cssi/SciSciGPT-SciSciNet huggingface dataset:
Rapid screening of engineered microbial therapies in a 3D multicellular model

Synthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation, infections, metabolic disorders, and cancer. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation. In vitro approaches to address this challenge have been limited in scalability and broad applicability. Here, we present a bacteria-in-spheroid coculture (BSCC) platform that simultaneously tests host species, therapeutic payloads, and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen Salmonella typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies, using a syngeneic mouse model. Last, we show that our platform can be expanded to dynamically profile diverse microbial species including Listeria monocytogenes, Proteus mirabilis, and Escherichia coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and for understanding the host–microbe interactions in disease sites.
High-molecular-weight polymers from dietary fiber drive aggregation of particulates in the murine small intestine

The lumen of the small intestine (SI) is filled with particulates: microbes, therapeutic particles, and food granules. The structure of this particulate suspension could impact uptake of drugs and nutrients and the function of microorganisms; however, little is understood about how this suspension is re-structured as it transits the gut. Here, we demonstrate that particles spontaneously aggregate in SI luminal fluid ex vivo. We find that mucins and immunoglobulins are not required for aggregation. Instead, aggregation can be controlled using polymers from dietary fiber in a manner that is qualitatively consistent with polymer-induced depletion interactions, which do not require specific chemical interactions. Furthermore, we find that aggregation is tunable; by feeding mice dietary fibers of different molecular weights, we can control aggregation in SI luminal fluid. This work suggests that the molecular weight and concentration of dietary polymers play an underappreciated role in shaping the physicochemical environment of the gut.
Learning models from data with measurement error: Tackling underreporting

Measurement error in observational datasets can lead to systematic bias in inferences based on these datasets. As studies based on observational data are increasingly used to inform decisions with real-world impact, it is critical that we develop a robust set of techniques for analyzing and adjusting for these biases. In this paper we present a method for estimating the distribution of an outcome given a binary exposure that is subject to underreporting. Our method is based on a missing data view of the measurement error problem, where the true exposure is treated as a latent variable that is marginalized out of a joint model. We prove three different conditions under which the outcome distribution can still be identified from data containing only error-prone observations of the exposure. We demonstrate this method on synthetic data and analyze its sensitivity to near violations of the identifiability conditions. Finally, we use this method to estimate the effects of maternal smoking and opioid use during pregnancy on childhood obesity, two import problems from public health. Using the proposed method, we estimate these effects using only subject-reported drug use data and substantially refine the range of estimates generated by a sensitivity analysis-based approach. Further, the estimates produced by our method are consistent with existing literature on both the effects of maternal smoking and the rate at which subjects underreport smoking.
DO INSIDERS CLUSTER TRADES WITH COLLEAGUES? EVIDENCE FROM DAILY INSIDER TRADING

We explore similarities in insider trading as a proxy for information flows. We observe that corporate insiders cluster trades around those of other insiders at their firm, especially around trades of insiders with whom they work closely. Clustering is greater when informational advantages are larger: during periods of low investor attention, high uncertainty, and high information asymmetry. We also document that clustered insider purchases are followed by abnormal returns in excess of 2% during the subsequent month. Our results are consistent with informed trading, which could result from information sharing among corporate insiders.
The Implicit Fairness Criterion of Unconstrained Learning

We clarify what fairness guarantees we can and cannot expect to follow from unconstrained machine learning. Specifically, we characterize when unconstrained learning on its own implies group calibration, that is, the outcome variable is conditionally independent of group membership given the score. We show that under reasonable conditions, the deviation from satisfying group calibration is upper bounded by the excess risk of the learned score relative to the Bayes optimal score function. A lower bound confirms the optimality of our upper bound. Moreover, we prove that as the excess risk of the learned score decreases, it strongly violates separation and independence, two other standard fairness criteria. Our results show that group calibration is the fairness criterion that unconstrained learning implicitly favors. On the one hand, this means that calibration is often satisfied on its own without the need for active intervention, albeit at the cost of violating other criteria that are at odds with calibration. On the other hand, it suggests that we should be satisfied with calibration as a fairness criterion only if we are at ease with the use of unconstrained machine learning in a given application.
Smoothing Hazard Rates

The nonparametric approach to estimate hazard rates for lifetime data is flexible, model-free, and data-driven. No shape assumption is imposed other than that the hazard function is a smooth function. Such an approach typically involves smoothing of an initial hazard estimate, with arbitrary choice of smoother. We describe methods for grouped lifetime data observed at certain time intervals and for continuously observed lifetime data. There are some intrinsic differences between the smoothing approaches for these two types of data. More specifically, smoothing an initial hazard estimate based on the life table is adopted for grouped lifetime data; while for continuous data, smoothing is employed to increments of the Nelson–Aalen cumulative hazard estimate aiming at the derivative of the cumulative hazard function. A few nonparametric hazard regression methods are also discussed. Keywords: life table; Nelson–Aalen estimator; nonparametric smoothing methods; bandwidth choices; boundary effects; hazard regression
Compliance With Skeletal Surveys for Child Abuse in General Hospitals: A Statewide Quality Improvement Process.

