Multiply charged magnetic black branes

We discuss analytic solutions describing magnetically charged black branes in $d$ dimensional AdS space. Focusing on $d=5$, we study the response of the brane to an external short lived electric field. We argue that when the theory possesses an 't Hooft anomaly then at sufficiently low temperature a long lived oscillatory current will be observed long after the electric field has been turned off. We demonstrate this ``anomalous resonance'' effect via a numerical study.Comment: 28 pages, 7 figure

Graph Neural Networks Use Graphs When They Shouldn't

Predictions over graphs play a crucial role in various domains, including social networks, molecular biology, medicine, and more. Graph Neural Networks (GNNs) have emerged as the dominant approach for learning on graph data. Instances of graph labeling problems consist of the graph-structure (i.e., the adjacency matrix), along with node-specific feature vectors. In some cases, this graph-structure is non-informative for the predictive task. For instance, molecular properties such as molar mass depend solely on the constituent atoms (node features), and not on the molecular structure. While GNNs have the ability to ignore the graph-structure in such cases, it is not clear that they will. In this work, we show that GNNs actually tend to overfit the graph-structure in the sense that they use it even when a better solution can be obtained by ignoring it. We examine this phenomenon with respect to different graph distributions and find that regular graphs are more robust to this overfitting. We then provide a theoretical explanation for this phenomenon, via analyzing the implicit bias of gradient-descent-based learning of GNNs in this setting. Finally, based on our empirical and theoretical findings, we propose a graph-editing method to mitigate the tendency of GNNs to overfit graph-structures that should be ignored. We show that this method indeed improves the accuracy of GNNs across multiple benchmarks

Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma

Multiple myeloma, a plasma cell malignancy, is the second most common blood cancer. Despite extensive research, disease heterogeneity is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA sequencing to study the heterogeneity of 40 individuals along the multiple myeloma progression spectrum, including 11 healthy controls, demonstrating high interindividual variability that can be explained by expression of known multiple myeloma drivers and additional putative factors. We identify extensive subclonal structures for 10 of 29 individuals with multiple myeloma. In asymptomatic individuals with early disease and in those with minimal residual disease post-treatment, we detect rare tumor plasma cells with molecular characteristics similar to those of active myeloma, with possible implications for personalized therapies. Single cell analysis of rare circulating tumor cells allows for accurate liquid biopsy and detection of malignant plasma cells, which reflect bone marrow disease. Our work establishes single cell RNA sequencing for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients

Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03287-8.</jats:p

Reinforcement Learning Agents for Interacting with Humans

We tackle the problem of an agent interacting with humans in a general-sum environment, i.e., a non-zero sum, non-fully cooperative setting, where the agent's goal is to increase its own utility. We show that when data is limited, building an accurate human model is very challenging, and that a reinforcement learning agent, which is based on this data, does not perform well in practice. Therefore, we propose that the agent should try maximizing a linear combination of the human's utility and its own utility rather than simply trying to maximize only its own utility

The effect of unpleasant experiences on evaluation and behavior

Analyses of the impact of unpleasant experiences reveal two contradictory effects: direct studies of experienced utility reflect overweighting the peak (rare and most extreme) experience, but studies of decisions from experience reflect underweighting of the peak and reliance on the frequent experiences. The present research highlights the role of two contributors to this pattern. First, the results suggest that evaluations are more sensitive to rare events than decisions. It seems that the implied weighting of the peak experiences is a reflection of beliefs that affect evaluation and decisions in different ways. Second, the results show clear indications of underweighting rare events in ongoing decisions, but not in planning decisions. This pattern can be explained with the assertion of beliefs concerning the probability of the peak event is approximately accurate on average, but it changes from trial to trial. The potential value of these results is highlighted with a discussion of safety enhancement in industrial settings

Compaction of single DNA molecules induced by binding of integration host factor (IHF)

We studied the interaction between the integration host factor (IHF), a major nucleoid-associated protein in bacteria, and single DNA molecules. Force–extension measurements of λ DNA and an analysis of the Brownian motion of small beads tethered to a surface by single short DNA molecules, in equilibrium with an IHF solution, indicate that: (i) the DNA–IHF complex retains a random, although more compact, coiled configuration for zero or small values of the tension, (ii) IHF induces DNA compaction by binding to multiple DNA sites with low specificity, and (iii) with increasing tension on the DNA, the elastic properties of bare DNA are recovered. This behavior is consistent with the predictions of a statistical mechanical model describing how proteins bending DNA are driven off by an applied tension on the DNA molecule. Estimates of the amount of bound IHF in DNA–IHF complexes obtained from the model agree very well with independent measurements of this quantity obtained from the analysis of DNA–IHF crosslinking. Our findings support the long-held view that IHF and other histone-like proteins play an important role in shaping the long-scale structure of the bacterial nucleoid

Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq

In multicellular organisms, dedicated regulatory circuits control cell type diversity and responses. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. Here, we present CRISP-seq, an integrated method for massively parallel single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-pooled screens. We show that profiling the genomic perturbation and transcriptome in the same cell enables us to simultaneously elucidate the function of multiple factors and their interactions. We applied CRISP-seq to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors. These include opposing effects of Cebpb and Irf8 in regulating the monocyte/macrophage versus dendritic cell lineages and differential functions for Rela and Stat1/2 in monocyte versus dendritic cell responses to pathogens. This study establishes CRISP-seq as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits