bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insights into the Interactions of Peptides with Monolayer-Protected Metal Nanoclusters
Authors: Tiwari Vikas , Garg Sonali , Karmakar Tarak 
Published: November 2022

AbstractMonolayer-protected atomically precise metal nanoclusters (MPC) are an important class of molecules that have potential applications in catalysis, imaging, and drug delivery. Recent studies have shown that peptide-based drugs can be complexed with MPCs to avoid enzymatic degradation and get delivered to targeted cells. Although the MPCs potential role in imaging and drug delivery processes have been studied, for their impactful use, specific molecular interactions between MPCs and biomolecules, mainly proteins and peptides should be explored in detail. In this work, we have carried out atomistic molecular dynamics simulations to investigate the interactions between Au-based MPCs and an anticancer peptide, melittin. The MEL peptides get attached to the MPCs surface by the formation of multiple hydrogen bonds between the peptide amino acid residues with MPCs ligands. Additionally, the positively charged residues such as Lys and Arg, the Trp, and the N-terminal of the peptide anchor strongly to the MPC core playing a crucial role in the peptide’s overall stabilization on the MPC surface.
Prediction-error signals in anterior cingulate cortex drive task-switching
Authors: Cole Nicholas , Harvey Matthew , Myers-Joseph Dylan , Gilra Aditya , Khan Adil G. 
Published: November 2022

AbstractTask-switching is a fundamental cognitive ability that allows animals to update their knowledge of current rules or contexts. Detecting discrepancies between predicted and observed events is essential for this process. However, little is known about how the brain computes cognitive prediction-errors and whether neural prediction-error signals are causally related to task-switching behaviours. Here we trained mice to use a prediction-error to switch, in a single trial, between responding to the same stimuli using two distinct rules. Optogenetic silencing and un-silencing, together with widefield and two-photon calcium imaging revealed that the anterior cingulate cortex (ACC) was specifically required for this rapid task-switching, but only when it exhibited neural prediction-error signals. These prediction-error signals were projection-target dependent and were larger preceding successful behavioural transitions. An all-optical approach revealed a disinhibitory interneuron circuit required for successful prediction-error computation. These results reveal a circuit mechanism for computing prediction-errors and transitioning between distinct cognitive states.
Global Endometrial DNA Multi-omics Analysis Reveals Insights into mQTL Regulation and Associated Endometriosis Disease Risk
Authors: Mortlock Sally , Houshdaran Sahar , Kosti Idit , Rahmioglu Nilufer , Nezhat Camran , Vitonis Allison F. , Andrews Shan V. , Grosjean Parker , Paranjpe Manish , Horne Andrew W. , Jacoby Alison , Lager Jeannette , Opoku-Anane Jessica , Vo Kim Chi , Manvelyan Evelina , Sen Sushmita , Ghukasyan Zhanna , Collins Frances , Santamaria Xavier , Saunders Philippa , Kober Kord , McRae Allan F. , Terry Kathryn L. , Vallvé-Juanico Júlia , Becker Christian , Rogers Peter A.W. , Irwin Juan C. , Zondervan Krina , Montgomery Grant W. , Missmer Stacey , Sirota Marina , Giudice Linda 
Published: November 2022

AbstractEndometriosis is a leading cause of pain and infertility affecting millions of women globally. Identifying biologic and genetic effects on DNA methylation (DNAm) in endometrium increases understanding of mechanisms that influence gene regulation predisposing to endometriosis and offers an opportunity for novel therapeutic target discovery. Herein, we characterize variation in endometrial DNAm and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genome-wide genotype data and methylation at 759,345 DNAm sites in endometrial samples from 984 deeply-phenotyped participants. We identify significant differences in DNAm profiles between menstrual cycle phases and at four DNAm sites between stage III/IV endometriosis and controls. We estimate that 15.4% of the variation in endometriosis is captured by DNAm, and identify DNAm networks associated with endometriosis. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independentcis-mQTL including some tissue-specific effects. We find significant differences in DNAm profiles between endometriosis sub- phenotypes and a significant association between genetic regulation of methylation in endometrium and disease risk, providing functional evidence for genomic targets contributing to endometriosis risk and pathogenesis.
PIEZO2 in somatosensory neurons controls gastrointestinal transit
Authors: Servin-Vences M. Rocio , Lam Ruby M. , Koolen Alize , Wang Yu , Saade Dimah N. , Loud Meaghan , Kacmaz Halil , Beyder Arthur , Marshall Kara L. , Bönnemann Carsten G. , Chesler Alexander T. , Patapoutian Ardem 
Published: November 2022