OBJECTIVE. The purpose of this study is to perform a statewide quality improvement process to improve compliance with the American College of Radiology (ACR) guidelines in performing skeletal surve...
The utility of direct questions in eliciting subjective content from children disclosing sexual abuse

Abstract Background Children alleging sexual abuse rarely exhibit emotion when disclosing, but they may be able to describe their subjective reactions to abuse if asked. Objective This study examined the extent to which different types of questions in child sexual abuse interviews elicited subjective content, namely emotional reactions, cognitive content, and physical sensations. Participants and setting The study included transcripts of 205 Child Advocacy Center interviews with 4- to 12-year-old children alleging sexual abuse. Methods We coded questions for question type, distinguishing among invitations, wh- questions, yes/no and forced-choice questions, and suggestive questions. We coded both questions and answers for whether they referenced subjective content. Results When questions did not reference subjective content, the most productive questions were invitations, though they elicited subjective content less than 5% of the time. When questions specifically referenced subjective content, children were likely to explicitly mention such content, particularly in response to “how feel” and “what think” questions. Children’s responsiveness and productivity was enhanced by requests to elaborate on their subjective responses, and both emotional and physical reactions could be elicited. There was little evidence of non-responsiveness or counterintuitive reactions to abuse. Younger children were less likely than older children to provide subjective responses to questions that did not reference subjective content, but were no less likely to do so when asked questions with subjective content. Conclusions Children, even young children, can be successfully encouraged to provide subjective content about sexual abuse, particularly when free recall questions are supplemented with “how feel” or “what think” questions.
Talk of Calling: Novice School Principals Narrating Destiny, Duty, and Fulfillment in Work:

Purpose: School principals’ commitment and motivation have not been systematically investigated, but concerted research is needed as 25% of principals leave their jobs each year. This article inves...
Policy perceptions of US state public health and child and family services regarding maternal opioid use and neonatal exposure

Abstract Objective To explore how state legislatures and departments of health are responding to the public health and economic issues of increases in opioid use disorder and the impact on pregnant women and infants. Design The design was a non-experimental descriptive study using a mixed methods survey research approach. Setting Electronic and telephone survey of individuals from state departments of health associated with departments of behavioral health and substance use, or child and family services. Participants Fifty-two respondents employed by individual state departments of health and child and family services. Methods Univariate analysis and frequency distribution of ordinal variables was completed. Thematic analysis was used to analyze free text questions and identify themes. Results All states reported recent changes or plans to address the problem of opioid misuse in their state. Many respondents feel their state continues to lack adequate services for treatment. Some states are exploring unique methods for addressing this in a safe and timely fashion, such as moving medication-assisted treatment to primary care and expanding licensure to Primary Care Physicians (PCPs) and nurse practitioners. Conclusions Our findings demonstrate an increased commitment throughout the United States to enhance access to clinically appropriate treatment of substance use disorder particularly during pregnancy, consider unique methods for addressing the problem of opioid dependency, and increase education and primary prevention programs.
Are Automated Vehicles Safer than Manually Driven Cars

Are automated vehicles really safer than manually driven vehicles? If so, how would we know? Answering this question has spurred a contentious debate. Unfortunately, several issues make answering this question difficult for the foreseeable future. First, how do we measure safety? Second, how can we keep track of automated vehicle (AV) safety? Finally, how do we determine what is or what is not an AV? Until these questions are addressed, it will continue to be difficult to determine whether or when AVs might really be safer than manually driven vehicles.
Aluminum-containing mesostructural materials

This article reviews syntheses of mesoporous aluminosilicates and aluminum oxides based on surfactant templating methods. The incorporation of aluminum in the silicate frameworks generates acid sites and ion-exchange sites. Both, tetrahedral framework aluminum and octahedral extraframework aluminum can be present, depending on the aluminum precursor used. The aluminum-containing structures tend to be less ordered than their purely siliccous analogs. Dealumination plays a significant role during template removal. Other methods for the synthesis of mesoporous aluminum-containing sieves are based on the structural transformation of kanemite, and on cluster precursors which may be connected by self-condensation or by condensation with silicate bridges. Purely aluminous mesostructures can be prepared with neutral templates or by condensing Keggin-like aluminum clusters in an ordered salt with an anionic surfactant.
BENZOTRIAZOLE-ASSISTED PREPARATIONS OF 2-(SUBSTITUTED AMINO)PYRIDINES AND PYRID-2-ONES

