bluuebunny/crossref_metadata_2025 huggingface dataset:
Localized non-intrusive reduced-order modelling in the operator inference framework
Authors: Geelen Rudy , Willcox Karen
Published: June 2022

This paper presents data-driven learning of localized reduced models. Instead of a global reduced basis, the approach employs multiple local approximation subspaces. This localization permits adaptation of a reduced model to local dynamics, thereby keeping the reduced dimension small. This is particularly important for reduced models of nonlinear systems of partial differential equations, where the solution may be characterized by different physical regimes or exhibit high sensitivity to parameter variations. The contribution of this paper is a non-intrusive approach that learns the localized reduced model from snapshot data using operator inference. In the offline phase, the approach partitions the state space into subregions and solves a regression problem to determine localized reduced operators. During the online phase, a local basis is chosen adaptively based on the current system state. The non-intrusive nature of localized operator inference makes the method accessible, portable and applicable to a broad range of scientific problems, including those that use proprietary or legacy high-fidelity codes. We demonstrate the potential for achieving large computational speedups while maintaining good accuracy for a Burgers’ equation governing shock propagation in a one-dimensional domain and a phase-field problem governed by the Cahn–Hilliard equation.

This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Data-driven prediction in dynamical systems: recent developments
Authors: Ghadami Amin , Epureanu Bogdan I.
Published: June 2022

In recent years, we have witnessed a significant shift toward ever-more complex and ever-larger-scale systems in the majority of the grand societal challenges tackled in applied sciences. The need to comprehend and predict the dynamics of complex systems have spurred developments in large-scale simulations and a multitude of methods across several disciplines. The goals of understanding and prediction in complex dynamical systems, however, have been hindered by high dimensionality, complexity and chaotic behaviours. Recent advances in data-driven techniques and machine-learning approaches have revolutionized how we model and analyse complex systems. The integration of these techniques with dynamical systems theory opens up opportunities to tackle previously unattainable challenges in modelling and prediction of dynamical systems. While data-driven prediction methods have made great strides in recent years, it is still necessary to develop new techniques to improve their applicability to a wider range of complex systems in science and engineering. This focus issue shares recent developments in the field of complex dynamical systems with emphasis on data-driven, data-assisted and artificial intelligence-based discovery of dynamical systems.

This article is part of the theme issue 'Data-driven prediction in dynamical systems'.
Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities
Authors: Turba Rachel , Thai Glory H. , Jacobs David K.
Published: June 2022

Coastal lagoons are an important habitat for endemic and threatened species in California that have suffered impacts from urbanization and increased drought. Environmental DNA has been promoted as a way to aid in the monitoring of biological communities, but much remains to be understood on the biases introduced by different protocols meant to overcome challenges presented by unique systems under study. Turbid water is one methodologic challenge to eDNA recovery in these systems as it quickly clogs filters, preventing timely processing of samples. We investigated biases in community composition produced by two solutions to overcome slow filtration due to turbidity: freezing of water prior to filtration (for storage purposes and long-term processing), and use of sediment (as opposed to water samples). Bias assessments of community composition in downstream eDNA analysis was conducted for two sets of primers, 12S (fish) and 16S (bacteria and archaea). Our results show that freezing water prior to filtration had different effects on community composition for each primer, especially for the 16S, when using a filter of larger pore size (3 μm). Nevertheless, pre-freezing water samples can still be a viable alternative for storage and processing of turbid water samples when focusing on fish communities (12S). The use of sediment samples as an alternative to processing water samples should be done with caution, and at minimum the number of biological replicates and/or volume sampled should be increased.
A non-classical mechanism of β-lactam resistance in Methicillin-Resistant Staphylococcus aureus (MRSA) and its effect on virulence
Authors: Satishkumar Nidhi , Lai Li-Yin , Mukkayyan Nagaraja , Vogel Bruce E. , Chatterjee Som S.
Published: June 2022

Methicillin-Resistant Staphylococcus aureus (MRSA) are pathogenic bacteria that are infamously resistant to β-lactam antibiotics, a property attributed to the mecA gene. Recent studies have reported that mutations associated with the promoter region of pbp4 demonstrated high levels of β-lactam resistance, suggesting the role of PBP4 as an important non-mecA mediator of β-lactam resistance. The pbp4 promoter-associated mutations have been detected in strains with or without mecA. Our previous studies that were carried out in strains devoid of mecA described that pbp4 promoter-associated mutations lead to PBP4 overexpression and β-lactam resistance. In this study, by introducing various pbp4 promoter-associated mutations in the genome of an MRSA strain, we demonstrate that PBP4 overexpression can supplement mecA-associated resistance in S. aureus and can lead to increased β-lactam resistance. The promoter and regulatory region of pbp4 is shared with a divergently transcribed gene, abcA, which encodes for a multidrug exporter. We demonstrate that the promoter mutations caused an upregulation of pbp4 and downregulation of abcA, confirming that the resistant phenotype is associated with PBP4 overexpression only. PBP4 has also been associated with staphylococcal pathogenesis, however, its exact role remains unclear. Using a C. elegans model, we demonstrate that strains having increased PBP4 expression are less virulent compared to wild-type strains, suggesting that β-lactam resistance mediated via PBP4 likely comes at the cost of virulence.

