cssi/SciSciGPT-SciSciNet huggingface dataset:
Programmable patterns in a DNA-based reaction–diffusion system

Biology offers compelling proof that macroscopic "living materials" can emerge from reactions between diffusing biomolecules. Here, we show that molecular self-organization could be a similarly powerful approach for engineering functional synthetic materials. We introduce a programmable DNA embedded hydrogel that produces tunable patterns at the centimeter length scale. We generate these patterns by implementing chemical reaction networks through synthetic DNA complexes, embedding the complexes in the hydrogel, and triggering with locally applied input DNA strands. We first demonstrate ring pattern formation around a circular input cavity and show that the ring width and intensity can be predictably tuned. Then, we create patterns of increasing complexity, including concentric rings and non-isotropic patterns. Finally, we show "destructive" and "constructive" interference patterns, by combining several ring-forming modules in the gel and triggering them from multiple sources. We further show that computer simulations based on the reaction-diffusion model can predict and inform the programming of target patterns.
The Role of Evolving Interfacial Substrate Properties on Heterogeneous Cellulose Hydrolysis Kinetics

Interfacial enzyme reactions require formation of an enzyme-substrate complex at the surface of a heterogeneous substrate, but often multiple modes of enzyme binding and types of binding sites comp...
State Prosecutors at the Center of Mass Imprisonment and Criminal Justice Reform

State prosecutors around the country have played a crucial role in mass imprisonment. Little supervision and virtually unsurpassed decision making power have provided them with unrivaled influence over the size, growth, and composition of our criminal justice system. They decide which cases to prosecute, whether to divert a case, whether to offer a plea, and what sentence to recommend. Their impact does not stop at sentencing. They weigh in on alternative dockets, supervision violations, parole release, and even clemency requests. But they are also part of a larger system that constrains them. Funding, judicial limits on their power, and legislative grants of authority to other players in the criminal justice system all serve to limit the freedom of prosecutors. The public health threat COVID-19 presents to those detained in jails and prisons has turned into a case study of prosecutorial authority. It powerfully displays the sway political ideology, divergent purposes of punishment, and public safety considerations hold over release decisions. The prosecutors most successful in decreasing inmate population numbers quickly have been not only proactive but also able to build effective coalitions with other criminal justice actors. Whether COVID-19 will in the long run lead to smaller jail populations and shorter prison terms remains an open question. Yet, it further reinforces and strengthens the role of prosecutors whose expansive reach into our communities—with an eye to incarceration or decarceration—continues to be a powerful feature of the American criminal justice system.
Childhood Medicaid Coverage and Later Life Health Care Utilization

Exploiting a discontinuity in childhood Medicaid eligibility based on date of birth, we find that more years of childhood eligibility are associated with fewer hospitalizations in adulthood. For blacks, we find a 7-15% decrease in hospitalizations and a suggestive 2-5% decrease in emergency department visits, but no similar effect for non-blacks. The effects are pronounced for utilization related to chronic illnesses and for patients living in low-income zip codes. Calculations suggest that lower rates of hospitalizations during one year in adulthood for blacks offset between 2 and 4 percent of the initial costs of expanding Medicaid for all children.
Detection of anomalous high-frequency events in human intracranial EEG.

Author(s): Charupanit, Krit; Sen-Gupta, Indranil; Lin, Jack J; Lopour, Beth A | Abstract: ObjectiveHigh-frequency oscillations (HFOs) are a promising biomarker for the epileptogenic zone. However, no physiological definition of an HFO has been established, so detection relies on the empirical definition of an HFO derived from visual observation. This can bias estimates of HFO features such as amplitude and duration, thereby hindering their utility as biomarkers. Therefore, we set out to develop an algorithm that detects high-frequency events in the intracranial EEG that are morphologically distinct from background without requiring assumptions about event amplitude or shape.MethodWe propose the anomaly detection algorithm (ADA), which uses unsupervised machine learning to identify segments of data that are distinct from the background. We apply ADA and a standard HFO detector using a root mean square amplitude threshold to intracranial EEG from 11 patients undergoing evaluation for epilepsy surgery. The rate, amplitude, and duration of the detected events and the percent overlap between the two detectors are compared.ResultIn the seizure onset zone (SOZ), ADA detected a subset of conventional HFOs. In non-SOZ channels, ADA detected at least twice as many events as the standard approach, including some conventional HFOs; however, ADA also identified many low and intermediate amplitude events missed by the standard amplitude-based method. The rate of ADA events was similar across all channels; however, the amplitude of ADA events was significantly higher in SOZ channels (Pnln.0045), and the amplitude measurement was more stable over time than the HFO rate, as indicated by a lower coefficient of variation (Pnln.0125).SignificanceADA does not require human supervision, parameter optimization, or prior assumptions about event shape, amplitude, or duration. Our results suggest that the algorithm's estimate of event amplitude may differentiate SOZ and non-SOZ channels. Further studies will examine the utility of HFO amplitude as a biomarker for epilepsy surgical outcome.
Chapter 12 – Ecology