Base-promoted reactions of benzotriazolyl-containing acetic acid derivatives, 2-(benzotriazol-1-yl)acetonitrile (7a), 2-(benzotriazol-1-yl)acetamide (7b), and (±)-2-(benzotriazol-1-yl)propionamide (7c), with α,β-unsaturated ketones 8 give efficient and regioselective access to previously difficult to attain 3-unsubstituted pyridine derivatives: the 2-(substituted amino)pyridines 14a−k and the 4,6-substituted pyrid-2-ones 15a−h. The pyridine rings result from tandem [3 + 3] annulations involving a Michael addition followed by cyclization.
A large close relative of C. elegans is slow-developing but not long-lived

Variation in body size is thought to be a major driver of a wide variety of ecological and evolutionary patterns, including changes in development, reproduction, and longevity. Additionally, drastic changes in natural context often have profound effects on multiple fitness-related traits. Caenorhabditis inopinata is a recently-discovered fig-associated nematode that is unusually large relative to other members of the genus, including the closely related model system C. elegans. Here we test whether the dramatic increase in body size and shift in ecological context has led to correlated changes in key life history and developmental parameters within this species. Using four developmental milestones, C. inopinata was found to have a slower rate of development than C. elegans across a range of temperatures. Despite this, C. inopinata did not reveal any differences in adult lifespan from C. elegans after accounting for differences in developmental timing and reproductive mode. C. inopinata fecundity was generally lower than that of C. elegans, but fitness improved under continuous-mating, consistent with sperm-limitation under gonochoristic (male/female) reproduction. C. inopinata also revealed greater fecundity and viability at higher temperatures. Consistent with observations in other ectotherms, slower growth in C. inopinata indicates a potential trade-off between body size and developmental timing, whereas its unchanged lifespan suggests that longevity is largely uncoupled from its increase in body size. Additionally, temperature-dependent patterns of fitness in C. inopinata are consistent with its geographic origins in subtropical Okinawa. Overall, these results underscore the extent to which changes in ecological context and body size can shape life history traits.
Deriving the exact nonadiabatic quantum propagator in the mapping variable representation

We derive an exact quantum propagator for nonadiabatic dynamics in multi-state systems using the mapping variable representation, where classical-like Cartesian variables are used to represent both continuous nuclear degrees of freedom and discrete electronic states. The resulting Liouvillian is a Moyal series that, when suitably approximated, can allow for the use of classical dynamics to efficiently model large systems. We demonstrate that different truncations of the exact Liouvillian lead to existing approximate semiclassical and mixed quantum–classical methods and we derive an associated error term for each method. Furthermore, by combining the imaginary-time path-integral representation of the Boltzmann operator with the exact Liouvillian, we obtain an analytic expression for thermal quantum real-time correlation functions. These results provide a rigorous theoretical foundation for the development of accurate and efficient classical-like dynamics to compute observables such as electron transfer reaction rates in complex quantized systems.
A web-based, branching logic questionnaire for the automated classification of migraine:

ObjectiveTo identify migraineurs and headache-free individuals with an online questionnaire and automated analysis algorithm.MethodsWe created a branching-logic, web-based questionnaire – the Penn ...
Zika Fetal Neuropathogenesis: Etiology of a Viral Syndrome.

The ongoing Zika virus epidemic in the Americas and the observed association with both fetal abnormalities (primary microcephaly) and adult autoimmune pathology (Guillain–Barre syndrome) has brought attention to this neglected pathogen. While initial case studies generated significant interest in the Zika virus outbreak, larger prospective epidemiology and basic virology studies examining the mechanisms of Zika viral infection and associated pathophysiology are only now starting to be published. In this review, we analyze Zika fetal neuropathogenesis from a comparative pathology perspective, using the historic metaphor of “TORCH” viral pathogenesis to provide context. By drawing parallels to other viral infections of the fetus, we identify common themes and mechanisms that may illuminate the observed pathology. The existing data on the susceptibility of various cells to both Zika and other flavivirus infections are summarized. Finally, we highlight relevant aspects of the known molecular mechanisms of flavivirus replication.
Keeping Context In Mind: Automating Mobile App Access Control with User Interface Inspection

Recent studies observe that app foreground is the most striking component that influences the access control decisions in mobile platform, as users tend to deny permission requests lacking visible evidence. However, none of the existing permission models provides a systematic approach that can automatically answer the question: Is the resource access indicated by app foreground?In this work, we present the design, implementation, and evaluation of COSMOS, a context-aware mediation system that bridges the semantic gap between foreground interaction and background access, in order to protect system integrity and user privacy. Specifically, COSMOS learns from a large set of apps with similar functionalities and user interfaces to construct generic models that detect the outliers at runtime. It can be further customized to satisfy specific user privacy preference by continuously evolving with user decisions. Experiments show that COSMOS achieves both high precision and high recall in detecting malicious requests. We also demonstrate the effectiveness of COSMOS in capturing specific user preferences using the decisions collected from 24 users and illustrate that COSMOS can be easily deployed on smartphones as a real-time guard with a very low performance overhead.
A One-Week, Unique, and Authentic Leadership Development Camp for Undergraduate Students

Annually, students from the Department of Kinesiology attend a 1-week residential leadership camp. Prior to attending the camp, students complete a self-evaluation of perceived leadership skills. Students are in small teams in which they lead their peers through a series of problem solving activities. For this study, students (N=314) completed the survey again at the end of the 1-week leadership development camp. Paired t-test statistical analysis revealed a significant change in 14 out of the 20 dimensions (p < .001). Findings of this study suggest students perceive an increase in their leadership skills following a 1- week leadership development camp.
Top compositeness at the Tevatron and LHC

We explore the possibility that the right-handed top quark is composite. We examine the consequences that compositeness would have on t production at the Tevatron, and derive a weak constraint on the scale of compositeness of order a few hundred GeV from the t inclusive cross section. More detailed studies of differential properties of t production could potentially improve this limit. We find that a composite top can result in an enhancement of the tt production rate at the LHC (of as much as 103 compared to the Standatd Model four top rate). We explore observables which allow us to extract the four top rate from the backgrounds, and show that the LHC can either discover or constrain top compositeness for wide ranges of parameter space.
The stability of organometallic ligands in oxidation catalysis

Abstract Organometallic precatalysts are increasingly applied to oxidation catalysis, where the spectator character of such ligands as Cp and Cp* is often assumed without definite proof. A number of reports of ligand lability under oxidative conditions have now appeared in the literature, raising concerns in reactions where primary oxidants are present. In such a case, partial or complete degradative loss of the organometallic ligand from the metal may need to be considered. This loss can sometimes deactivate a catalyst but it may also activate it by opening up labile sites at the metal. The highest risk applies to oxidation of the least reactive substrates, such as alkanes, since the catalyst may then also oxidize the CH bonds of its own ligands. More reactive substrates such as alkenes are likely to provide greater stabilization to the catalysts by providing a pathway for faster reaction of the substrate with the oxidized form of the catalyst. We therefore look at these and some related reactions to probe organometallic ligand loss under oxidative conditions, a topic that has received too little attention considering its important implications. Ligand loss can also affect applications to asymmetric catalysis and heterogenized homogeneous catalysts where the organometallic ligand is functionalized with a homochiral substituent or a tether to a surface. Ligands covered include CO, alkyls, aryls, alkenes, arenes, NHCs, cyclopentadienyls and other soft ligands.
Synthesis of N-Acylcarbazoles through Palladium-Catalyzed Aryne Annulation of 2-Haloacetanilides

N-Acylcarbazoles have been synthesized in moderate to good yields by the annulation of in situ generated arynes with 2-haloacetanilides in the presence of a palladium catalyst and CsF. Both C-C and C-N bonds are formed simultaneously, and a variety of functional groups are tolerated in this reaction.
Highly potent and selective zwitterionic agonists of the δ-opioid receptor. Part 1

Abstract A series of zwitterionic δ-opioid agonists, with targeted physicochemistry, as a strategy to limit potential for CNS exposure, were prepared. These agents were found to possess exquisite potency and selectivity over mu and κ-opiate activity. Furthermore, analogue 3a was found to display restricted CNS exposure, as evidenced by its inactivity in a rodent hyperlocomotion assay of central opiate activity. Dog pharmacokinetic studies on 3a indicated encouraging oral bioavailability.
A Proposed Chaperone of the Bacterial Type VI Secretion System Functions To Constrain a Self-Identity Protein

The bacterium Proteus mirabilis can communicate identity through the secretion of the self-identity protein IdsD via the type VI secretion (T6S) system. IdsD secretion is essential for self-versus-nonself recognition behaviors in these populations. Here we provide an answer to the unresolved question of how the activity of a T6S substrate, such as IdsD, is regulated before secretion. We demonstrate that IdsD is found in clusters that form independently of the T6S machinery and activity. We show that the IdsC protein, which is a member of the proposed DUF4123 chaperone family, is essential for the maintenance of these clusters and of the IdsD protein itself. We provide evidence that amino acid disruptions in IdsC are sufficient to disrupt IdsD secretion but not IdsD localization into subcellular clusters, strongly supporting the notion that IdsC functions in at least two different ways: maintaining IdsD levels and secreting IdsD. We propose that IdsC, and likely other DUF4123-containing proteins, functions to regulate T6S substrates in the donor cell both by maintaining protein levels and by mediating secretion at the T6S machinery.IMPORTANCE Understanding the subcellular dynamics of self-identity proteins is crucial for developing models of self-versus-nonself recognition. We directly addressed how a bacterium restricts self-identity information before cell-cell exchange. We resolved two conflicting models for type VI secretion (T6S) substrate regulation by focusing on the self-identity protein IdsD. One model is that a cognate immunity protein binds the substrate, inhibiting activity before transport. Another model proposes that DUF4123 proteins act as chaperones in the donor cell, but no detailed molecular mechanism was previously known. We resolve this discrepancy and propose a model wherein a chaperone couples IdsD sequestration with its localization. Such a molecular mechanism restricts the communication of identity, and possibly other T6S substrates, in producing cells.
Schwartz reagent mediated synthesis of thiazolones and imidazolones from thiazolidine-2,4-diones and imidazolidine-2,4-diones

