Modern science is formally structured around scholarly publication, where scientific knowledge is canonized through citation. Precisely how citations are given and accrued can provide information about the value of discovery, the history of scientific ideas, the structure of fields, and the space or scope of inquiry. Yet parsing this information has been challenging because citations are not simply present or absent; rather, they differ in purpose, function, and sentiment. In this paper, we investigated how critical and favorable sentiments were distributed across citations, and tested the hypothesis that more favorable sentiment would be utilized among ingroup members, whereas more critical sentiment would be utilized toward outgroup members. We considered three group types: collaborators, those with a similar h-index, and those with the same gender. We observed that citation sentiment was more favorable to collaborators than non-collaborators, an effect that was modulated by both gender and hindex. Further, we observed that disciplinary and country-level factors impacting a scholar's perception of the size of their ingroup also explained citation sentiment: Largely experimental fields that engage in regular scholarly synthesis through review articles employed less citation sentiment, as did countries with more collectivist attitudes and greater acceptance of social hierarchies. Collectively, we demonstrated how sociocultural groups displayed ingroup preferences in the use of sentiment in scientific communication. Our study contributes to a broader understanding of how human factors influence the practice of science, and underscores the importance of considering the larger sociocultural contexts in which science progresses.

Multipartite entanglement is an essential aspect of quantum systems, needed to execute quantum algorithms, implement error correction, and achieve quantum-enhanced sensing. In solid-state quantum registers such nitrogen-vacancy (NV) centers in diamond, entangled states are typically created using sequential, pairwise gates between the central electron and individual nuclear qubits. This sequential approach is slow and suffers from crosstalk errors. Here, we demonstrate a parallelized multi-qubit entangling gate to generate a four-qubit GHZ state using a room-temperature NV center in only 14.8 μs - 10 times faster than using sequences of two-qubit gates. The entangled states are verified by measuring multiple quantum coherences. Two-qubit entangling gates have an average fidelity of 0.96(1), and the four-qubit parallel gate has a fidelity of 0.92(4), whereas the sequential four-qubit gate fidelity is only 0.69(3). The approach is generalizable to other solid-state platforms, and it lays the foundation for scalable generation and control of entanglement in practical devices.

Prions are misfolded proteins that transmit their structural arrangement to neighboring proteins. In biological systems, prion dynamics can produce a variety of complex functional outcomes. Yet, an understanding of prionic causes has been hampered by the fact that few computational models exist that allow for experimental design, hypothesis testing, and control. Here, we identify essential prionic properties and present a biologically inspired model of prions using simple mechanical structures capable of undergoing complex conformational change. We demonstrate the utility of our approach by designing a prototypical mechanical prion and validating its properties experimentally. Our work provides a design framework for harnessing and manipulating prionic properties in natural and artificial systems.

Mitochondria are essential for bioenergetics and cellular processes including cell differentiation and immunity; alterations in these processes cause a wide range of muscular and neurological pathologies. Although these pathologies have traditionally been associated with ATP deficits, mitochondrial dysfunction also leads to reactive oxygen species (ROS) generation, inflammation, and alterations in the function of other organelles. Although the negative impact of mitochondrial dysfunction on lysosomal activity is established, the relationship between mitochondria and the rest of the endocytic compartment remains poorly understood. Here, we show that inhibiting mitochondrial activity through genetic and chemical approaches causes early endosome (EE) perinuclear aggregation and impairs cargo delivery to lysosomes. This impairment is due to ROS-mediated alterations in microtubule architecture and centrosome dynamics. Antioxidants can rescue these EE defects, underlying the pivotal role of mitochondria in maintaining cellular activities through ROS regulation of microtubule networks. Our findings highlight the significance of mitochondria beyond ATP production, emphasizing their critical involvement in endocytic trafficking and cellular homeostasis. These insights emphasize mitochondria's critical involvement in cellular activities and suggest novel targets for therapies to mitigate the effects of mitochondrial dysfunction.

Mitochondria are essential for bioenergetic functions and various cellular processes, including differentiation and immunity, their dysfunction leading to several pathologies. While these pathologies have traditionally been associated with ATP deficits, mitochondrial dysfunction also leads to reactive oxygen species (ROS) generation, inflammation, and alterations the function of other organelles. While the negative impact of mitochondrial dysfunction on lysosomal activity has been established, the relationship between mitochondria and the rest of the endocytic compartment remains poorly understood. Here, we show that inhibiting mitochondrial activity through genetic and chemical approaches causes early endosome (EE) perinuclear aggregation and impairs cargo delivery to lysosomes. This impairment is due to altered microtubule architecture and centrosome dynamics, mediated by ROS. Antioxidants can rescue these EE defects, underlying the pivotal role of mitochondria in maintaining cellular activities through ROS regulation of microtubule networks. Our findings highlight the significance of mitochondria beyond ATP production, emphasizing their critical involvement in endocytic trafficking and cellular homeostasis. These insights emphasize mitochondria's critical involvement in cellular activities and suggest novel targets for therapies to mitigate the effects of mitochondrial dysfunction. ### Competing Interest Statement The authors have declared no competing interest.

In interacting dynamical systems, specific local interaction rules for system components give rise to diverse and complex global dynamics. Long dynamical cycles are a key feature of many natural interacting systems, especially in biology. Examples of dynamical cycles range from circadian rhythms regulating sleep to cell cycles regulating reproductive behavior. Despite the crucial role of cycles in nature, the properties of network structure that give rise to cycles still need to be better understood. Here, we use a Boolean interaction network model to study the relationships between network structure and cyclic dynamics. We identify particular structural motifs that support cycles, and other motifs that suppress them. More generally, we show that the presence of dynamical reflection symmetry in the interaction network enhances cyclic behavior. In simulating an artificial evolutionary process, we find that motifs that break reflection symmetry are discarded. We further show that dynamical reflection symmetries are over-represented in Boolean models of natural biological systems. Altogether, our results demonstrate a link between symmetry and functionality for interacting dynamical systems, and they provide evidence for symmetry's causal role in evolving dynamical functionality.

Nuclear quadrupolar resonance (NQR) spectroscopy reveals chemical bonding patterns in materials and molecules through the unique coupling between nuclear spins and local fields. However, traditional NQR techniques require macroscopic ensembles of nuclei to yield a detectable signal, which obscures molecule-to-molecule variations. Solid-state spin qubits, such as the nitrogen-vacancy (NV) center in diamond, facilitate the detection and control of individual nuclei through their local magnetic couplings. Here, we use NV centers to perform NQR spectroscopy on their associated nitrogen-14 (14N) nuclei at room temperature. In mapping the nuclear quadrupolar Hamiltonian, we resolve minute variations between individual nuclei. The measurements reveal correlations between the Hamiltonian parameters associated with the NV center's electronic and nuclear spin states, as well as a previously unreported symmetry-breaking quadrupolar term. We further design pulse sequences to initialize, read out, and control the quantum evolution of the 14N nuclear state using the nuclear quadrupolar Hamiltonian.

Modern science is formally structured around scholarly publication, where scientific knowledge is canonized through citation. Precisely how citations are given and accrued can provide information about the value of discovery, the history of scientific ideas, the structure of fields, and the space or scope of inquiry. Yet parsing this information has been challenging because citations are not simply present or absent; rather, they differ in purpose, function, and sentiment. In this paper, we investigate how critical and favorable sentiments are distributed across citations, and demonstrate that citation sentiment tracks sociocultural norms across scales of collaboration, discipline, and country. At the smallest scale of individuals, we find that researchers cite scholars they have collaborated with more favorably (and less critically) than scholars they have not collaborated with. Outside collaborative relationships, higher h-index scholars cite lower h-index scholars more critically. At the mesoscale of disciplines, we find that wetlab disciplines tend to be less critical than drylab disciplines, and disciplines that engage in more synthesis through publishing more review articles tend to be less critical. At the largest scale of countries, we find that greater individualism (and lesser acceptance of the unequal distribution of power) is associated with more critical sentiment. Collectively, our results demonstrate how sociocultural factors can explain variations in sentiment in scientific communication. As such, our study contributes to the broader understanding of how human factors influence the practice of science, and underscore the importance of considering the larger sociocultural contexts in which science progresses.