Publisher Summary This chapter explains why there are so many species, why a given set of species occurs in a particular area, and how those species interact and persist. Ecological studies typically deal with assemblages of individuals of a single species (populations), the set of species in a given taxon living in a particular area or habitat (assemblages), or all species in some defined area (communities). Populations have characteristics that communities do not have, including population growth rates, survivorship schedules, birth rates, and replacement rates. Although, communities are composed of sets of species that are producers (plants), primary consumers (herbivores), secondary consumers (carnivores), and decomposers (bacteria). The terms “community and assemblage” are often interchanged, and most community studies of amphibians or reptiles are actually studies of assemblages. The term “assemblage” is usually applied to a taxonomic subset of species in a community. As adults, amphibians and reptiles are mainly primary and secondary predators, eating other consumers and in turn being eaten. Larvae of most anurans and some adult reptiles are herbivores. Consequently, herpetological assemblages occupy the middle region of the trophic chain or food web.
Computing Feasible Trajectories for an Articulated Probe in Three Dimensions.

Consider an input consisting of a set of $n$ disjoint triangular obstacles in $\mathbb{R}^3$ and a target point $t$ in the free space, all enclosed by a large sphere $S$ of radius $R$ centered at $t$. An articulated probe is modeled as two line segments $ab$ and $bc$ connected at point $b$. The length of $ab$ can be equal to or greater than $R$, while $bc$ is of a given length $r \leq R$. The probe is initially located outside $S$, assuming an unarticulated configuration, in which $ab$ and $bc$ are collinear and $b \in ac$. The goal is to find a feasible (obstacle-avoiding) probe trajectory to reach $t$, with the condition that the probe is constrained by the following sequence of moves -- a straight-line insertion of the unarticulated probe into $S$, possibly followed by a rotation of $bc$ at $b$ for at most $\pi/2$ radians, so that $c$ coincides with $t$. We prove that if there exists a feasible probe trajectory, then a set of extremal feasible trajectories must be present. Through careful case analysis, we show that these extremal trajectories can be represented by $O(n^4)$ combinatorial events. We present a solution approach that enumerates and verifies these combinatorial events for feasibility in overall $O(n^{4+\epsilon})$ time using $O(n^{4+\epsilon})$ space, for any constant $\epsilon > 0$. The enumeration algorithm is highly parallel, considering that each combinatorial event can be generated and verified for feasibility independently of the others. In the process of deriving our solution, we design the first data structure for addressing a special instance of circular sector emptiness queries among polyhedral obstacles in three dimensional space, and provide a simplified data structure for the corresponding emptiness query problem in two dimensions.
An Efficiency Approach to the Evaluation of Policy Changes

This paper describes an efficiency approach to the evaluation of policy changes. Rather than comparing the utility allocations that arise before and after a policy change is introduced, this approach evaluates a policy change by comparing it with other possible changes which might be made from the status quo. The main merit of the approach is that it is founded on the Pareto criterion rather than on a distributional value judgement. The paper provides a precise statement of the approach and applies it to a number of examples. Some objections to the approach are also anticipated and discussed.
Applying knowledge-driven mechanistic inference to toxicogenomics

When considering toxic chemicals in the environment, a mechanistic, causal explanation of toxicity may be preferred over a statistical or machine learning-based prediction by itself. Elucidating a mechanism of toxicity is, however, a costly and time-consuming process that requires the participation of specialists from a variety of fields, often relying on animal models. We present an innovative mechanistic inference framework (MechSpy), which can be used as a hypothesis generation aid to narrow the scope of mechanistic toxicology analysis. MechSpy generates hypotheses of the most likely mechanisms of toxicity, by combining a semantically-interconnected knowledge representation of human biology, toxicology and biochemistry with gene expression time series on human tissue. Using vector representations of biological entities, MechSpy seeks enrichment in a manually curated list of high-level mechanisms of toxicity, represented as biochemically- and causally-linked ontology concepts. Besides predicting the canonical mechanism of toxicity for many well-studied compounds, we experimentally validated some of our predictions for other chemicals without an established mechanism of toxicity. This mechanistic inference framework is an advantageous tool for predictive toxicology, and the first of its kind to produce a mechanistic explanation for each prediction. MechSpy can be modified to include additional mechanisms of toxicity, and is generalizable to other types of mechanisms of human biology.
DISTRIBUTION AND HABITABILITY OF (META)STABLE BRINES ON PRESENT-DAY MARS.

