolizers and 5.0% (36 of 719) vs 2.0% (14 of 692) (HR, 2.99 [95% CI, 1.51-5.93]) among poor metabolizers (P = .66 for interaction).Conclusions and Relevance: This prespecified analysis of a randomized clinical trial found no difference in treatment effect between poor and intermediate CYP2C19 metabolizers. The relative clinical efficacy and safety of ticagrelor-aspirin vs clopidogrel-aspirin were consistent across CYP2C19 genotypes.Trial Registration: ClinicalTrials.gov Identifier: NCT0407873

Incorporation of a hinge domain improves the expansion of chimeric antigen receptor T cells

© 2017 The Author(s). Background: Multiple iterations of chimeric antigen receptors (CARs) have been developed, mainly focusing on intracellular signaling modules. However, the effect of non-signaling extracellular modules on the expansion and therapeutic efficacy of CARs remains largely undefined. Methods: We generated two versions of CAR vectors, with or without a hinge domain, targeting CD19, mesothelin, PSCA, MUC1, and HER2, respectively. Then, we systematically compared the effect of the hinge domains on the growth kinetics, cytokine production, and cytotoxicity of CAR T cells in vitro and in vivo. Results: During in vitro culture period, the percentages and absolute numbers of T cells expressing the CARs containing a hinge domain continuously increased, mainly through the promotion of CD4+ CAR T cell expansion, regardless of the single-chain variable fragment (scFv). In vitro migration assay showed that the hinges enhanced CAR T cells migratory capacity. The T cells expressing anti-CD19 CARs with or without a hinge had similar antitumor capacities in vivo, whereas the T cells expressing anti-mesothelin CARs containing a hinge domain showed enhanced antitumor activities. Conclusions: Hence, our results demonstrate that a hinge contributes to CAR T cell expansion and is capable of increasing the antitumor efficacy of some specific CAR T cells. Our results suggest potential novel strategies in CAR vector design.Link_to_subscribed_fulltex

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages