@inproceedings{9646,
  abstract     = {We consider the fundamental problem of deriving quantitative bounds on the probability that a given assertion is violated in a probabilistic program. We provide automated algorithms that obtain both lower and upper bounds on the assertion violation probability. The main novelty of our approach is that we prove new and dedicated fixed-point theorems which serve as the theoretical basis of our algorithms and enable us to reason about assertion violation bounds in terms of pre and post fixed-point functions. To synthesize such fixed-points, we devise algorithms that utilize a wide range of mathematical tools, including repulsing ranking supermartingales, Hoeffding's lemma, Minkowski decompositions, Jensen's inequality, and convex optimization. On the theoretical side, we provide (i) the first automated algorithm for lower-bounds on assertion violation probabilities, (ii) the first complete algorithm for upper-bounds of exponential form in affine programs, and (iii) provably and significantly tighter upper-bounds than the previous approaches. On the practical side, we show our algorithms can handle a wide variety of programs from the literature and synthesize bounds that are remarkably tighter than previous results, in some cases by thousands of orders of magnitude.},
  author       = {Wang, Jinyi and Sun, Yican and Fu, Hongfei and Chatterjee, Krishnendu and Goharshady, Amir Kafshdar},
  booktitle    = {Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation},
  isbn         = {9781450383912},
  location     = {Online},
  pages        = {1171--1186},
  publisher    = {Association for Computing Machinery},
  title        = {{Quantitative analysis of assertion violations in probabilistic programs}},
  doi          = {10.1145/3453483.3454102},
  year         = {2021},
}

@article{9647,
  abstract     = {Gene expression is regulated by the set of transcription factors (TFs) that bind to the promoter. The ensuing regulating function is often represented as a combinational logic circuit, where output (gene expression) is determined by current input values (promoter bound TFs) only. However, the simultaneous arrival of TFs is a strong assumption, since transcription and translation of genes introduce intrinsic time delays and there is no global synchronisation among the arrival times of different molecular species at their targets. We present an experimentally implementable genetic circuit with two inputs and one output, which in the presence of small delays in input arrival, exhibits qualitatively distinct population-level phenotypes, over timescales that are longer than typical cell doubling times. From a dynamical systems point of view, these phenotypes represent long-lived transients: although they converge to the same value eventually, they do so after a very long time span. The key feature of this toy model genetic circuit is that, despite having only two inputs and one output, it is regulated by twenty-three distinct DNA-TF configurations, two of which are more stable than others (DNA looped states), one promoting and another blocking the expression of the output gene. Small delays in input arrival time result in a majority of cells in the population quickly reaching the stable state associated with the first input, while exiting of this stable state occurs at a slow timescale. In order to mechanistically model the behaviour of this genetic circuit, we used a rule-based modelling language, and implemented a grid-search to find parameter combinations giving rise to long-lived transients. Our analysis shows that in the absence of feedback, there exist path-dependent gene regulatory mechanisms based on the long timescale of transients. The behaviour of this toy model circuit suggests that gene regulatory networks can exploit event timing to create phenotypes, and it opens the possibility that they could use event timing to memorise events, without regulatory feedback. The model reveals the importance of (i) mechanistically modelling the transitions between the different DNA-TF states, and (ii) employing transient analysis thereof.},
  author       = {Petrov, Tatjana and Igler, Claudia and Sezgin, Ali and Henzinger, Thomas A and Guet, Calin C},
  issn         = {0304-3975},
  journal      = {Theoretical Computer Science},
  pages        = {1--16},
  publisher    = {Elsevier},
  title        = {{Long lived transients in gene regulation}},
  doi          = {10.1016/j.tcs.2021.05.023},
  volume       = {893},
  year         = {2021},
}