Special Regions on Mars are defined as environments able to host liquid water that simultaneously meets certain temperature and water activity requirements that allow known terrestrial organisms to replicate1,2 and therefore could be habitable. Such regions would be of concern for planetary protection policies owing to the potential for forward contamination (biological contamination from Earth). Pure liquid water is unstable on the Martian surface3,4 but brines may be present3,5. Experimental work has shown that brines persist beyond their predicted stability region, leading to metastable liquids6–8. Here we show that (meta)stable brines can form and persist from the equator to high latitudes on the surface of Mars for a few percent of the year for up to six consecutive hours, a broader range than previously thought9,10. However, only the lowest eutectic solutions can form, leading to brines with temperatures of less than 225 K. Our results indicate that (meta)stable brines on the Martian surface and its shallow subsurface (a few centimetres deep) are not habitable because their water activities and temperatures fall outside the known tolerances for terrestrial life. Furthermore, (meta)stable brines do not meet the Special Region requirements, reducing the risk of forward contamination and easing threats related to the exploration of the Martian surface. A map of the stability of brines on Mars, obtained by combining thermodynamic and climate modelling, shows that some brines can stay liquid for longer than previously thought, particularly at high northern latitudes. However, they are not habitable to known terrestrial life, and can be explored without risk of biological contamination from Earth.
Best-of-three contest experiments: Strategic versus psychological momentum

Abstract We conduct an experimental analysis of a best-of-three Tullock contest. Intermediate prizes lead to higher efforts, while increasing the role of luck (as opposed to effort) leads to lower efforts. Both intermediate prizes and luck reduce the probability of the contest ending in two rounds. The patterns of players' efforts and the probability that a contest ends in two rounds are consistent with ‘strategic momentum’, i.e., a momentum generated due to strategic incentives inherent in the contest. We do not find evidence for ‘psychological momentum’, i.e., a momentum which emerges when winning affects players' confidence. Similar to the previous studies of contests, we find significantly higher efforts than predicted and strong heterogeneity in effort between the subjects.
The Trilemma in History: Tradeoffs among Exchange Rates, Monetary Policies, and Capital Mobility

The exchange-rate regime is often seen as constrained by the monetary policy trilemma, which imposes a stark tradeoff among exchange stability, monetary independence, and capital market openness. Yet the trilemma has not gone without challenge. Some argue that under the modern float there could be limited monetary autonomy; others, that even under the classical gold standard domestic monetary autonomy was considerable. This paper studies the coherence of international interest rates over more than 130 years. The constraints implied by the trilemma are largely borne out by history.
Dual Role of Auxin in Regulating Plant Defense and Bacterial Virulence Gene Expression During Pseudomonas syringae PtoDC3000 Pathogenesis

Modification of host hormone biology is a common strategy used by plant pathogens to promote disease. For example, the bacterial pathogen strain Pseudomonas syringae DC3000 (PtoDC3000) produces the plant hormone auxin (indole-3-acetic acid [IAA]) to promote PtoDC3000 growth in plant tissue. Previous studies suggest that auxin may promote PtoDC3000 pathogenesis through multiple mechanisms, including both suppression of salicylic acid (SA)-mediated host defenses and via an unknown mechanism that appears to be independent of SA. To test if host auxin signaling is important during pathogenesis, we took advantage of Arabidopsis thaliana lines impaired in either auxin signaling or perception. We found that disruption of auxin signaling in plants expressing an inducible dominant axr2-1 mutation resulted in decreased bacterial growth and that this phenotype was suppressed by introducing the sid2-2 mutation, which impairs SA synthesis. Thus, host auxin signaling is required for normal susceptibility to PtoDC3000 and is involved in suppressing SA-mediated defenses. Unexpectedly, tir1 afb1 afb4 afb5 quadruple-mutant plants lacking four of the six known auxin coreceptors that exhibit decreased auxin perception, supported increased levels of bacterial growth. This mutant exhibited elevated IAA levels and reduced SA-mediated defenses, providing additional evidence that auxin promotes disease by suppressing host defense. We also investigated the hypothesis that IAA promotes PtoDC3000 virulence through a direct effect on the pathogen and found that IAA modulates expression of virulence genes, both in culture and in planta. Thus, in addition to suppressing host defenses, IAA acts as a microbial signaling molecule that regulates bacterial virulence gene expression.
The Crimmigration Crisis: Immigrants, Crime, and Sovereign Power