SummaryThe gastrointestinal tract is in a state of constant motion. These movements are tightly regulated by the presence of food and help digestion by mechanically breaking down and propelling gut content. Mechanical sensing in the gut is thought to be essential for regulating motility; however, the identity of the neuronal populations, the molecules involved, and the functional consequences of this sensation are unknown. Here, we show that humans lacking PIEZO2 exhibit impaired bowel sensation and motility. Piezo2 in mouse dorsal root but not nodose ganglia is required to sense gut content, and this activity slows down food transit rates in the stomach, small intestine, and colon. Indeed, Piezo2 is directly required to detect colon distensionin vivo. Our study unveils the mechanosensory mechanisms that regulate the transit of luminal contents throughout the gut, which is a critical process to ensure proper digestion, nutrient absorption, and waste removal.HighlightsIndividuals with PIEZO2 syndrome present impaired bowel sensation and gastrointestinal dysfunction.PIEZO2 in DRG neurons plays an important role in regulating gut motility.Lack of PIEZO2 from sensory neurons accelerates gastric emptying and intestinal transit.DRG neurons detect colon distension via PIEZO2.
Conformational changes in the essentialE. coliseptal cell wall synthesis complex suggest an activation mechanism
Authors: Britton Brooke M. , Yovanno Remy A. , Costa Sara F. , McCausland Joshua , Lau Albert Y. , Xiao Jie , Hensel Zach 
Published: November 2022

ABSTRACTThe bacterial divisome, a macromolecular machine that is composed of more than thirty proteins inE. coli, orchestrates the essential process of cell wall constriction during cell division. Novel antimicrobial strategies can target protein-protein interactions within the divisome and will benefit from insights into divisome structure and dynamics. In this work, we combined structure prediction, molecular dynamics simulation, single-molecule imaging, and mutagenesis to construct a model of the core complex of theE. colidivisome composed of the essential septal cell wall synthase complex formed by FtsW and FtsI, and its regulators FtsQ, FtsL, FtsB, and FtsN. We observed extensive interactions in four key regions in the periplasmic domains of the complex. FtsQ, FtsL, and FtsB scaffold FtsI in an extended conformation with the FtsI transpeptidase domain lifted away from the membrane through interactions among the C-terminal domains. FtsN binds between FtsI and FtsL in a region rich in residues with superfission (activating) and dominant negative (inhibitory) mutations. Mutagenesis experimentsin celluloandin silicorevealed that the essential domain of FtsN functions as a tether to tie FtsI and FtsL together, impacting interactions between the anchor-loop of FtsI and the putative catalytic region of FtsW, suggesting a mechanism of how FtsN activates the cell wall synthesis activities of FtsW and FtsI.
The connectome of an insect brain
Authors: Winding Michael , Pedigo Benjamin D. , Barnes Christopher L. , Patsolic Heather G. , Park Youngser , Kazimiers Tom , Fushiki Akira , Andrade Ingrid V. , Khandelwal Avinash , Valdes-Aleman Javier , Li Feng , Randel Nadine , Barsotti Elizabeth , Correia Ana , Fetter Richard D. , Hartenstein Volker , Priebe Carey E. , Vogelstein Joshua T. , Cardona Albert , Zlatic Marta 
Published: November 2022

AbstractBrains contain networks of interconnected neurons, so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an insect brain (Drosophilalarva) with rich behavior, including learning, value-computation, and action-selection, comprising 3,013 neurons and 544,000 synapses. We characterized neuron-types, hubs, feedforward and feedback pathways, and cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain’s most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled powerful machine learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.One-Sentence SummaryWe generated a synaptic-resolution brain connectome and characterized its connection types, neuron types, and circuit motifs.
Reputation risk during dishonest social decision-making modulates anterior insular and cingulate cortex activity and connectivity
Authors: Dupont Lennie , Santangelo Valerio , Azevedo Ruben , Panasiti Maria Serena , Aglioti Salvatore Maria 
Published: November 2022

AbstractTo explore the neural underpinnings of (dis)honest decision making under quasi-ecological conditions, we used an fMRI adapted version of a card game in which deceptive or truthful decisions are made to an opponent, with or without the risk of getting caught by them. Dishonest decisions were associated to increased activity in a cortico-subcortical circuit including the bilateral anterior cingulate cortex (ACC), anterior insula (AI), left dorsolateral prefrontal cortex, supplementary motor area, and right caudate. Crucially, deceptive immoral decisions under reputation risk enhanced activity of – and functional connectivity between – the bilateral ACC and left AI, suggesting the need for heightened emotional processing and cognitive control when making immoral decisions under reputation risk. Tellingly, more manipulative individuals required less involvement of the ACC during risky self-gain lies but more involvement during other-gain truths, pointing to the need of cognitive control only when going against one’s own moral code.
Balance between direct and indirect pathways of the nucleus accumbens controls social behavior in mice
Authors: Le Merrer J. , Detraux B. , Gandía J. , De Groote A. , Fonteneau M. , de Kerchove d’Exaerde A. , Becker J.A.J. 
Published: November 2022

