bluuebunny/crossref_metadata_2025_split huggingface dataset:
The winding path towards symbiotic autonomous systems
Authors: Saracco Roberto , Grise Kathy , Martinez Terence 
Published: August 2021

Over the next 10 years, we are likely to see the convergence of two independent evolutionary paths: one leading to an augmentation of machine capabilities; the other with the augmentation of human capabilities. This convergence will not happen at a specific point in time; instead, it will be the result of progressive overlapping, to the point that it might be difficult to identify a defining moment. The following decade will likely be quite different from the present one. 5G will probably be remembered as a transitional system, artificial intelligence (AI) as a misplaced objective. We are looking forward to a communications fabric created by autonomous systems that will exist both in the physical world as well as in cyberspace, determining a continuum that gives rise to digital reality and where intelligence is an emerging property of the ambient. Hence, the dichotomy between AI and natural intelligence will no longer exist and AI will be considered as a tool for human augmentation and as the glue connecting minds and machines.
This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
Digital twins as run-time predictive models for the resilience of cyber-physical systems: a conceptual framework
Authors: Flammini Francesco 
Published: August 2021

Digital twins (DT) are emerging as an extremely promising paradigm for run-time modelling and performability prediction of cyber-physical systems (CPS) in various domains. Although several different definitions and industrial applications of DT exist, ranging from purely visual three-dimensional models to predictive maintenance tools, in this paper, we focus on data-driven evaluation and prediction of critical dependability attributes such as safety. To that end, we introduce a conceptual framework based on autonomic systems to host DT run-time models based on a structured and systematic approach. We argue that the convergence between DT and self-adaptation is the key to building smarter, resilient and trustworthy CPS that can self-monitor, self-diagnose and—ultimately—self-heal. The conceptual framework eases dependability assessment, which is essential for the certification of autonomous CPS operating with artificial intelligence and machine learning in critical applications.
This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
A screening pipeline identifies a broad-spectrum inhibitor of bacterial AB toxins with cross protection against influenza A virus H1N1 and SARS-CoV-2
Authors: Wu Yu , Mahtal Nassim , Swistak Léa , Sagadiev Sara , Acharya Mridu , Demeret Caroline , van der Werf Sylvie , Guivel-Benhassine Florence , Schwartz Olivier , Petracchini Serena , Mettouchi Amel , Paillares Eléa , Caramelle Lucie , Couvineau Pierre , Thai Robert , Barbe Peggy , Keck Mathilde , Brodin Priscille , Machelart Arnaud , Sencio Valentin , Trottein François , Sachse Martin , Chicanne Gaëtan , Payrastre Bernard , Ville Florian , Kreis Victor , Popoff Michel-Robert , Johannes Ludger , Cintrat Jean-Christophe , Barbier Julien , Gillet Daniel , Lemichez Emmanuel 
Published: August 2021

ABSTRACTA challenge for the development of host-targeted anti-infectives against a large spectrum of AB-like toxin-producing bacteria encompasses the identification of chemical compounds corrupting toxin transport through both endolysosomal and retrograde pathways. Here, we performed a high-throughput screening of small chemical compounds blocking active Rac1 proteasomal degradation triggered by the Cytotoxic Necrotizing Factor-1 (CNF1) toxin, followed by orthogonal screens against two AB toxins hijacking defined endolysosomal (Diphtheria toxin) or retrograde (Shiga-like toxin 1) pathways to intoxicate cells. This led to the identification of the molecule N-(3,3-diphenylpropyl)-1-propyl-4-piperidinamine, referred to as C910. This compound induces the swelling of EEA1-positive early endosomes, in absence of PIKfyve kinase inhibition, and disturbs the trafficking of CNF1 and the B-subunit of Shiga toxin along the endolysosomal or retrograde pathways, respectively. Together, we show that C910 protects cells against 8 bacterial AB toxins including large clostridial glucosylating toxins from Clostridium difficile. Of interest, C910 also reduced viral infection in vitro including influenza A virus subtype H1N1 and SARS-CoV-2. Moreover, parenteral administration of C910 to the mice resulted in its accumulation in lung tissues and reduced lethal influenza infection.
Pairwise Relative Distance (PRED) is an intuitive and robust metric for assessing vector similarity and class separability
Authors: Mittal Aarush Mohit , Lin Andrew C. , Gupta Nitin 
Published: August 2021