@article{9656,
  abstract     = {Tropisms, growth responses to environmental stimuli such as light or gravity, are spectacular examples of adaptive plant development. The plant hormone auxin serves as a major coordinative signal. The PIN auxin exporters, through their dynamic polar subcellular localizations, redirect auxin fluxes in response to environmental stimuli and the resulting auxin gradients across organs underly differential cell elongation and bending. In this review, we discuss recent advances concerning regulations of PIN polarity during tropisms, focusing on PIN phosphorylation and trafficking. We also cover how environmental cues regulate PIN actions during tropisms, and a crucial role of auxin feedback on PIN polarity during bending termination. Finally, the interactions between different tropisms are reviewed to understand plant adaptive growth in the natural environment.},
  author       = {Han, Huibin and Adamowski, Maciek and Qi, Linlin and Alotaibi, SS and Friml, Jiří},
  issn         = {1469-8137},
  journal      = {New Phytologist},
  number       = {2},
  pages        = {510--522},
  publisher    = {Wiley},
  title        = {{PIN-mediated polar auxin transport regulations in plant tropic responses}},
  doi          = {10.1111/nph.17617},
  volume       = {232},
  year         = {2021},
}

@article{9657,
  abstract     = {To overcome nitrogen deficiency, legume roots establish symbiotic interactions with nitrogen-fixing rhizobia that is fostered in specialized organs (nodules). Similar to other organs, nodule formation is determined by a local maximum of the phytohormone auxin at the primordium site. However, how auxin regulates nodule development remains poorly understood. Here, we found that in soybean, (Glycine max), dynamic auxin transport driven by PIN-FORMED (PIN) transporter GmPIN1 is involved in nodule primordium formation. GmPIN1 was specifically expressed in nodule primordium cells and GmPIN1 was polarly localized in these cells. Two nodulation regulators, (iso)flavonoids trigger expanded distribution of GmPIN1b to root cortical cells, and cytokinin rearranges GmPIN1b polarity. Gmpin1abc triple mutants generated with CRISPR-Cas9 showed impaired establishment of auxin maxima in nodule meristems and aberrant divisions in the nodule primordium cells. Moreover, overexpression of GmPIN1 suppressed nodule primordium initiation. GmPIN9d, an ortholog of Arabidopsis thaliana PIN2, acts together with GmPIN1 later in nodule development to acropetally transport auxin in vascular bundles, fine-tuning the auxin supply for nodule enlargement. Our findings reveal how PIN-dependent auxin transport modulates different aspects of soybean nodule development and suggest that establishment of auxin gradient is a prerequisite for the proper interaction between legumes and rhizobia.},
  author       = {Gao, Z and Chen, Z and Cui, Y and Ke, M and Xu, H and Xu, Q and Chen, J and Li, Y and Huang, L and Zhao, H and Huang, D and Mai, S and Xu, T and Liu, X and Li, S and Guan, Y and Yang, W and Friml, Jiří and Petrášek, J and Zhang, J and Chen, X},
  issn         = {1532-298x},
  journal      = {Plant Cell},
  number       = {9},
  pages        = {2981–3003},
  publisher    = {American Society of Plant Biologists},
  title        = {{GmPIN-dependent polar auxin transport is involved in soybean nodule development}},
  doi          = {10.1093/plcell/koab183},
  volume       = {33},
  year         = {2021},
}

@article{9669,
  abstract     = {The set of known stable phases of water may not be complete, and some of the phase boundaries between them are fuzzy. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuations as well as proton disorder. Such calculations are only made tractable because we combine machine-learning methods and advanced free-energy techniques. The computed phase diagram is in qualitative agreement with experiment, particularly at pressures ≲ 8000 bar, and the discrepancy in chemical potential is comparable with the subtle uncertainties introduced by proton disorder and the spread between the three hybrid functionals. None of the hypothetical ice phases considered is thermodynamically stable in our calculations, suggesting the completeness of the experimental water phase diagram in the region considered. Our work demonstrates the feasibility of predicting the phase diagram of a polymorphic system from first principles and provides a thermodynamic way of testing the limits of quantum-mechanical calculations.},
  author       = {Reinhardt, Aleks and Cheng, Bingqing},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  number       = {1},
  publisher    = {Springer Nature},
  title        = {{Quantum-mechanical exploration of the phase diagram of water}},
  doi          = {10.1038/s41467-020-20821-w},
  volume       = {12},
  year         = {2021},
}