AbstractBackgroundDeficient social interactions are a hallmark of major neuropsychiatric disorders, and cumulating evidence point to altered social reward and motivation as key underlying mechanisms in these pathologies. In the present study, we aimed at assessing the role of the two striatal projecting neuronal (SPN) populations bearing either D1R or D2R dopamine receptors (D1R- and D2R-SPNs), in modulating social behavior and other behaviors often altered in neuropsychiatric disorders.MethodsWe selectively ablated D1R- and D2R-SPNs using an inducible diphtheria toxin receptor (DTR)-mediated cell targeting strategy and assessed social behavior as well as repetitive/perseverative behavior, motor function and anxiety levels. We tested the effects of optogenetic stimulation of D2R-SPNs in theNucleus Accumbens(NAc) and pharmacological compounds repressing D2R-SPN.ResultsTargeted deletion of D1R-SPNs in the NAc blunted social behavior in mice, facilitated skill motor learning and increased anxiety levels. These behaviors were normalized by pharmacological inhibition of D2R-SPN, which also repressed transcription in the efferent nucleus, the ventral pallidum (VP). In contrast, ablation of D1R-SPNs in the dorsal striatum had no impact on social behavior, impaired motor skill learning, and decreased anxiety levels. Deletion of D2R-SPNs in the NAc also produced motor stereotypies but facilitated social behavior and impaired skill motor learning. We mimicked excessive D2R-SPN activity by optically stimulating D2R-SPNs in the NAc and evidenced a severe deficit in social interaction that was prevented by D2R-SPN pharmacological inhibition.ConclusionsRepressing D2R-SPN activity may represent a promising therapeutic strategy to relieve social deficit in neuropsychiatric disorders.
A study on experimental bias in post-translational modification predictors
Authors: Zuallaert Jasper , Ramasamy Pathmanaban , Bouwmeester Robbin , Callewaert Nico , Degroeve Sven 
Published: November 2022

AbstractProtein post-translational modifications (PTMs) play an important role in numerous biological processes by significantly affecting protein structure and dynamics. Effective computational methods that provide a sequence-based prediction of PTM sites are desirable to guide functional experiments. Whereas these methods typically train neural networks on one-hot encoded amino acid sequences, protein language models carry higher-level pattern information that may improve sequence based prediction performance and hence constitute the current edge of the field. In this study, we first evaluate the training of convolutional neural networks on top of various protein language models for sequence based PTM prediction. Our results show substantial prediction accuracy improvements for various PTMs with current procedures of dataset compilation and model performance evaluation. We then used model interpretation methods to study what these advanced models actually base their learning on. Importantly for the entire field of PTM site predictors trained on proteomics-derived data, our model interpretation and transferability experiments reveal that the current approach to compile training datasets based on proteomics data leads to an artefactual protease-specific training bias that is exploited by the prediction models. This results in an overly optimistic estimation of prediction accuracy, an important caveat in the application of advanced machine learning approaches to PTM prediction based on proteomics data. We suggest a partial solution to reduce this data bias by implementing negative sample filtering, only allowing candidate PTM sites in matched peptides that are present in the experimental metadata.Availability and implementationThe prediction tool, with training and evaluation code, trained models, datasets, and predictions for various PTMs are available athttps://github.com/jasperzuallaert/PhosphoLingo.Contactsven.degroeve@vib-ugent.beandnico.callewaert@vib-ugent.beSupplementary informationSupplementary materials are available atbioRxiv.
Consumer attitudes and sociodemographic profiles in purchasing organic food products: evidence from a Greek and Swedish survey
Authors: Diagourtas Georgios , Kounetas Kostas Elias , Simaki Vasiliki 
Published: November 2022

PurposeThis study explores Greek and Swedish consumers' attitude towards organic food consumption in order to demonstrate possible differences that can be identified based on health and ecological consciousness beliefs rather than demographic factors. The examination of an emerging and a more mature market allow the authors to provide more targeted marketing strategies that possibly increase organic food consumption in both countries.Design/methodology/approachThe authors adopt an econometric approach to the analysis of consumer behavior in relation to organic food consumption in Sweden and Greece. More specifically, the authors examine the motivations and postexperiences of organic food consumers of different socioeconomic profiles in these two countries, one in northern and one in southern Europe. The authors apply an ordered logistic regression analysis model to map out the interaction between consumer attitudes and sociodemographic variables.FindingsThe authors results show that consumers in Sweden more frequently purchase organic foods than consumers in Greece. Environmental protection and ethical values increase the odds for Swedish organic food consumers to buy organic food products. Health consciousness and family well-being are perceived as factors that increase the odds for Greek organic food consumers to buy organic foods. Sociodemographic factors do not play a pivotal role for consumer behavior in relation to organic food in both countries.Originality/valueThis study distinguishes between organic food consumers in two countries with different levels of organic food production and export activity, size of organic market, national organic labeling system and legal definition and standards of organic food. Within these differences, the organic food industry could align its marketing efforts better rather focus on simplistic demographics. The current view unfolds the fact that there are limited studies comparing two European markets at different stages of development and the factors that influence organic food consumer behavior.
Doing well by doing good: why is investing in university social responsibility a good business for higher education institutions cross culturally?
Authors: El-Kassar Abdul-Nasser , Makki Dania , Gonzalez-Perez Maria Alejandra , Cathro Virginia 
Published: November 2022