AbstractScientific studies often require assessment of similarity between ordered sets of values. Each set, containing one value for every dimension or class of data, can be conveniently represented as a vector. The commonly used metrics for vector similarity include angle-based metrics, such as cosine similarity or Pearson correlation, which compare the relative patterns of values, and distance-based metrics, such as the Euclidean distance, which compare the magnitudes of values. Here we evaluate a newly proposed metric, pairwise relative distance (PRED), which considers both relative patterns and magnitudes to provide a single measure of vector similarity. PRED essentially reveals whether the vectors are so similar that their values across the classes are separable. By comparing PRED to other common metrics in a variety of applications, we show that PRED provides a stable chance level irrespective of the number of classes, is invariant to global translation and scaling operations on data, has high dynamic range and low variability in handling noisy data, and can handle multi-dimensional data, as in the case of vectors containing temporal or population responses for each class. We also found that PRED can be adapted to function as a reliable metric of class separability even for datasets that lack the vector structure and simply contain multiple values for each class.
Changes in resting state functional connectivity associated with dynamic adaptation of wrist movements
Authors: Farrens Andria J. , Vahdat Shahabeddin , Sergi Fabrizio 
Published: August 2021

Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics (1). Adapted motor plans are consolidated into motor memories that contribute to better performance on re-exposure to the same dynamic condition. In parallel, dynamic perturbations can be compensated for by alternate motor control processes, such as co-contraction, that contribute to error reduction (2). Whether these control strategies share the same neural resources for memory formation is unclear. To address this gap in knowledge, we used a novel fMRI-compatible wrist robot, the MR-SoftWrist (3), to identify neural processes specific to dynamic adaptation and subsequent memory formation. Using the MR-SoftWrist, we acquired fMRI during a motor performance and a dynamic perturbation task to localize brain networks of interest. Resting state fMRI scans were acquired immediately before and after task performance to quantify changes in resting state functional connectivity (rsFC) within these networks. Twenty-four hours later, we assessed behavioral retention of training. A variance decomposition analysis was used to isolate behavior associated with adaptation versus alternate error reduction strategies. Immediately after the dynamic perturbation task, rsFC significantly increased within the corticothalamic-cerebellar network of the trained wrist and decreased interhemispherically within the cortical sensorimotor network. These changes were associated to behavioral measures of initial acquisition and retention, indicative of memory formation. Variance decomposition analysis revealed that increases within the cortico-thalamic-cerebellar network were associated with adaptation, while interhemispheric decreases in rsFC within the sensorimotor network were associated with alternate error reduction processes.Significance StatementMotor memory formation processes have been studied using resting state functional connectivity (rsFC) before and after exposure to adaptation tasks. However, due to technical limitations, previous studies have not investigated rsFC within brain regions localized during task execution, nor quantified rsFC within minutes after task performance. The present study used an fMRI-compatible wrist robot to localize relevant brain regions during dynamic adaptation within the cortico-thalamic-cerebellar network and bilateral sensorimotor network. Immediately following dynamic adaptation, we measured significant changes in rsFC within these networks, that were associated with adaptation behavior and with gains in behavior assessed 24 hours later, indicative of memory formation. Variance decomposition analysis identified distinct rsFC networks associated with adaptation specific processes, and with alternate motor control strategies.
Targeted Reactivation of X-linked Endogenous FOXP3 Gene from X-chromosome Inactivation in Human Female Breast Cancer Cells
Authors: Cui Xuelian , Xu Zhifang , Wang Shuaibin , Li Xin , Stringer-Reasor Erica , Bae Sejong , Zeng Leiping , Zhao Dehua , Liu Runhua , Qi Lei S. , Wang Lizhong 
Published: August 2021