Nanodiamonds containing nitrogen-vacancy (NV) centers can serve as colloidal quantum sensors of local fields in biological and chemical environments. However, nanodiamond surfaces are challenging to modify without degrading their colloidal stability or the NV center's optical and spin properties. Here, we report a simple and general method to coat nanodiamonds with a thin emulsion layer that preserves their quantum features, enhances their colloidal stability, and provides functional groups for subsequent crosslinking and click-chemistry conjugation reactions. To demonstrate this technique, we decorate the nanodiamonds with combinations of carboxyl- and azide-terminated amphiphiles that enable conjugation using two different strategies. We study the effect of the emulsion layer on the NV center's spin lifetime, and we quantify the nanodiamonds' chemical sensitivity to paramagnetic ions using $T_1$ relaxometry. This general approach to nanodiamond surface functionalization will enable advances in quantum nanomedicine and biological sensing.

Across all scales of the physical world, dynamical systems can be usefully represented as abstract networks that encode the systems' units and interunit interactions. Understanding how physical rules shape the topological structure of those networks can clarify a system's function and enhance our ability to design, guide, or control its behavior. In the emerging area of quantum network science, a key challenge lies in distinguishing between the topological properties that reflect a system's underlying physics and those that reflect the assumptions of the employed conceptual model. To elucidate and address this challenge, we study networks that represent nonequilibrium quantum-electronic transport through quantum antidot devices-an example of an open, mesoscopic quantum system. The network representations correspond to two different models of internal antidot states: a single-particle, noninteracting model and an effective model for collective excitations including Coulomb interactions. In these networks, nodes represent accessible energy states and edges represent allowed transitions. We find that both models reflect spin conservation rules in the network topology through bipartiteness and the presence of only even-length cycles. The models diverge, however, in the minimum length of cycle basis elements, in a manner that depends on whether electrons are considered to be distinguishable. Furthermore, the two models reflect spin-conserving relaxation effects differently, as evident in both the degree distribution and the cycle-basis length distribution. Collectively, these observations serve to elucidate the relationship between network structure and physical constraints in quantum-mechanical models. More generally, our approach underscores the utility of network science in understanding the dynamics of quantum systems.

Intrinsically motivated exploration has proven useful for reinforcement learning, even without additional extrinsic rewards. When the environment is naturally represented as a graph, how to guide exploration best remains an open question. In this work, we propose a novel approach for exploring graph-structured data motivated by two theories of human curiosity: the information gap theory and the compression progress theory. The theories view curiosity as an intrinsic motivation to optimize for topological features of subgraphs induced by nodes visited in the environment. We use these proposed features as rewards for graph neural-network-based reinforcement learning. On multiple classes of synthetically generated graphs, we find that trained agents generalize to longer exploratory walks and larger environments than are seen during training. Our method computes more efficiently than the greedy evaluation of the relevant topological properties. The proposed intrinsic motivations bear particular relevance for recommender systems. We demonstrate that next-node recommendations considering curiosity are more predictive of human choices than PageRank centrality in several real-world graph environments.