This article provides a fresh theoretical perspective on the most important development in immigration law today: the convergence of immigration and criminal law. It proposes a unifying theory membership theory for why these two areas of law recently have become so connected, and why that convergence is troubling. Membership theory restricts individual rights and privileges to those who are members of a social contract between the government and the people. Membership theory provides decisionmakers with justification for excluding individuals from society, using immigration and criminal law as the means of exclusion. It operates in the intersection between criminal and immigration law to mark an ever-expanding group of outsiders by denying them the privileges that citizens hold, such as the right to vote or to remain in the United States. Membership theory manifests in this new area through certain powers of the sovereign state: the power to punish, and the power to express moral condemnation. This use of membership theory places the law on the edge of a crimmigration crisis. Only the harshest elements of each area of law make their way into the criminalization of immigration law, and the apparatus of the state is used to expel from society those deemed criminally alien. The result is an ever-expanding population of the excluded and alienated. The article begins with a dystopia, narrating a future in which criminal and immigration law have completely merged, and membership theory has resulted in extreme divisions in our society between insiders and outsiders between the included and the alienated. The rest of the article describes the seeds of that future in the past and present. Part II describes the present confluence of immigration and criminal law. Part III sets out the role of membership theory in those areas in excluding noncitizens and ex-offenders from society. It details the role of sovereign power in drawing and enforcing those lines of exclusion. The article concludes by describing the potential consequences of the convergence of these two areas and the use of membership theory to justify decisions to exclude.
Reconstitution of the human tRNA splicing endonuclease complex: insight into the regulation of pre-tRNA cleavage.

The splicing of tRNA introns is a critical step in pre-tRNA maturation. In archaea and eukaryotes, tRNA intron removal is catalyzed by the tRNA splicing endonuclease (TSEN) complex. Eukaryotic TSEN is comprised of four core subunits (TSEN54, TSEN2, TSEN34 and TSEN15). The human TSEN complex additionally co-purifies with the polynucleotide kinase CLP1; however, CLP1's role in tRNA splicing remains unclear. Mutations in genes encoding all four TSEN subunits, as well as CLP1, are known to cause neurodegenerative disorders, yet the mechanisms underlying the pathogenesis of these disorders are unknown. Here, we developed a recombinant system that produces active TSEN complex. Co-expression of all four TSEN subunits is required for efficient formation and function of the complex. We show that human CLP1 associates with the active TSEN complex, but is not required for tRNA intron cleavage in vitro. Moreover, RNAi knockdown of the Drosophila CLP1 orthologue, cbc, promotes biogenesis of mature tRNAs and circularized tRNA introns (tricRNAs) in vivo. Collectively, these and other findings suggest that CLP1/cbc plays a regulatory role in tRNA splicing by serving as a negative modulator of the direct tRNA ligation pathway in animal cells.
Multidimensional and multiresolution ensemble networks for brain tumor segmentation

In this work, we developed multiple 2D and 3D segmentation models with multiresolution input to segment brain tumor components and then ensembled them to obtain robust segmentation maps. Ensembling reduced overfitting and resulted in a more generalized model. Multiparametric MR images of 335 subjects from the BRATS 2019 challenge were used for training the models. Further, we tested a classical machine learning algorithm with features extracted from the segmentation maps to classify subject survival range. Preliminary results on the BRATS 2019 validation dataset demonstrated excellent performance with DICE scores of 0.898, 0.784, 0.779 for the whole tumor (WT), tumor core (TC), and enhancing tumor (ET), respectively and an accuracy of 34.5% for predicting survival. The Ensemble of multiresolution 2D networks achieved 88.75%, 83.28% and 79.34% dice for WT, TC, and ET respectively in a test dataset of 166 subjects.
Transmission dynamics of and insights from the 2018–2019 measles outbreak in New York City: A modeling study

In 2018-2019, New York City experienced the largest measles outbreak in the United States in nearly three decades. To identify key contributing factors, we modeled the transmission dynamics of this outbreak. Results indicate that delayed vaccination of 1- to 4-year-olds enabled the initial spread and that increased infectious contact, likely via "measles parties," facilitated later transmission. We found that around half of infants were susceptible by age 1 and thus had many infections. Without the implemented vaccination campaigns, numbers of infections and hospitalizations could have been >10 times higher and would predominantly affect those under 4. These results suggest that a first vaccine dose before age 1 and the second dose before age 4 could allow parents to vaccinate and protect children more effectively should a high level of vaccine hesitancy persist. Enhanced public health education is needed to reduce activities that unnecessarily expose children to measles and other infections.
Fiedler Vector Approximation via Interacting Random Walks