Abstract A novel reduction/elimination method of thiazolidine-2,4-dione and imidazolidine-2,4-dione derivatives using Schwartz reagent to synthesize numerous thiazolones and imidazolones in a single step is reported.
Generalized Data Augmentation for Low-Resource Translation

Low-resource language pairs with a paucity of parallel data pose challenges for machine translation in terms of both adequacy and fluency. Data augmentation utilizing a large amount of monolingual data is regarded as an effective way to alleviate the problem. In this paper, we propose a general framework of data augmentation for low-resource machine translation not only using target-side monolingual data, but also by pivoting through a related high-resource language. Specifically, we experiment with a two-step pivoting method to convert high-resource data to the low-resource language, making best use of available resources to better approximate the true distribution of the low-resource language. First, we inject low-resource words into high-resource sentences through an induced bilingual dictionary. Second, we further edit the high-resource data injected with low-resource words using a modified unsupervised machine translation framework. Extensive experiments on four low-resource datasets show that under extreme low-resource settings, our data augmentation techniques improve translation quality by up to 1.5 to 8 BLEU points compared to supervised back-translation baselines.
Predictability of Genetic Interactions from Functional Gene Modules.

Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.
The principle of nonperfect synchronization: how does it apply to aromatic systems?

According to the Principle of Nonperfect Synchronization (PNS), a product-stabilizing factor, the development of which at the transition state lags behind bond changes, increases the intrinsic barrier of a reaction, but lowers it if it develops ahead of bond changes. Because of the generality of this principle, details of transition state structures can be deduced from comparisons of intrinsic barriers within classes of reactions. A major conclusion that has emerged from such comparisons is that reactions that lead to charge delocalization/resonance stabilized products have transition states in which the development of charge delocalization/resonance stabilization lags behind bond changes and, hence, have relatively high intrinsic barriers. This paper deals with reactions that lead to aromatic molecules or ions. The question we are asking is whether or not aromaticity follows the pattern of common resonance effects and lags behind bond changes at the transition state. Evidence based on experimentally determined intrinsic barriers of proton transfers from rhenium carbene complexes in solution, as well as that based on ab initio calculations of proton transfers in the gas phase, suggests that aromaticity development at the transition state may actually be ahead of bond changes. Copyright © 2004 John Wiley & Sons, Ltd.
Enantioselective syntheses of ring-C precursors of vitamin B12. Substrate control. A novel Si-assisted elimination of vinyl bromides.

Homochiral ring-C precursors 34 of Vitamin B12 have been prepared by Ireland−Claisen rearrangement of allyl esters 32, followed by a novel Si-assisted elimination of HBr.
Controlling Parent Systems Through Swarms Using Abstraction

This study considers the control of parent–child systems where a parent system is acted on by a set of controllable child systems (i.e., a swarm). Examples of such systems include a swarm of robots pushing an object over a surface, a swarm of aerial vehicles carrying a large load, or a set of end-effectors manipulating an object. In this paper, a general approach for decoupling the swarm from the parent system through a low-dimensional abstract state space is presented. The conditions that enable this approach are given along with how constraints on both systems propagate through the abstract state and impact the requirements of their controllers. To demonstrate, several controllers with hard state constraints are designed to track a given desired angle trajectory of a tilting plane with a swarm of robots driving on top. Both homogeneous and heterogeneous swarms of varying sizes and properties are considered to test the robustness of this architecture. The controllers are shown to be locally asymptotically stable and are demonstrated in simulation.
Secondary Amines as Lewis Bases in Nitroalkene Activation

Secondary amines, the well-known enamine and iminium catalysts, can also be used as Lewis bases for the activation of electron-deficient olefins. In this Focus Review, a series of systematic studies from the last five years on activation of nitroolefins with secondary amines as Lewis bases that give different multicomponent condensation products are described. Asymmetric syntheses of heterocycles based on this strategy are also presented.
Limitations of Correlation-Based Inference in Complex Virus-Microbe Communities.