Theoretical constructs, such as the information gap theory and compression progress theory, seek to explain how humans practice curiosity. According to the former, curiosity is the drive to acquire information missing from our understanding of the world. According to the latter, curiosity is the drive to construct parsimonious mental world models. To complement the densification and simplification processes inherent to these frameworks, we propose the conformational change theory, wherein we posit that curiosity builds mental models with marked conceptual flexibility. We formalize curiosity as a knowledge-network-building process to investigate each theoretical account for individuals and collectives. In knowledge networks, gaps can be identified as topological cavities, compression progress can be quantified using network compressibility, and flexibility can be measured as the number of conformational degrees of freedom. We find that curiosity fills gaps and constructs increasingly compressible and flexible knowledge networks. Across individuals and collectives, we determine the contexts in which each account is explanatory, clarifying their complementary and distinct contributions. Our findings offer a novel networks-based perspective that harmonizes with (and compels an expansion of) the traditional taxonomy of curiosity.

Recent work has demonstrated that the relationship between structural and functional connectivity varies regionally across the human brain, with reduced coupling emerging along the sensory-association cortical hierarchy. The biological underpinnings driving this expression, however, remain largely unknown. Here, we postulate that intracortical myelination and excitation-inhibition (EI) balance mediate the heterogeneous expression of structure-function coupling (SFC) and its temporal variance across the cortical hierarchy. We employ atlas- and voxel-based connectivity approaches to analyze neuroimaging data acquired from two groups of healthy participants. Our findings are consistent across six complementary processing pipelines: 1) SFC and its temporal variance respectively decrease and increase across the unimodal-transmodal and granular-agranular gradients; 2) increased myelination and lower EI-ratio are associated with more rigid SFC and restricted moment-to-moment SFC fluctuations; 3) a gradual shift from EI-ratio to myelination as the principal predictor of SFC occurs when traversing from granular to agranular cortical regions. Collectively, our work delivers a framework to conceptualize structure-function relationships in the human brain, paving the way for an improved understanding of how demyelination and/or EI-imbalances induce reorganization in brain disorders.

Mathieu Ouellet, Jason Z. Kim, Harmange Guillaume, 4 Sydney M. Shaffer, 4, 5 Lee C. Bassett, 6 and Dani S. Bassett 2, 6, 7, 8, 9, 10 Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104 USA Department of Biological Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104 USA Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Cell and Molecular Biology Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Co-contributors. Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104 USA Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA Santa Fe Institute, Santa Fe, NM 87501 USA∗ (Dated: February 25, 2022)

From the perfect radial symmetries of radiolarian mineral skeletons to the broken symmetry of homochirality, the logic of Nature's regularities has fascinated scientists for centuries. Some of Nature's symmetries are clearly visible in morphology and physical structure, whereas others are hidden in the network of interactions among system components. Just as visible symmetries and asymmetries contribute to the system's beauty, might hidden symmetries contribute to the system's functional harmony? And if so, how? Here we demonstrate that the interaction networks of biological systems from cell signaling to cancer display a form of dynamical reflection symmetry that serves to expand their dynamical complexity. The expansion proceeds according to precise rules regarding the lengths of dynamical cycles, made possible by a peculiar imbalance between excitation and inhibition. To probe the conditions under which this reflection symmetry evolves, we use a multi-objective genetic algorithm to produce networks with long dynamical cycles. We find that local structural motifs that break the reflection symmetry are deleted in the evolutionary process, providing evidence for symmetry's causal role in dynamical complexity. Finally, we identify symmetries in real continuous-valued scRNA-seq data of gene expression in drug-resistant cancer cells. Broadly, our work reveals a class of hidden symmetries in biology, present in the network of interactions among system components, and it underscores their functional importance. Mathematically simple and computational inexpensive, our approach is applicable to the types of biological data commonly acquired in modern experiments.