AbstractUnlike autosomal tumor suppressors, which must be inactivated by a two-hit Knudson mechanism, X-linked tumor suppressors can be inactivated by a single hit due to X-chromosome inactivation (XCI). Here, we argue that targeted reactivation of the non-mutated allele from XCI offers a potential therapy for female breast cancers. Towards this goal, we developed a dual CRISPR interference and activation (CRISPRi/a) approach for simultaneously silencing and reactivating multiple X-linked genes using two orthogonal, nuclease-deficient CRISPR/Cas9 (dCas9) proteins. We verified the efficacy for use of Streptococcus pyogenes (Sp) dCas9-KRAB for silencing XIST and Staphylococcus aureus (Sa) dCas9-VPR for activating FOXP3 in various cell lines of human female breast cancers. We confirmed CRISPR reactivation of the non-mutated copy of FOXP3 from XCI in human breast cancer CRL2316 cells, which express a synonymous heterozygous mutation (p.L266L; c.798G>C) in the coding region of FOXP3. Further, simultaneous silencing of XIST from XCI led to enhanced and prolonged FOXP3 reactivation. We optimized CRISPRa by fusing SadCas9 to the demethylase TET1 and observed enhanced FOXP3 activation. Analysis of the conserved CpG-rich region of FOXP3 intron 1 confirmed that CRISPRi/a-mediated simultaneous FOXP3 activation and XIST silencing were accompanied by elevated H4 acetylation, including H4K5ac, H4K8ac, and H4K16ac, and H3K4me3 and lower DNA methylation. This indicates that CRISPRi/a targeting to XIST and FOXP3 loci alters their transcription and their nearby epigenetic modifications. The simultaneous activation and repression of the X-linked, endogenous FOXP3 and XIST from XCI offers a useful research tool and a potential therapeutic for female breast cancers. This approach also provides new routes of targeted therapy for other X-chromosome-linked genetic disorders.
Quaternary structure independent folding of voltage-gated ion channel pore domain subunits
Authors: Arrigoni Cristina , Lolicato Marco , Shaya David , Rohaim Ahmed , Findeisen Felix , Colleran Claire M. , Dominik Pawel , Kim Sangwoo S. , Schuermann Jonathan , Kossiakoff Anthony A. , Minor Daniel L. 
Published: August 2021

AbstractEvery voltage-gated ion channel (VGIC) superfamily member has an ion conducting pore consisting of four pore domain (PD) subunits that are each built from a common plan comprising an antiparallel transmembrane helix pair, a short, obliquely positioned helix (the pore helix), and selectivity filter. The extent to which this structure, the VGIC-PD fold, relies on the extensive quaternary interactions observed in PD assemblies is unclear. Here, we present crystal structures of three bacterial voltage-gated sodium channel (BacNav) pores that adopt a surprising set of non-canonical quaternary structures and yet maintain the native tertiary structure of the PD monomer. This context-independent structural robustness demonstrates that the VGIC-PD fold, the fundamental VGIC structural building block, can adopt its native-like tertiary fold independent of native quaternary interactions. In line with this observation, we find that the VGIC-PD fold is not only present throughout the VGIC superfamily and other channel classes but has homologs in diverse transmembrane and soluble proteins. Characterization of the structures of two synthetic Fabs (sFabs) that recognize the VGIC-PD fold shows that such sFabs can bind purified full-length channels and indicates that non-canonical quaternary PD assemblies can occur in the context of complete VGICs. Together, our data demonstrate that the VGIC-PD structure can fold independently of higher-order assembly interactions and suggest that full-length VGIC PDs can access previously unknown non-canonical quaternary states. These PD properties have deep implications for understanding how the complex quaternary architectures of VGIC superfamily members are achieved and point to possible evolutionary origins of this fundamental VGIC structural element.
Lupus Gut Microbiota Transplants Cause Autoimmunity and Inflammation
Authors: Ma Yiyangzi , Guo Ruru , Sun Yiduo , Li Xin , He Lun , Li Zhao , Silverman Gregg J. , Chen Guobing , Gao Feng , Yuan Jiali , Wei Qiang , Li Mengtao , Lu Liangjing , Niu Haitao 
Published: August 2021