ABSTRACT Microbes are present in high abundances in the environment and in human-associated microbiomes, often exceeding 1 million per ml. Viruses of microbes are present in even higher abundances and are important in shaping microbial populations, communities, and ecosystems. Given the relative specificity of viral infection, it is essential to identify the functional linkages between viruses and their microbial hosts, particularly given dynamic changes in virus and host abundances. Multiple approaches have been proposed to infer infection networks from time series of in situ communities, among which correlation-based approaches have emerged as the de facto standard. In this work, we evaluate the accuracy of correlation-based inference methods using an in silico approach. In doing so, we compare predicted networks to actual networks to assess the self-consistency of correlation-based inference. At odds with assumptions underlying its widespread use, we find that correlation is a poor predictor of interactions in the context of viral infection and lysis of microbial hosts. The failure to predict interactions holds for methods that leverage product-moment, time-lagged, and relative-abundance-based correlations. In closing, we discuss alternative inference methods, particularly model-based methods, as a means to infer interactions in complex microbial communities with viruses. IMPORTANCE Inferring interactions from population time series is an active and ongoing area of research. It is relevant across many biological systems—particularly in virus-microbe communities, but also in gene regulatory networks, neural networks, and ecological communities broadly. Correlation-based inference—using correlations to predict interactions—is widespread. However, it is well-known that “correlation does not imply causation.” Despite this, many studies apply correlation-based inference methods to experimental time series without first assessing the potential scope for accurate inference. Here, we find that several correlation-based inference methods fail to recover interactions within in silico virus-microbe communities, raising questions on their relevance when applied in situ.
Thermoelectric Properties and Site-Selective Rb + /K + Distribution in the K2-xRbxBi8Se13 Series

β-K2Bi8Se13 possesses promising thermoelectric properties whereas Rb2Bi8Se13 does not. The formation of solid solutions between these two compounds was attempted to study the alkali metal distribution in the structure and its influence in the electronic properties. The structure of the K2-xRbxBi8Se13 series of solid solutions was studied and the members with 0 < x ≤ 1 were found to adopt the β-K2Bi8Se13 structure. Detailed crystallographic studies were performed for the x = 1.0 composition to examine in detail the K/Rb distribution in the lattice and the effect on the K/Bi disorder that exists in the β-K2Bi8Se13 structure. The Rb+ ions occupy exclusively one crystallographic site replacing K+. This defines RbKBi8Se13 as a new quaternary compound. Lattice parameters and band gaps are reported for the different compositions. Charge transport measurements including electrical conductivity, thermoelectric power, and Hall effect show that the materials are n-type semiconductors with increasing carrier concentr...
Synthesis of trifluoromethylated heterocycles using partially fluorinated epoxides

Abstract Reaction of 2-trifluoromethyl- (1) and 2,2-bis(trifluoromethyl)- (2) oxiranes with a variety of sulfur nucleophiles proceeds rapidly and under mild conditions. For example, epoxide 2 reacts with aqueous solution of Na2S, producing S[CH2C(CF3)2OH]2. Reaction of 2 with Na2S2O3 leads to the formation of the corresponding Bunte salt. Interaction of 2 with NaSCN in water proceeds exothermically and results in high-yield formation of cyclic imine 5. Although this material can be isolated, it has limited stability and undergoes cyclotrimerization at ambient temperature, giving the corresponding 1,3,5-triazine. A number of heterocyclic compounds containing pendant –CH2C(CF3)2OH group were prepared by the reaction of the corresponding thio-derivatives, such as pyridine-2-thiole with epoxide 2. It was found that fluoride anion catalyzes the reaction of epoxides 1 and 2 with isothiocyanates carrying electron withdrawing groups at nitrogen. The reaction results in nucleophilic cyclization and formation of the corresponding exocyclic imines containing a 1,3-oxothiolane moiety. Carbon disulfide was also found to be active in this process, reacting with epoxides 1 and 2 at ambient to give the corresponding trifluoromethylated 1,3-oxathiolane-2-thiones in 58–65% yield.
A cryptography-based approach for movement decoding

Brain decoders use neural recordings to infer the activity or intent of a user. To train a decoder, one generally needs to infer the measured variables of interest (covariates) from simultaneously measured neural activity. However, there are cases for which obtaining supervised data is difficult or impossible. Here, we describe an approach for movement decoding that does not require access to simultaneously measured neural activity and motor outputs. We use the statistics of movement-much like cryptographers use the statistics of language-to find a mapping between neural activity and motor variables, and then align the distribution of decoder outputs with the typical distribution of motor outputs by minimizing their Kullback-Leibler divergence. By using datasets collected from the motor cortex of three non-human primates performing either a reaching task or an isometric force-production task, we show that the performance of such a distribution-alignment decoding algorithm is comparable to the performance of supervised approaches. Distribution-alignment decoding promises to broaden the set of potential applications of brain decoding.
Studies on the Synthesis of Chlorothricolide: Diastereo- and Enantioselective Syntheses of Model Top-Half Spirotetronate Units