@inproceedings{9678,
  abstract     = {We introduce a new graph problem, the token dropping game, and we show how to solve it efficiently in a distributed setting. We use the token dropping game as a tool to design an efficient distributed algorithm for stable orientations and more generally for locally optimal semi-matchings. The prior work by Czygrinow et al. (DISC 2012) finds a stable orientation in O(Δ^5) rounds in graphs of maximum degree Δ, while we improve it to O(Δ^4) and also prove a lower bound of Ω(Δ). For the more general problem of locally optimal semi-matchings, the prior upper bound is O(S^5) and our new algorithm runs in O(C · S^4) rounds, which is an improvement for C = o(S); here C and S are the maximum degrees of customers and servers, respectively.},
  author       = {Brandt, Sebastian and Keller, Barbara and Rybicki, Joel and Suomela, Jukka and Uitto, Jara},
  booktitle    = {Annual ACM Symposium on Parallelism in Algorithms and Architectures},
  isbn         = {9781450380706},
  location     = { Virtual Event, United States},
  pages        = {129--139},
  title        = {{Efficient load-balancing through distributed token dropping}},
  doi          = {10.1145/3409964.3461785},
  year         = {2021},
}

@article{9679,
  abstract     = {The relative motion of three impenetrable particles on a ring, in our case two identical fermions and one impurity, is isomorphic to a triangular quantum billiard. Depending on the ratio κ of the impurity and fermion masses, the billiards can be integrable or non-integrable (also referred to in the main text as chaotic). To set the stage, we first investigate the energy level distributions of the billiards as a function of 1/κ ∈ [0, 1] and find no evidence of integrable cases beyond the limiting values 1/κ = 1 and 1/κ = 0. Then, we use machine learning tools to analyze properties of probability distributions of individual quantum states. We find that convolutional neural networks can correctly classify integrable and non-integrable states. The decisive features of the wave functions are the normalization and a large number of zero elements, corresponding to the existence of a nodal line. The network achieves typical accuracies of 97%, suggesting that machine learning tools can be used to analyze and classify the morphology of probability densities obtained in theory or experiment.},
  author       = {Huber, David and Marchukov, Oleksandr V. and Hammer, Hans Werner and Volosniev, Artem},
  issn         = {1367-2630},
  journal      = {New Journal of Physics},
  number       = {6},
  publisher    = {IOP Publishing},
  title        = {{Morphology of three-body quantum states from machine learning}},
  doi          = {10.1088/1367-2630/ac0576},
  volume       = {23},
  year         = {2021},
}

@unpublished{9696,
  abstract     = {Most water in the universe may be superionic, and its thermodynamic and transport properties are crucial for planetary science but difficult to probe experimentally or theoretically. We use machine learning and free energy methods to overcome the limitations of quantum mechanical simulations, and characterize hydrogen diffusion, superionic transitions, and phase behaviors of water at extreme conditions. We predict that a close-packed superionic phase with mixed stacking is stable over a wide temperature and pressure range, while a body-centered cubic phase is only thermodynamically stable in a small window but is kinetically favored. Our phase boundaries, which are consistent with the existing-albeit scarce-experimental observations, help resolve the fractions of insulating ice, different superionic phases, and liquid water inside of ice giants.},
  author       = {Cheng, Bingqing and Bethkenhagen, Mandy and Pickard, Chris J. and Hamel, Sebastien},
  booktitle    = {arXiv},
  title        = {{Predicting the phase behaviors of superionic water at planetary conditions}},
  doi          = {10.48550/arXiv.2103.09035},
  year         = {2021},
}

@article{9698,
  abstract     = {Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. This review is written for new and experienced researchers working at the intersection of both fields. We first provide concise tutorials of computational chemistry and machine learning methods, showing how insights involving both can be achieved. We then follow with a critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful (and useful) predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design.},
  author       = {Keith, John A. and Valentin Vassilev-Galindo, Valentin and Cheng, Bingqing and Chmiela, Stefan and Gastegger, Michael and Müller, Klaus-Robert and Tkatchenko, Alexandre},
  issn         = {1520-6890},
  journal      = {Chemical Reviews},
  number       = {16},
  pages        = {9816--9872},
  publisher    = {American Chemical Society},
  title        = {{Combining machine learning and computational chemistry for predictive insights into chemical systems}},
  doi          = {10.1021/acs.chemrev.1c00107},
  volume       = {121},
  year         = {2021},
}