ABSTRACTBackgroundThe etiology of systemic lupus erythematosus (SLE) is multifactorial. Recently, growing evidence suggests that the microbiota plays a role in SLE, yet whether gut microbiota participates in the development of SLE remains largely unknown. To investigate this issue, we carried out 16s rDNA sequencing analyses in a cohort of 18 female un-treated active SLE patients and 7 female healthy controls, and performed fecal microbiota transplantation from patients and healthy controls to germ-free mice.ResultsCompared to the healthy controls, we found no significant different microbial diversity but some significantly different species in SLE patients including Turicibacter genus and other 5 species. Fecal transfer from SLE patients to germ free (GF) C57BL/6 mice caused GF mice to develop a series of lupus-like phenotyptic features, which including an increased serum autoimmune antibodies, and imbalanced cytokines, altered distribution of immune cells in mucosal and peripheral immune response, and upregulated expression of genes related to SLE in recipient mice that received SLE fecal microbiota transplantation (FMT). Moreover, the metabolism of histidine was significantly altered in GF mice treated with SLE patient feces, as compared to those which received healthy fecal transplants.ConclusionsOverall, our results describe a causal role of aberrant gut microbiota in contributing to the pathogenesis of SLE. The interplay of gut microbial and histidine metabolism may be one of the mechanisms intertwined with autoimmune activation in SLE.
Respiratory Alkalosis Provokes Spike-Wave Discharges in Seizure-Prone Rats
Authors: Salvati Kathryn A. , Souza George M.P.R. , Lu Adam C. , Ritger Matthew L. , Guyenet Patrice G. , Abbott Stephen B. , Beenhakker Mark P. 
Published: August 2021

AbstractHyperventilation reliably provokes seizures in patients diagnosed with absence epilepsy. Despite this predictable patient response, the mechanisms that enable hyperventilation to powerfully activate absence seizure-generating circuits remain entirely unknown. Using the WAG/Rij rat, an established rodent model of absence epilepsy, we demonstrate that absence seizures are highly sensitive to arterial carbon dioxide, suggesting that seizure-generating circuits are sensitive to pH. Moreover, hyperventilation consistently activated neurons within the intralaminar nuclei of the thalamus, a structure implicated in seizure generation. We show that intralaminar thalamus also contains pH-sensitive neurons. Collectively, these observations suggest that hyperventilation activates pH-sensitive neurons of the intralaminar nuclei to provoke absence seizures.
SMOG 2 and OpenSMOG: Extending the limits of structure-based models
Authors: de Oliveira Antonio B. , Contessoto Vinícius G. , Hassan Asem , Byju Sandra , Wang Ailun , Wang Yang , Dodero-Rojas Esteban , Mohanty Udayan , Noel Jeffrey K. , Onuchic Jose N. , Whitford Paul C. 
Published: August 2021

AbstractApplying simulations with structure-based (Gō-like) models has proven to be an effective strategy for investigating the factors that control biomolecular dynamics. The common element of these models is that some (or all) of the intra/inter-molecular inter-actions are explicitly defined to stabilize an experimentally-determined structure. To facilitate the development and application of this broad class of models, we previously released the SMOG 2 software package. This suite allows one to easily customize and distribute structure-based (i.e. SMOG) models for any type of polymer-ligand system. Since its original release, user feedback has driven the implementation of numerous enhancements. Here, we describe recent extensions to the software and demonstrate the capabilities of the most recent version, SMOG v2.4. Changes include new tools that aid user-defined customization of force fields, as well as an interface with the OpenMM simulation libraries (OpenSMOG v1.0). To illustrate the utility of these advances, we present several applications of SMOG2 and OpenSMOG, which include systems with millions of atoms, long polymers and explicit ions. We also highlight how one can incorporate non-structure-based (e.g. AMBER-based) energetics to define a hybrid class of models. The representative applications include large-scale rearrangements of the SARS-CoV-2 Spike protein, the HIV-1 capsid in the presence of explicit ions, and crystallographic lattices of ribosomes and proteins. In summary, SMOG 2 and OpenSMOG provide robust support for researchers who seek to apply structure-based models to large and/or intricate biomolecular systems.
Constructing Functional Networks of Phosphorylation Sites Using Co-Phosphorylation
Authors: Ayati Marzieh , Yılmaz Serhan , Chance Mark R. , Koyutürk Mehmet 
Published: August 2021