Highly enantio- and diastereoselective syntheses of spirotetronates 9 and 10, corresponding to the top-half fragment of chlorothricolide, are described. Key steps in these syntheses are the Diels−A...
Reactions of carbon nucleophiles with 2,2,3-trisubstituted ethynylaziridines

Abstract Carbon nucleophiles were used to open a 2,2,3-trisubstituted ethynylaziridine. A cyanide nucleophile opened the ring at the more substituted carbon, proceeding regioselectively with inversion of configuration. In an attempt to expand upon the scope of the reaction, Normant cuprates were reacted with a 2,2,3-trisubstituted ethynylaziridine. This reaction produced chiral allenes via an anti-SN2′ pathway. X-ray analysis of a derivative allowed the absolute stereochemistry of the anti-allenes to be assigned as P.
Dynamic prediction during perception of everyday events

The ability to predict what is going to happen in the near future is integral for daily functioning. Previous research suggests that predictability varies over time, with increases in prediction error at those moments that people perceive as boundaries between meaningful events. These moments also tend to be points of rapid change in the environment. Eye tracking provides a method for noninterruptive measurement of prediction as participants watch a movie of an actor performing a series of actions. In two studies, we used eye tracking to study the time course of prediction around event boundaries. In both studies, viewers looked at objects that were about to be touched by the actor shortly before the objects were contacted, demonstrating predictive looking. However, this behavior was modulated by event boundaries: looks to to-be-contacted objects near event boundaries were less likely to be early and more likely to be late compared to looks to objects contacted within events. This result is consistent with theories proposing that event segmentation results from transient increases in prediction error.
Allyl cation stereochemistry in the intramolecular 4+3 cycloaddition reaction

Abstract Initial allyl cation geometry appears to be irrelevant with respect to the stereochemistry of cycloadducts in the intramolecular 4+3 cycloaddition of alkoxyallylic cations derived from alkoxyallylic sulfones.
Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components.

Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of signif...
Stereoselective approach to the dihydroagarofuran framework via directed intramolecular radical addition

Abstract The radical derived from bromoacetal 12 undergoes intramolecular addition to give predominantly the cyclic acetal 13 in which the C12 methyl substituent is endo.
Autoxidative annulation cascade of the α-cyano β-TMS-capped alkynyl cycloalkanone system.

The autoxidative annulation cascade promoted by an α-cyano β-TMS-capped alkynyl cycloalkanone system under catalysis with pyridine in one oxygen atmosphere has proven to be highly viable. On the ba...
Synthesis and aqueous aggregation properties of amphiphilic surface-block dendrimers.

A family of dendritic amphiphiles were synthesized from the natural metabolites of glycerol, succinic acid, and myristic acid. The surfaces of these dendrimers display different numbers of alkyl chains and carboxylic acids, varying the hydrophobic-to-hydrophilic ratio over a relatively broad range. In solution these dendritic amphiphiles form supramolecular structures, and these aggregates have been characterized by light microscopy, transmission electron microscopy, and tensiometry. These aggregates can entrap the hydrophobic species pyrene.
Thermochemistry of Benzvalene, Dihydrobenzvalene, and Cubane: A High-Level Computational Study

The thermochemical properties of benzvalene, dihydrobenzvalene, and cubane were determined using ab initio molecular orbital calculations at the G2, G2(MP2), and G2(MP2,SVP) levels of theory. The e...
A convenient and efficient method for incorporation of pentafluorosulfanyl (SF5) substituents into aliphatic compounds

Abstract Both SF5Cl and SF5Br undergo smooth, high yield addition to alkenes and alkynes under the mild free radical chain reaction conditions of triethylborane initiation at low temperature, although the SF5Br chemistry is somewhat limited by its competing high electrophilic reactivity with electron rich alkenes. The SF5Cl addition reaction is relatively insensitive to a wide variety of non-allylic functionalities.
Hydrothermal synthesis, structure, and property characterization of rare earth silicate compounds: NaBa3Ln3Si6O20 (Ln = Y, Nd, Sm, Eu, Gd)