@phdthesis{9733,
  abstract     = {This thesis is the result of the research carried out by the author during his PhD at IST Austria between 2017 and 2021. It mainly focuses on the Fröhlich polaron model, specifically to its regime of strong coupling. This model, which is rigorously introduced and discussed in the introduction, has been of great interest in condensed matter physics and field theory for more than eighty years. It is used to describe an electron interacting with the atoms of a solid material (the strength of this interaction is modeled by the presence of a coupling constant α in the Hamiltonian of the system). The particular regime examined here, which is mathematically described by considering the limit α →∞, displays many interesting features related to the emergence of classical behavior, which allows for a simplified effective description of the system under analysis. The properties, the range of validity and a quantitative analysis of the precision of such classical approximations are the main object of the present work. We specify our investigation to the study of the ground state energy of the system, its dynamics and its effective mass. For each of these problems, we provide in the introduction an overview of the previously known results and a detailed account of the original contributions by the author.},
  author       = {Feliciangeli, Dario},
  issn         = {2663-337X},
  pages        = {180},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The polaron at strong coupling}},
  doi          = {10.15479/at:ista:9733},
  year         = {2021},
}

@article{9746,
  abstract     = {Evolutionary adaptation is a major source of antibiotic resistance in bacterial pathogens. Evolution-informed therapy aims to constrain resistance by accounting for bacterial evolvability. Sequential treatments with antibiotics that target different bacterial processes were previously shown to limit adaptation through genetic resistance trade-offs and negative hysteresis. Treatment with homogeneous sets of antibiotics is generally viewed to be disadvantageous, as it should rapidly lead to cross-resistance. We here challenged this assumption by determining the evolutionary response of Pseudomonas aeruginosa to experimental sequential treatments involving both heterogenous and homogeneous antibiotic sets. To our surprise, we found that fast switching between only β-lactam antibiotics resulted in increased extinction of bacterial populations. We demonstrate that extinction is favored by low rates of spontaneous resistance emergence and low levels of spontaneous cross-resistance among the antibiotics in sequence. The uncovered principles may help to guide the optimized use of available antibiotics in highly potent, evolution-informed treatment designs.},
  author       = {Batra, Aditi and Römhild, Roderich and Rousseau, Emilie and Franzenburg, Sören and Niemann, Stefan and Schulenburg, Hinrich},
  issn         = {2050-084X},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{High potency of sequential therapy with only beta-lactam antibiotics}},
  doi          = {10.7554/elife.68876},
  volume       = {10},
  year         = {2021},
}

@article{9759,
  author       = {Bartlett, Michael John and Arslan, Feyza N and Bankston, Adriana and Sarabipour, Sarvenaz},
  issn         = {1553-7358},
  journal      = {PLoS Computational Biology},
  number       = {7},
  publisher    = {Public Library of Science},
  title        = {{Ten simple rules to improve academic work- life balance}},
  doi          = {10.1371/journal.pcbi.1009124},
  volume       = {17},
  year         = {2021},
}

@article{9761,
  abstract     = {The important roles of mitochondrial function and dysfunction in the process of neurodegeneration are widely acknowledged. Retinal ganglion cells (RGCs) appear to be a highly vulnerable neuronal cell type in the central nervous system with respect to mitochondrial dysfunction but the actual reasons for this are still incompletely understood. These cells have a unique circumstance where unmyelinated axons must bend nearly 90° to exit the eye and then cross a translaminar pressure gradient before becoming myelinated in the optic nerve. This region, the optic nerve head, contains some of the highest density of mitochondria present in these cells. Glaucoma represents a perfect storm of events occurring at this location, with a combination of changes in the translaminar pressure gradient and reassignment of the metabolic support functions of supporting glia, which appears to apply increased metabolic stress to the RGC axons leading to a failure of axonal transport mechanisms. However, RGCs themselves are also extremely sensitive to genetic mutations, particularly in genes affecting mitochondrial dynamics and mitochondrial clearance. These mutations, which systemically affect the mitochondria in every cell, often lead to an optic neuropathy as the sole pathologic defect in affected patients. This review summarizes knowledge of mitochondrial structure and function, the known energy demands of neurons in general, and places these in the context of normal and pathological characteristics of mitochondria attributed to RGCs. },
  author       = {Muench, Nicole A. and Patel, Sonia and Maes, Margaret E and Donahue, Ryan J. and Ikeda, Akihiro and Nickells, Robert W.},
  issn         = {2073-4409},
  journal      = {Cells},
  number       = {7},
  publisher    = {MDPI},
  title        = {{The influence of mitochondrial dynamics and function on retinal ganglion cell susceptibility in optic nerve disease}},
  doi          = {10.3390/cells10071593},
  volume       = {10},
  year         = {2021},
}