AbstractProtein phosphorylation is a ubiquitous regulatory mechanism that plays a central role in cellular signaling. According to recent estimates, up to 70% of human proteins can be phosphorylated. Therefore, characterization of phosphorylation dynamics is critical for understanding a broad range of biological and biochemical processes. Technologies based on mass spectrometry are rapidly advancing to meet the needs for high-throughput screening of phosphorylation. These technologies enable untargeted quantification of thousands of phosphorylation sites in a given sample. Many labs are already utilizing these technologies to comprehensively characterize signaling landscapes by examining perturbations with drugs and knockdown approaches, or by assessing diverse phenotypes in cancers, neuro-degerenational diseases, infectious diseases, and normal development. Here, we comprehensively investigate the concept of “co-phosphorylation”, defined as the correlated phosphorylation of a pair of phosphosites across various biological states. We integrate nine publicly available phospho-proteomics datasets for various diseases (including breast cancer, ovarian cancer and Alzhemier’s disease) and utilize functional data related to sequence, evolutionary histories, kinase annotations, and pathway annotations to investigate the functional relevance of co-phosphorylation. Our results across a broad range of studies consistently show that functionally associated sites tend to exhibit significant positive or negative co-phosphorylation. Specifically, we show that co-phosphorylation can be used to predict with high precision the sites that are on the same pathway or that are targeted by the same kinase. Overall, these results establish co-phosphorylation as a useful resource for analyzing phospho-proteins in a network context, which can help extend our knowledge on cellular signaling and its dysregulation.
Optimized analysis for sensitive detection and analysis of single proteins via interferometric scattering microscopy
Authors: Dastjerdi Houman Mirzaalian , Dahmardeh Mahyar , Gemeinhardt André , Mahmoodabadi Reza Gholami , Köstler Harald , Sandoghdar Vahid 
Published: August 2021

AbstractIt has been shown that interferometric detection of Rayleigh scattering (iSCAT) can reach an exquisite sensitivity for label-free detection of nano-matter, down to single proteins. The sensitivity of iSCAT detection is intrinsically limited by shot noise, which can be indefinitely improved by employing higher illumination power or longer integration times. In practice, however, a large speckle-like background and technical issues in the experimental setup limit the attainable signal-to-noise ratio. Strategies and algorithms in data analysis are, thus, crucial for extracting quantitative results from weak signals, e.g. regarding the mass (size) of the detected nano-objects or their positions. In this article, we elaborate on some algorithms for processing iSCAT data and identify some key technical as well as conceptual issues that have to be considered when recording and interpreting the data. The discussed methods and analyses are made available in the extensive python-based platform, PiSCAT§.
Early adopters’ responses to a virtual tourism product: Airbnb’s online experiences
Authors: Cenni Irene , Vásquez Camilla 
Published: August 2021

Purpose
In April 2020, Airbnb launched “Online Experiences,” (OE) a virtual tourism product responding to pandemic-related restrictions on physical travel. The purpose of this study is to explore the characteristics of this innovative product that were most salient to consumers and in so doing, to provide preliminary insights into the factors related to its success.

Design/methodology/approach
Using a grounded theory approach in this qualitative study, the authors investigated a sample of 500 online consumer reviews of 100 different Airbnb OE. The analysis identified five major themes associated with reviewers’ positive evaluations of OEs.

Findings
The study’s findings corroborate prior research on peer-to-peer businesses regarding the centrality of the host and the social appeal of such services, yet they also reveal newer, multifaceted expectations for OEs’ hosts. Further, consumers reacted positively to both the entertaining and educational aspects of OEs. Finally, reviewers’ comments reflect factors related to pandemic-related conditions such as seeking social interaction and virtual escape, yet they also identify factors that suggest the durative appeal of OEs as a tourism product (e.g. “repeatability” of OEs; OEs as sites for virtual connection with family/friends; OEs as a marketing tool for future travel).

Originality/value
To the best of my knowledge, this is one of the first studies investigating this recently launched virtual tourism product. The findings, thus, represent an important empirical baseline for future research on this topic.