Curiosity is an internally motivated search for information. It is enduring and open-ended, and may have evolved to help us build accurate mental representations of our ever-changing environments. Due to the significant role that curiosity plays in our lives, several theoretical constructs, such as the information gap theory and compression progress theory, have sought to explain how we engage in its practice. According to the former, curiosity is the drive to acquire information that is missing from our understanding of the world. According to the latter, curiosity is the drive to construct an increasingly parsimonious mental model of the world. To complement the densification processes inherent to these two theories, we propose the conformational change theory, wherein we posit that the practice of curiosity results in mental models with marked conceptual flexibility. To validate these three theories, we must overcome the fundamental challenge of constructing formal models of mental representations of knowledge. Here, we address that challenge by formalizing curiosity as the process of building a growing knowledge network. We then quantitatively investigate information gap theory, compression progress theory, and the conformational change theory of curiosity. In knowledge networks, gaps can be identified as topological cavities, compression progress can be quantified using network compressibility, and flexibility can be measured as the number of conformational degrees of freedom. We leverage data acquired from the online encyclopedia Wikipedia to determine the degree to which each theory explains the growth of knowledge networks built by individuals and by collectives. Our findings lend support to a pluralistic view of curiosity, wherein intrinsically motivated information acquisition fills knowledge gaps and simultaneously leads to increasingly compressible and flexible knowledge networks. Across individuals and collectives, we determine the contexts in which each theoretical account may be explanatory, thereby clarifying their complementary and distinct explanations of curiosity. Our findings offer a novel network theoretical perspective on intrinsically motivated information acquisition that may harmonize with or compel an expansion of the traditional taxonomy of curiosity. premised on the conformational change theory—can be quantified as the number of conformational degrees of freedom. We use data acquired from Wikipedia to construct growing knowledge networks for individuals and for collectives. We find that as networks grow, knowledge gaps increase in number, suggesting an expanding interior of ignorance. Yet, in support of an aversion to gaps predicted by information gap theory, we also find fewer-than-expected disconnected network components (or 0-dimensional topological cavities) and fewer-than-expected loops of edges (or 1-dimensional topological cavities) in growing knowledge networks. This set of findings suggests that knowledge “gaps” as conceptualized by information gap theory may best translate, in a network theoretical sense, to 0 and 1-dimensional cavities. We also find that growing individual knowledge networks possess greater-than-expected compressibility, indicating that information acquisition is driven to construct parsimonious mental world models. In addition, we find that knowledge networks built by individuals become increasingly flexible with growth, foregrounding the longstanding relevance of conformational change in the mind. Our results lend support to a pluralistic view of curiosity, wherein intrinsically motivated information acquisition fills knowledge gaps and builds increasingly compressible and flexible mental representations of the world. Our findings offer a novel network theoretical perspective on intrinsically motivated information acquisition that may harmonize with or compel an expansion of the classical taxonomy of curiosity.

Cortical variations in cytoarchitecture form a sensory-fugal axis that shapes regional profiles of extrinsic connectivity and is thought to guide signal propagation and integration across the cortical hierarchy. While neuroimaging work has shown that this axis constrains local properties of the human connectome, it remains unclear whether it also shapes the asymmetric signaling that arises from higher-order topology. Here, we used network control theory to examine the amount of energy required to propagate dynamics across the sensory-fugal axis. Our results revealed an asymmetry in this energy, indicating that bottom-up transitions were easier to complete compared to top-down. Supporting analyses demonstrated that asymmetries were underpinned by a connectome topology that is wired to support efficient bottom-up signaling. Lastly, we found that asymmetries correlated with differences in communicability and intrinsic neuronal time scales and lessened throughout youth. Our results show that cortical variation in cytoarchitecture may guide the formation of macroscopic connectome topology.