@article{9769,
  abstract     = {A few years ago, flow equations were introduced as a technique for calculating the ground-state energies of cold Bose gases with and without impurities. In this paper, we extend this approach to compute observables other than the energy. As an example, we calculate the densities, and phase fluctuations of one-dimensional Bose gases with one and two impurities. For a single mobile impurity, we use flow equations to validate the mean-field results obtained upon the Lee-Low-Pines transformation. We show that the mean-field approximation is accurate for all values of the boson-impurity interaction strength as long as the phase coherence length is much larger than the healing length of the condensate. For two static impurities, we calculate impurity-impurity interactions induced by the Bose gas. We find that leading order perturbation theory fails when boson-impurity interactions are stronger than boson-boson interactions. The mean-field approximation reproduces the flow equation results for all values of the boson-impurity interaction strength as long as boson-boson interactions are weak.},
  author       = {Brauneis, Fabian and Hammer, Hans-Werner and Lemeshko, Mikhail and Volosniev, Artem},
  issn         = {2542-4653},
  journal      = {SciPost Physics},
  number       = {1},
  publisher    = {SciPost Foundation},
  title        = {{Impurities in a one-dimensional Bose gas: The flow equation approach}},
  doi          = {10.21468/scipostphys.11.1.008},
  volume       = {11},
  year         = {2021},
}

@article{9770,
  abstract     = {We study an effective one-dimensional quantum model that includes friction and spin-orbit coupling (SOC), and show that the model exhibits spin polarization when both terms are finite. Most important, strong spin polarization can be observed even for moderate SOC, provided that the friction is strong. Our findings might help to explain the pronounced effect of chirality on spin distribution and transport in chiral molecules. In particular, our model implies static magnetic properties of a chiral molecule, which lead to Shiba-like states when a molecule is placed on a superconductor, in accordance with recent experimental data.},
  author       = {Volosniev, Artem and Alpern, Hen and Paltiel, Yossi and Millo, Oded and Lemeshko, Mikhail and Ghazaryan, Areg},
  issn         = {2469-9969},
  journal      = {Physical Review B},
  number       = {2},
  publisher    = {American Physical Society},
  title        = {{Interplay between friction and spin-orbit coupling as a source of spin polarization}},
  doi          = {10.1103/physrevb.104.024430},
  volume       = {104},
  year         = {2021},
}

@article{9778,
  abstract     = {The hippocampal mossy fiber synapse is a key synapse of the trisynaptic circuit. Post-tetanic potentiation (PTP) is the most powerful form of plasticity at this synaptic connection. It is widely believed that mossy fiber PTP is an entirely presynaptic phenomenon, implying that PTP induction is input-specific, and requires neither activity of multiple inputs nor stimulation of postsynaptic neurons. To directly test cooperativity and associativity, we made paired recordings between single mossy fiber terminals and postsynaptic CA3 pyramidal neurons in rat brain slices. By stimulating non-overlapping mossy fiber inputs converging onto single CA3 neurons, we confirm that PTP is input-specific and non-cooperative. Unexpectedly, mossy fiber PTP exhibits anti-associative induction properties. EPSCs show only minimal PTP after combined pre- and postsynaptic high-frequency stimulation with intact postsynaptic Ca2+ signaling, but marked PTP in the absence of postsynaptic spiking and after suppression of postsynaptic Ca2+ signaling (10 mM EGTA). PTP is largely recovered by inhibitors of voltage-gated R- and L-type Ca2+ channels, group II mGluRs, and vacuolar-type H+-ATPase, suggesting the involvement of retrograde vesicular glutamate signaling. Transsynaptic regulation of PTP extends the repertoire of synaptic computations, implementing a brake on mossy fiber detonation and a “smart teacher” function of hippocampal mossy fiber synapses.},
  author       = {Vandael, David H and Okamoto, Yuji and Jonas, Peter M},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  keywords     = {general physics and astronomy, general biochemistry, genetics and molecular biology, general chemistry},
  number       = {1},
  publisher    = {Springer},
  title        = {{Transsynaptic modulation of presynaptic short-term plasticity in hippocampal mossy fiber synapses}},
  doi          = {10.1038/s41467-021-23153-5},
  volume       = {12},
  year         = {2021},
}