Abstract A series of new lanthanide (Ln) silicates have been synthesized using high temperature hydrothermal techniques, and structurally characterized using single crystal and powder X-ray diffraction. The compounds have the general formula NaBa3Ln3Si6O20 (Ln = Y, Nd, Sm, Eu, Gd), and crystallize in the space group Ama2 (No.40). As a representative example, the unit cell parameters of NaBa3Gd3Si6O20 are a = 14.731(3) A, b = 23.864(5) A, c = 5.5449(11) A and Z = 4. The title compounds adopt a three dimensional polar acentric framework made of Ln–O–Si bonding. The framework is comprised of LnO8 and LnO7 units forming edge-sharing infinite chains along the c-axis. These oxy-bridged infinite chains are also linked by [Si4O13] tetrasilicate and [Si2O7] disilicate units to form the three-dimensional framework structure, with Ba2+ and Na+ cations residing inside channels of the framework. The polarity in the structure is imparted by the unusual tetrasilicate arrangement. The luminescence and magnetic properties were investigated on selected compounds. The temperature dependent magnetic susceptibility measurements on the Nd, Sm, and Gd derivatives reveal a Curie–Weiss behavior with an antiferromagnetic coupling parameter. For the Eu-derivative, the temperature dependent magnetic susceptibility deviates significantly from Curie–Weiss behavior. Luminescence properties of NaBa3Eu3Si6O20 and NaBa3Sm3Si6O20 compounds exhibited the characteristic transitions of Eu3+ (5D0 → 7FJ, J = 0–4) and Sm3+ (4G5/2 → 6HJ, J = 5/2, 7/2), respectively, leading to strong visible red and orange emissions, respectively.
CHAIN CONDITIONS ON ÉTALE GROUPOID ALGEBRAS WITH APPLICATIONS TO LEAVITT PATH ALGEBRAS AND INVERSE SEMIGROUP ALGEBRAS

The author has previously associated to each commutative ring with unit and etale groupoid with locally compact, Hausdorff and totally disconnected unit space an -algebra . In this paper we characterize when is Noetherian and when it is Artinian. As corollaries, we extend the characterization of Abrams, Aranda Pino and Siles Molina of finite-dimensional and of Noetherian Leavitt path algebras over a field to arbitrary commutative coefficient rings and we recover the characterization of Okninski of Noetherian inverse semigroup algebras and of Zelmanov of Artinian inverse semigroup algebras.
Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase

There have been several efforts to extend distributional semantics beyond individual words, to measure the similarity of word pairs, phrases, and sentences (briefly, tuples ; ordered sets of words, contiguous or noncontiguous). One way to extend beyond words is to compare two tuples using a function that combines pairwise similarities between the component words in the tuples. A strength of this approach is that it works with both relational similarity (analogy) and compositional similarity (paraphrase). However, past work required hand-coding the combination function for different tasks. The main contribution of this paper is that combination functions are generated by supervised learning. We achieve state-of-the-art results in measuring relational similarity between word pairs (SAT analogies and SemEval 2012 Task 2) and measuring compositional similarity between noun-modifier phrases and unigrams (multiple-choice paraphrase questions).
Gamma Factors of Pairs and a Local Converse Theorem in Families

We prove a GL(n)xGL(n-1) local converse theorem for l-adic families of smooth representations of GL(n,F) where F is a finite extension of Q_p and l is different from p. To do so, we also extend the theory of Rankin-Selberg integrals, first introduced by Jacquet, Piatetski-Shapiro, and Shalika, to the setting of families, continuing previous work of the author.
Tautological ring of strata of differentials

Strata of k-differentials on smooth curves parameterize sections of the k-th power of the canonical bundle with prescribed orders of zeros and poles. Define the tautological ring of the projectivized strata using the $$\kappa $$ and $$\psi $$ classes of moduli spaces of pointed smooth curves along with the class $$\eta = \mathcal O(-1)$$ of the Hodge bundle. We show that if there is no pole of order k, then the tautological ring is generated by $$\eta $$ only, and otherwise it is generated by the $$\psi $$ classes corresponding to the poles of order k.
Expander graph and communication-efficient decentralized optimization

In this paper, we discuss how to design the graph topology to reduce the communication complexity of certain algorithms for decentralized optimization. Our goal is to minimize the total communication needed to achieve a prescribed accuracy. We discover that the so-called expander graphs are near-optimal choices. We propose three approaches to construct expander graphs for different numbers of nodes and node degrees. Our numerical results show that the performance of decentralized optimization is significantly better on expander graphs than other regular graphs.
Demixing structured superposition signals from periodic and aperiodic nonlinear observations

We consider the demixing problem of two (or more) structured high-dimensional vectors from a limited number of nonlinear observations where this nonlinearity is due to either a periodic or an aperiodic function. We study certain families of structured superposition models, and propose a method which provably recovers the components given (nearly) m = O (s) samples where s denotes the sparsity level of the underlying components. This strictly improves upon previous nonlinear demixing techniques and asymptotically matches the best possible sample complexity. We also provide a range of simulations to illustrate the performance of the proposed algorithms.