Racial discrimination in housing has long fueled disparities in homeownership and wealth in the United States. Now, automated algorithms play a dominant role in rental and lending decisions. Advocates of these technologies argue that mortgage lending algorithms reduce discrimination. However, “errors in background check reports persist and remain pervasive,” and algorithms are at risk for inheriting prejudices from society and reflect pre-existing patterns of inequality. Additionally, algorithmic discrimination is often challenging to identify and difficult to explain or prosecute in court. While the Federal Trade Commission (FTC) is responsible for prosecuting this type of discrimination under the Fair Credit Reporting Act (FCRA), their enforcement regime “has inadequately regulated industry at the federal and state level and failed to provide consumers access to justice at an individual level,” as evidenced by its mere eighty-seven enforcement actions in the past forty years. In comparison, 4,531 lawsuits have been brought under the FCRA by other groups in 2018 alone. Therefore, the FTC must update its policies to ensure it can identify, prosecute, and facilitate third-party lawsuits against a primary driver of housing discrimination in the 21st century: discrimination within algorithmic decision making. We recommend that the FTC issue a rule requiring companies to publish a data plan with all consumer reporting products. Currently, the FTC recommends that companies make an internal assessment of the components of the proposed data plan to ensure that they are not in violation of the FCRA. Therefore, requiring that these plans be published publicly does not place undue burden on companies and empowers consumers to advocate for themselves and report unfair practices to the FTC. Coupled together, these will reduce the costs of investigation and enforcement by the FTC and decrease the discriminatory impact of automated decision systems on marginalized communities.

Mitochondrial DNA (mtDNA) maintenance is essential to sustain a functionally healthy population of mitochondria within cells. Proper mtDNA replication and distribution within mitochondrial networks are essential to maintain mitochondrial homeostasis. However, the fundamental basis of mtDNA segregation and distribution within mitochondrial networks is still unclear. To address these questions, we developed an algorithm, Mitomate tracker to unravel the global distribution of nucleoids within mitochondria. Using this tool, we decipher the semi-regular spacing of nucleoids across mitochondrial networks. Furthermore, we show that mitochondrial fission actively regulates mtDNA distribution by controlling the distribution of nucleoids within mitochondrial networks. Specifically, we found that primary cells bearing disease-associated mutations in the fission proteins DRP1 and MYH14 show altered nucleoid distribution, and acute enrichment of enlarged nucleoids near the nucleus. Further analysis suggests that the altered nucleoid distribution observed in the fission mutants is the result of both changes in network structure and nucleoid density. Thus, our study provides novel insights into the role of mitochondria fission in nucleoid distribution and the understanding of diseases caused by fission defects. Significance statement Mutation or deletion of mitochondrial DNA (mtDNA) is associated with a large number of human diseases. However, the mechanisms controlling mtDNA replication and segregation are still poorly understood. Here, we have developed a new computational method to quantify the distribution of nucleoids (mtDNA with associated proteins) and define how nucleoid distribution is affected by changes in mitochondrial network structure. We demonstrate that mitochondrial fission is required for the proper distribution of nucleoids across mitochondrial networks, cells from patients with fission defects showing irregular nucleoid distribution and perinuclear accumulation. Nonetheless, each fission mutant behaved in a distinct manner, indicating a complex relationship between mitochondrial dynamics and nucleoid distribution.

Mitochondrial DNA (mtDNA) maintenance is essential to sustain a functionally healthy population of mitochondria within cells. Proper mtDNA replication and distribution within mitochondrial networks are essential to maintain mitochondrial homeostasis. However, the fundamental basis of mtDNA segregation and distribution within mitochondrial networks is still unclear. To address these questions, we developed an algorithm, Mitomate tracker to unravel the global distribution of nucleoids within mitochondria. Using this tool, we decipher the semi-regular spacing of nucleoids across mitochondrial networks. Furthermore, we show that mitochondrial fission actively regulates mtDNA distribution by controlling the distribution of nucleoids within mitochondrial networks. Specifically, we found that primary cells bearing disease-associated mutations in the fission proteins DRP1 and MYH14 show altered nucleoid distribution, and acute enrichment of enlarged nucleoids near the nucleus. Further analysis suggests that the altered nucleoid distribution observed in the fission mutants is the result of both changes in network structure and nucleoid density. Thus, our study provides novel insights into the role of mitochondria fission in nucleoid distribution and the understanding of diseases caused by fission defects.