@unpublished{9787,
  abstract     = {We investigate the Fröhlich polaron model on a three-dimensional torus, and give a proof of the second-order quantum corrections to its ground-state energy in the strong-coupling limit. Compared to previous work in the confined case, the translational symmetry (and its breaking in the Pekar approximation) makes the analysis substantially more challenging.},
  author       = {Feliciangeli, Dario and Seiringer, Robert},
  booktitle    = {arXiv},
  title        = {{The strongly coupled polaron on the torus: Quantum corrections to the Pekar asymptotics}},
  doi          = {10.48550/arXiv.2101.12566},
  year         = {2021},
}

@unpublished{9791,
  abstract     = {We provide a definition of the effective mass for the classical polaron described by the Landau-Pekar equations. It is based on a novel variational principle, minimizing the energy functional over states with given (initial) velocity. The resulting formula for the polaron's effective mass agrees with the prediction by Landau and Pekar.},
  author       = {Feliciangeli, Dario and Rademacher, Simone Anna Elvira and Seiringer, Robert},
  booktitle    = {arXiv},
  title        = {{The effective mass problem for the Landau-Pekar equations}},
  doi          = {10.48550/arXiv.2107.03720},
  year         = {2021},
}

@unpublished{9792,
  abstract     = {This paper establishes new connections between many-body quantum systems, One-body Reduced Density Matrices Functional Theory (1RDMFT) and Optimal Transport (OT), by interpreting the problem of computing the ground-state energy of a finite dimensional composite quantum system at positive temperature as a non-commutative entropy regularized Optimal Transport problem. We develop a new approach to fully characterize the dual-primal solutions in such non-commutative setting. The mathematical formalism is particularly relevant in quantum chemistry: numerical realizations of the many-electron ground state energy can be computed via a non-commutative version of Sinkhorn algorithm. Our approach allows to prove convergence and robustness of this algorithm, which, to our best knowledge, were unknown even in the two marginal case. Our methods are based on careful a priori estimates in the dual problem, which we believe to be of independent interest. Finally, the above results are extended in 1RDMFT setting, where bosonic or fermionic symmetry conditions are enforced on the problem.},
  author       = {Feliciangeli, Dario and Gerolin, Augusto and Portinale, Lorenzo},
  booktitle    = {arXiv},
  title        = {{A non-commutative entropic optimal transport approach to quantum composite systems at positive temperature}},
  doi          = {10.48550/arXiv.2106.11217},
  year         = {2021},
}

@article{9793,
  abstract     = {Astrocytes extensively infiltrate the neuropil to regulate critical aspects of synaptic development and function. This process is regulated by transcellular interactions between astrocytes and neurons via cell adhesion molecules. How astrocytes coordinate developmental processes among one another to parse out the synaptic neuropil and form non-overlapping territories is unknown. Here we identify a molecular mechanism regulating astrocyte-astrocyte interactions during development to coordinate astrocyte morphogenesis and gap junction coupling. We show that hepaCAM, a disease-linked, astrocyte-enriched cell adhesion molecule, regulates astrocyte competition for territory and morphological complexity in the developing mouse cortex. Furthermore, conditional deletion of Hepacam from developing astrocytes significantly impairs gap junction coupling between astrocytes and disrupts the balance between synaptic excitation and inhibition. Mutations in HEPACAM cause megalencephalic leukoencephalopathy with subcortical cysts in humans. Therefore, our findings suggest that disruption of astrocyte self-organization mechanisms could be an underlying cause of neural pathology.},
  author       = {Baldwin, Katherine T. and Tan, Christabel X. and Strader, Samuel T. and Jiang, Changyu and Savage, Justin T. and Elorza-Vidal, Xabier and Contreras, Ximena and Rülicke, Thomas and Hippenmeyer, Simon and Estévez, Raúl and Ji, Ru-Rong and Eroglu, Cagla},
  issn         = {1097-4199},
  journal      = {Neuron},
  number       = {15},
  pages        = {2427--2442.e10},
  publisher    = {Elsevier},
  title        = {{HepaCAM controls astrocyte self-organization and coupling}},
  doi          = {10.1016/j.neuron.2021.05.025},
  volume       = {109},
  year         = {2021},
}