The Fiedler vector of a graph, namely the eigenvector corresponding to the second smallest eigenvalue of a graph Laplacian matrix, plays an important role in spectral graph theory with applications in problems such as graph bi-partitioning and envelope reduction. Algorithms designed to estimate this quantity usually rely on a priori knowledge of the entire graph, and employ techniques such as graph sparsification and power iterations, which have obvious shortcomings in cases where the graph is unknown, or changing dynamically. In this paper, we develop a framework in which we construct a stochastic process based on a set of interacting random walks on a graph and show that a suitably scaled version of our stochastic process converges to the Fiedler vector for a sufficiently large number of walks. Like other techniques based on exploratory random walks and on-the-fly computations, such as Markov Chain Monte Carlo (MCMC), our algorithm overcomes challenges typically faced by power iteration based approaches. But, unlike any existing random walk based method such as MCMCs where the focus is on the leading eigenvector, our framework with interacting random walks converges to the Fiedler vector (second eigenvector). We also provide numerical results to confirm our theoretical findings on different graphs, and show that our algorithm performs well over a wide range of parameters and the number of random walks. Simulations results over time varying dynamic graphs are also provided to show the efficacy of our random walk based technique in such settings. As an important contribution, we extend our results and show that our framework is applicable for approximating not just the Fiedler vector of graph Laplacians, but also the second eigenvector of any time reversible Markov Chain kernel via interacting random walks. To the best of our knowledge, our attempt to approximate the second eigenvector of any time reversible Markov Chain using random walks is the first of its kind, opening up possibilities to achieving approximations of higher level eigenvectors using random walks on graphs.
Facet-Aware Evaluation for Extractive Summarization.

Commonly adopted metrics for extractive summarization focus on lexical overlap at the token level. In this paper, we present a facet-aware evaluation setup for better assessment of the information coverage in extracted summaries. Specifically, we treat each sentence in the reference summary as a facet, identify the sentences in the document that express the semantics of each facet as support sentences of the facet, and automatically evaluate extractive summarization methods by comparing the indices of extracted sentences and support sentences of all the facets in the reference summary. To facilitate this new evaluation setup, we construct an extractive version of the CNN/Daily Mail dataset and perform a thorough quantitative investigation, through which we demonstrate that facet-aware evaluation manifests better correlation with human judgment than ROUGE, enables fine-grained evaluation as well as comparative analysis, and reveals valuable insights of state-of-the-art summarization methods. Data can be found at https://github.com/morningmoni/FAR.
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks

The classical bias-variance trade-off predicts that bias decreases and variance increase with model complexity, leading to a U-shaped risk curve. Recent work calls this into question for neural networks and other over-parameterized models, for which it is often observed that larger models generalize better. We provide a simple explanation for this by measuring the bias and variance of neural networks: while the bias is monotonically decreasing as in the classical theory, the variance is unimodal or bell-shaped: it increases then decreases with the width of the network. We vary the network architecture, loss function, and choice of dataset and confirm that variance unimodality occurs robustly for all models we considered. The risk curve is the sum of the bias and variance curves and displays different qualitative shapes depending on the relative scale of bias and variance, with the double descent curve observed in recent literature as a special case. We corroborate these empirical results with a theoretical analysis of two-layer linear networks with random first layer. Finally, evaluation on out-of-distribution data shows that most of the drop in accuracy comes from increased bias while variance increases by a relatively small amount. Moreover, we find that deeper models decrease bias and increase variance for both in-distribution and out-of-distribution data.
Atomic commitment across blockchains

The recent adoption of blockchain technologies and open permissionless networks suggest the importance of peer-to-peer atomic cross-chain transaction protocols. Users should be able to atomically exchange tokens and assets without depending on centralized intermediaries such as exchanges. Recent peer-to-peer atomic cross-chain swap protocols use hashlocks and timelocks to ensure that participants comply to the protocol. However, an expired timelock could lead to a violation of the all-or-nothing atomicity property. An honest participant who fails to execute a smart contract on time due to a crash failure, denial of service attacks or even network delays might end up losing assets. Although a crashed participant is the only participant who ends up worse off, current proposals are unsuitable for atomic cross-chain transactions in asynchronous environments where crash failures and network delays are the norm. In this paper, we present AC3WN, the first decentralized all-or-nothing atomic cross-chain commitment protocol. The redeem and refund events of the smart contracts that exchange assets are modeled as conflicting events. An open permissionless network of witnesses is used to guarantee that conflicting events could never simultaneously occur and either all smart contracts in an atomic cross-chain transaction are redeemed or all of them are refunded.
Inquiry into the short- and long-term effects of Roux-en-Y gastric bypass on the glomerular filtration rate

Bariatric surgery is known to attenuate glomerular hyperfiltration over the long term and thereby protect the kidney from mechanical damage. Whether this effect is directly related to weight loss o...
Preserving the Reproductive Rights of Girls and Women in the Era of COVID-19: The Need for a Least Restrictive Solution.