PurposeThis paper aims to corroborate the importance of university social responsibility (USR) for universities and to establish a rationale for their investment in a strategically implement socially responsible initiatives and programmes and gain returns from such investments. This purpose can be achieved by examining a complex conceptual model connecting USR with many desired student-related outcomes that leverage the university's competitiveness, long sustainability and contribution to the triple bottom line – “people, planet, and profit”.Design/methodology/approachThe authors conducted a cross-country comparative study using quantitative techniques. Their analysis was guided by a holistic conceptual model constructed and experimentally evaluated using obtained primary data. The robustness of the suggested model was evaluated using structural equation modelling with partial least squares.FindingsThe findings validate the hypothesized associations and indicate that adopting USR initiatives increases student satisfaction and alumni loyalty through student-university identification, perceived university image, and service quality. In addition, the cross-country analysis finds no variation in the strength of the connections owing to cultural variations, except for the association between service quality and institution image.Practical implicationsIncorporating USR at the centre of university's strategy not only complements its teaching and research goals but also answers the requirements and expectations of stakeholders, increases competitiveness and assures sustainable performance.Originality/valueThis cross-cultural USR study uses a mix of methods to show that, even though USR is important, until now, its importance has been overlooked.
A robotic 3D printing system for supporting-free manufacturing of complex model based on FDM technology
Authors: Jing Xishuang , Lv Duanping , Xie Fubao , Zhang Chengyang , Chen Siyu , Mou Ben 
Published: November 2022

Purpose
3D printing technology has the characteristics of fast forming and low cost and can manufacture parts with complex structures. At present, it has been widely used in various manufacturing fields. However, traditional 3-axis printing has limitations of the support structure and step effect due to its low degree of freedom. The purpose of this paper is to propose a robotic 3D printing system that can realize support-free printing of parts with complex structures.

Design/methodology/approach
A robotic 3D printing system consisting of a 6-degrees of freedom robotic manipulator with a material extrusion system is proposed for multi-axis additive manufacturing applications. And the authors propose an approximation method for the extrusion value E based on the accumulated arc length of the already printed points, which is used to realize the synchronous movement between multiple systems. Compared with the traditional 3-axis printing system, the proposed robotic 3D printing system can provide greater flexibility when printing complex structures and even realize curved layer printing.

Findings
Two printing experiments show that compared with traditional 3D printing, a multi-axis 3D printing system saves 47% and 79% of materials, respectively, and the mechanical properties of curved layer printing using a multi-axis 3D printing system are also better than that of 3-axis printing.

Originality/value
This paper shows a simple and effective method to realize the synchronous movement between multiple systems so as to develop a robotic 3D printing system that can realize support-free printing and verifies the feasibility of the system through experiments.
Online political engagement, cognitive skills and engagement with misinformation: evidence from Sub-Saharan Africa and the United States
Authors: Ahmed Saifuddin , Madrid-Morales Dani , Tully Melissa 
Published: November 2022

PurposeInformational use of social media facilitates political engagement. Yet, there is also evidence of the perils of frequent political engagement in misinformation propagation. This study aims to examine the association between online political engagement, perceived exposure to misinformation, individuals’ cognitive characteristics and misinformation sharing.Design/methodology/approachIn this paper, online surveys were conducted in Kenya, Nigeria and South Africa (Study 1) and the United States (Study 2).FindingsStudy 1 finds that online political engagement is positively associated with perceived exposure to and sharing of misinformation. Mediation analyses suggest that the relationship between online political engagement and misinformation sharing is mediated by perceived exposure to misinformation. Further, the likelihood of sharing misinformation is found to increase at higher levels of online political engagement, but those with low need for cognition (NFC) are more vulnerable to such sharing. Study 2 explores cognitive ability in place of NFC. The results follow similar patterns as Study 1 – online political engagement is linked to misinformation sharing via higher perceived exposure to misinformation. The authors also find that the tendency to share misinformation increases with frequent exposure to misinformation but those with lower cognitive ability are more prone to such sharing.Originality/valueIn both contexts, the data show that perceived exposure to misinformation mediates the relationship between online political engagement and misinformation sharing and those with low NFC and cognitive ability are more vulnerable. Overall, the findings offer insight into the mechanisms of political engagement and sharing misinformation.