Fairchild and colleagues assert that while “equal” on the surface, the rapidly implemented, society-wide public health restrictions enacted in response to the COVID-19 pandemic veil harsh inequitie...
Reinforcement Learning for Mitigating Intermittent Interference in Terahertz Communication Networks

Emerging wireless services with extremely high data rate requirements, such as real-time extended reality applications, mandate novel solutions to further increase the capacity of future wireless networks. In this regard, leveraging large available bandwidth at terahertz frequency bands is seen as a key enabler. To overcome the large propagation loss at these very high frequencies, it is inevitable to manage transmissions over highly directional links. However, uncoordinated directional transmissions by a large number of users can cause substantial interference in terahertz networks. While such interference will be received over short random time intervals, the received power can be large. In this work, a new framework based on reinforcement learning is proposed that uses an adaptive multi-thresholding strategy to efficiently detect and mitigate the intermittent interference from directional links in the time domain. To find the optimal thresholds, the problem is formulated as a multidimensional multi-armed bandit system. Then, an algorithm is proposed that allows the receiver to learn the optimal thresholds with very low complexity. Another key advantage of the proposed approach is that it does not rely on any prior knowledge about the interference statistics, and hence, it is suitable for interference mitigation in dynamic scenarios. Simulation results confirm the superior bit-error-rate performance of the proposed method compared with two traditional time-domain interference mitigation approaches.
Engineering Cell-Permeable Proteins through Insertion of Cell-Penetrating Motifs into Surface Loops

Effective delivery of proteins into the cytosol of mammalian cells would open the door to a wide range of applications. However, despite great efforts from numerous investigators, effective protein delivery in a clinical setting is yet to be accomplished. Herein we report a potentially general approach to engineering cell-permeable proteins by genetically grafting a short cell-penetrating peptide (CPP) to an exposed loop of a protein of interest. The grafted peptide is conformationally constrained, exhibiting enhanced proteolytic stability and cellular entry efficiency. Applying this technique to enhanced green fluorescent protein (EGFP), protein-tyrosine phosphatase 1B (PTP1B), and purine nucleoside phosphorylase (PNP) rendered all three proteins cell-permeable and biologically active in cellular assays. When added into growth medium at 0.5-5 μM concentrations, the engineered PTP1B dose-dependently reduced the phosphotyrosine levels of intracellular proteins, while the modified PNP corrected the metabolic deficiency of PNP-deficient mouse T lymphocytes, providing a potential enzyme replacement therapy for a rare genetic disease.
Liquid-Liquid Phase Transitions in Silicon.

We use computationally simple neutral pseudoatom (``average atom'') density functional theory (DFT) and standard DFT to elucidate liquid-liquid phase transitions (LPTs) in liquid silicon. An ionization-driven transition and three LPTs including the known LPT near $2.5\text{ }\text{ }\mathrm{g}/{\mathrm{cm}}^{3}$ are found. They are robust even to 1 eV. The pair distributions functions, pair potentials, electrical conductivities, and compressibilites are reported. The LPTs are elucidated within a Fermi liquid picture of electron scattering at the Fermi energy that complements the transient covalent bonding picture.
Phenotypic Parallelism during Experimental Adaptation of a Free-Living Bacterium to the Zebrafish Gut.

ABSTRACT Although animals encounter a plethora of bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. However, our understanding of how bacteria initiate symbioses with animal hosts remains underexplored, and this process is central to the assembly and function of gut bacterial communities. Therefore, we used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). After approximately 200 bacterial generations, isolates from evolved populations improved their ability to colonize larval zebrafish during competition against their unpassaged ancestor. Genome sequencing revealed unique sets of mutations in the two evolved isolates exhibiting the highest mean competitive fitness. One isolate exhibited increased swimming motility and decreased biofilm formation compared to the ancestor, and we identified a missense mutation in the mannose-sensitive hemagglutinin pilus operon that is sufficient to increase fitness and reproduce these phenotypes. The second isolate exhibited enhanced swimming motility but unchanged biofilm formation, and here the genetic basis for adaptation is less clear. These parallel enhancements in motility and fitness resemble the behavior of a closely related Shewanella strain previously isolated from larval zebrafish and suggest phenotypic convergence with this isolate. Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association. IMPORTANCE Although animals encounter many bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. We used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association.
LRRK2 and Rab10 coordinate macropinocytosis to mediate immunological responses in phagocytes

Genetic variation in LRRK2 associates with the susceptibility to Parkinson's disease, Crohn's disease, and mycobacteria infection. High expression of LRRK2 and its substrate Rab10 occurs in phagocytic cells in the immune system. In mouse and human primary macrophages, dendritic cells, and microglia-like cells, we find that Rab10 specifically regulates a specialized form of endocytosis known as macropinocytosis, without affecting phagocytosis or clathrin-mediated endocytosis. LRRK2 phosphorylates cytoplasmic PI(3,4,5)P3-positive GTP-Rab10, before EEA1 and Rab5 recruitment to early macropinosomes occurs. Macropinosome cargo in macrophages includes CCR5, CD11b, and MHCII, and LRRK2-phosphorylation of Rab10 potently blocks EHBP1L1-mediated recycling tubules and cargo turnover. EHBP1L1 overexpression competitively inhibits LRRK2-phosphorylation of Rab10, mimicking the effects of LRRK2 kinase inhibition in promoting cargo recycling. Both Rab10 knockdown and LRRK2 kinase inhibition potently suppress the maturation of macropinosome-derived CCR5-loaded signaling endosomes that are critical for CCL5-induced immunological responses that include Akt activation and chemotaxis. These data support a novel signaling axis in the endolysosomal system whereby LRRK2-mediated Rab10 phosphorylation stalls vesicle fast recycling to promote PI3K-Akt immunological responses.
Resolving host and species boundaries for perithecia-producing nectriaceous fungi across the central Appalachian Mountains

Abstract The Nectriaceae includes numerous canker pathogens. Due to the scarcity of ascomata on many hosts, comprehensive surveys are lacking. Here we characterize the diversity of perithecia-producing nectriaceous fungi across the central Appalachians in eastern North America. Nine species from eleven hosts were recovered including a novel Corinectria sp. from Picea rubens. Neonectria ditissima and Neonectria faginata were most abundant and associated with Fagus grandifolia with beech bark disease (BBD). Neonectria ditissima was also recovered from additional cankered hardwoods, including previously unreported Acer spicatum, Ilex mucronata, and Sorbus americana. Cross-pathogenicity inoculations of N. ditissima confirmed susceptibility of Acer and Betula spp. Neonectria magnoliae was recovered from cankered Liriodendron tulipifera and Magnolia fraseri and pathogenicity on L. tulipifera was confirmed. Fusarium babinda was consistently recovered from beech with BBD, although its role remains unclear. This survey provides a contemporary snapshot of Nectriaceae diversity across the Appalachian Mountains. The following nomenclatural changes are proposed: Neonectria magnoliae comb. nov.
A structure theorem for finite fields

Abstract We present a new structure theorem for finite fields of odd order that relates multiplicative and additive properties in an interesting way. This theorem has several applications, including an improved understanding of Dickson and Chebyshev polynomials and some formulas with a number-theoretic flavor. This paper is an abridged version of two articles by the author.
Smallest k -Enclosing Rectangle Revisited

Given a set of n points in the plane, and a parameter $$k$$ , we consider the problem of computing the minimum (perimeter or area) axis-aligned rectangle enclosing $$k$$ points. We present the first near quadratic time algorithm for this problem, improving over the previous near- $$O(n^{5/2})$$ -time algorithm by Kaplan et al. (25th European Symposium on Algorithms. Leibniz Int Proc Inform, vol. 87, # 52. Leibniz-Zent Inform, Wadern, 2017). We provide an almost matching conditional lower bound, under the assumption that $$(\min ,+)$$ -convolution cannot be solved in truly subquadratic time. Furthermore, we present a new reduction (for both perimeter and area) that can make the time bound sensitive to $$k$$ , giving near $$O(nk)$$ time. We also present a near linear time $$(1+\varepsilon )$$ -approximation algorithm to the minimum area of the optimal rectangle containing $$k$$ points. In addition, we study related problems including the 3-sided, arbitrarily oriented, weighted, and subset sum versions of the problem.
ENGAGEMENTS AND ENTANGLEMENTS: THE CONTEMPORARY WAQF AND THE FRAGILITY OF SHI'I QUIETISM

Two primary impulses have historically motivated the Iraqi Shi'i juristic establishment in its relations with the Iraqi state. The first, deeply embedded in centuries of Islamic jurisprudence, is to achieve maximum autonomy for the Shi'i community from the state. The second has developed more recently in response to the modern state's efforts to extend its hegemonic control over areas that premodern empires were content either to leave to the jurists to administer or at least to share the administration of with jurists. This is to have the state recognize and implement Shi'i rules within parts of the state infrastructure that are of core interest to the juristic establishment. There is an obvious tension between these two desires, nowhere more evident than in the subject of this article—namely, the law pertaining to the creation, management, and liquidation of the Islamic charitable land trust known as the waqf. On the one hand, Article 43 of Iraq's constitution declares the followers of religions and sects to be “free” in administering the waqfs and their affairs, suggesting a strong desire for autonomy and separation from state control. Yet the implementing legislation for this provision extends the existence of a thick state bureaucracy and hands its administration over to juristic authorities. The ultimate irony of this arrangement is that it subjects juristic forces to far more potential interference as a legal matter than they have ever been subjected to, even during the totalitarian rule of the Ba'ath. In the end, a religious establishment historically deeply suspicious of political rulers and political engagement—indeed, one that defines itself by virtue of its separation from the state—now finds itself deeply and dangerously entangled in state political and administrative affairs. This article explores how this came to be and some of the significant consequences that arise from it.
Statistical prediction of the future impairs episodic encoding of the present

Memory is typically thought of as enabling reminiscence about past experiences. However, memory also informs and guides processing of future experiences. These two functions of memory are often at odds: Remembering specific experiences from the past requires storing idiosyncratic properties that define particular moments in space and time, but by definition such properties will not be shared with similar situations in the future and thus may not be applicable to future situations. We discovered that, when faced with this conflict, the brain prioritizes prediction over encoding. Behavioral tests of recognition and source recall showed that items allowing for prediction of what will appear next based on learned regularities were less likely to be encoded into memory. Brain imaging revealed that the hippocampus was responsible for this interference between statistical learning and episodic memory. The more that the hippocampus predicted the category of an upcoming item, the worse the current item was encoded. This competition may serve an adaptive purpose, focusing encoding on experiences for which we do not yet have a predictive model.
Simultaneous twinning and microband formation under dynamic compression in a high entropy alloy with a complex energetic landscape

Abstract High entropy alloys (HEAs) have been the subject of significant research in recent years due in part to their excellent mechanical properties and unique microstructure. Chemical disorder in these alloys is thought to lead to a complex energetic environment that affects the nucleation and movement of dislocations. In this study the development of deformation substructures is assessed in the Cantor HEA (CoCrFeMnNi) due to quasistatic and dynamic compression. Scanning and transmission electron microscopy (SEM/TEM) techniques are used to image and quantify dislocation density. When increasing the strain rate from 10−3 s−1 to 5000 s−1 we observe an increase in the overall dislocation density which leads to the formation of deformation twins. Further at a rate of 8000 s−1, both deformation twins and microbands become operative plasticity modes, which are usually associated with different extremes of stacking fault energy. To relate this plastic response to chemical disorder, atomistic calculations are used to compute the generalized stacking fault energy curve and approximate the temperature dependence of the intrinsic stacking fault energy for the Cantor alloy, which reveals significant local variation in these critical energetic parameters associated with dislocation and twinning behaviors.
Psychophysical scaling reveals a unified theory of visual memory strength.

Almost all models of visual memory implicitly assume that errors in mnemonic representations are linearly related to distance in stimulus space. Here we show that neither memory nor perception are appropriately scaled in stimulus space; instead, they are based on a transformed similarity representation that is nonlinearly related to stimulus space. This result calls into question a foundational assumption of extant models of visual working memory. Once psychophysical similarity is taken into account, aspects of memory that have been thought to demonstrate a fixed working memory capacity of around three or four items and to require fundamentally different representations—across different stimuli, tasks and types of memory—can be parsimoniously explained with a unitary signal detection framework. These results have substantial implications for the study of visual memory and lead to a substantial reinterpretation of the relationship between perception, working memory and long-term memory. Schurgin et al. propose a model of visual memory, arguing against a distinction between how many items are represented and how precisely they are represented, and in favour of a view based on continuous representations in noisy channels.
Interactions among Cloud, Water Vapor, Radiation, and Large-Scale Circulation in the Tropical Climate. Part II: Sensitivity to Spatial Gradients of Sea Surface Temperature

The responses of the large-scale circulation, clouds, and water vapor to an imposed sea surface temperature (SST) gradient are investigated. Simulations compare reasonably to averaged observations over the Pacific, considering the simplifications applied to the model. The model responses to sinusoidal SST patterns have distinct circulations in the upper and lower troposphere. The upper circulation is sensitive to the heating from deep convection over the warmest SST. Stronger SST gradients are associated with stronger longwave cooling above stratus clouds in the subsidence region, stronger lower-tropospheric large-scale circulation, a reduction of the rain area, and larger area coverage of low clouds. A similar SST gradient with a warmer mean temperature produces slightly weaker lower-tropospheric circulation, and slightly reduced low cloud coverage. The outgoing longwave radiation (OLR) is not sensitive to the mean SST or the range of the imposed sinusoidal SST gradient. The positive feedbacks of water vapor and decreasing high cloud OLR compensate for the increase in longwave emission with increasing mean temperature in these simulations. As the SST gradient is increased keeping the mean SST constant, the positive high cloud feedback is still active, but the air temperature increases in proportion to the maximum SST in the domain. increasing the clear-sky OLR value and keeping the average OLR constant. The net absorbed shortwave radiation (SWI) is found to he extremely sensitive to the SST gradient. The stronger lower-tropospheric large-scale circulation produces a higher water content in the high and low clouds, increasing the absolute magnitude of the shortwave cloud forcing. A 25% increase in the maximum zonal mass flux of the lower circulation of the 300-K mean 4-K SST range simulation leads to a 7.4 W m 2 decrease in SWI, Increasing the mean SST creates a positive feedback in these simulations because of the decrease in the lower-tropospheric large-scale circulation and the resultant decrease in cloud optical depth.