Importance

Our study demonstrates the ability of PBP4 to be an important mediator of β-lactam resistance in not only Methicillin-susceptible Staphylococcus aureus (MSSA) background strains as previously demonstrated, but also in MRSA strains. When present together, PBP2a and PBP4 overexpression can produce increased levels of β-lactam resistance, causing complications in treatment. Thus, this study suggests the importance of monitoring PBP4-associated resistance in clinical settings, as well as understanding the mechanistic basis of associated resistance, so that treatments targeting PBP4 may be developed. This study also demonstrates that S. aureus strains with increased PBP4 expression are less pathogenic, providing important hints about the role of PBP4 in S. aureus resistance and pathogenesis.
Factors determining success of the chronically instrumented unanesthetized fetal sheep model of human development: a retrospective cohort study
Authors: Wakefield Colin , Cao Mingju , Burns Patrick , Fecteau Gilles , Desrochers Andre , Frasch Martin G
Published: June 2022

Aim

Chronically instrumented non-anesthetized fetal sheep (CINAFS) have been the mainstay model of human fetal development for 60 years. As a large “two for one” animal model, with instrumentation of the ewe and her fetus, the model poses challenges to implement de novo and to maintain overtime at the highest standards of operating procedures to ensure its ongoing performance. A common, yet conventionally underreported issue researchers face is the rate of animal loss. Here, we investigate what determines the success of the pregnant sheep model.

Methods

We conducted a retrospective cohort study consisting of 82 experiments spanning the course of six years. Our team identified ten variables that we anticipated were likely to influence the experimental outcome, such as the time of year, animal size, and surgical complexity.

Results

The single variable identified in this study as determining the successful outcome of the experiments is the experience level of the team.

Conclusion

The CINAFS model offers enormous potential to further our understanding of human fetal development and to create interventional technologies. However, to improve the outcomes of CINAFS models, improved communication and training are needed. We discuss the implications of our findings for the successful implementation of this challenging yet scientifically advantageous animal model of human physiology.

Key points

The fetal sheep model closely mirrors the physiology of human fetal development

In addition to its high translational potential, this model is known to have some generally not reported rate of experimental failure

We show that factors such as animal characteristics & surgical complexity do not influence the experimental outcomes

Instead, the key factor in model experimental success is the level of the research team’s experience

The key factors to improve the animal model outcomes are an intra- and inter-team communication
Molecular evolution of IRG1 shapes itaconate production in metazoans and alleviates the “double-edged dilemma” of innate immune defense
Authors: Szeligowski Richard V. , Miros Francois , Saez Andres , DeCiucis Marisa , Wagner Gunter P. , Shen Hongying
Published: June 2022

Itaconate is an innate immune metabolite specifically produced in stimulated immune cells via the decarboxylation of the TCA cycle intermediate cis-aconitate. Due to its inhibition of succinate-related metabolic processes, itaconate exhibits antimicrobial properties at the expense of potentially disrupting the hosts’ own central energy metabolism, a “double-edged dilemma” of immunometabolism. To understand the evolutionary logic of itaconate biosynthesis, we investigate the evolutionary trajectory of the Irg1 gene, which codes for the itaconate-producing enzyme cis-aconitate decarboxylase (CAD). Phylogenetic analysis reveals a putative independent acquisition of metazoan and fungal Irg1 from prokaryotic sources. The metazoan Irg1 underwent duplication in vertebrates and a subsequent loss of one paralog in mammals, a process that removes the mitochondrial targeting sequences (MTS) and relocates CAD outside of the mitochondrial matrix thus preventing a direct inhibition of energy metabolism. Experiments in the most diverged metazoan species that are known to contain Irg1, oysters and amphioxus, reveal that the expression of primitive Irg1 genes is induced by innate immune stimulants in invertebrates and basal chordates, suggesting an already specialized role of itaconate production for innate immune defense in early bilaterians. Our combined in silico and experimental analysis of Irg1 highlights that a trend of tightened transcriptional regulation and sequence-level change optimizes itaconate biosynthesis for innate immunity, a mechanism that may be broadly utilized to resolve other types of double-edged dilemmas in immunometabolism.
Binding of a blast fungus Zinc-finger fold effector to a hydrophobic pocket in the host exocyst subunit Exo70 modulates immune recognition in rice
Authors: De la Concepcion Juan Carlos , Fujisaki Koki , Bentham Adam R. , Mireles Neftaly Cruz , de Medina Hernandez Victor Sanchez , Shimizu Motoki , Lawson David M. , Kamoun Sophien , Terauchi Ryohei , Banfield Mark J.
Published: June 2022

Exocytosis plays an important role in plant-microbe interactions, both in pathogenesis and symbiosis. Exo70 proteins are integral components of the exocyst, an octameric complex that mediates tethering of vesicles to membranes in eukaryotes. Although plant Exo70s are known to be targeted by pathogen effectors, the underpinning molecular mechanisms and the impact of this interaction on infection is poorly understood. Here, we show the molecular basis of the association between the effector AVR- Pii of the blast fungus Maganaporthe oryzae and rice Exo70 alleles OsExo70F2 and OsExo70F3, which is sensed by the immune receptor pair Pii via an integrated RIN4/NOI domain. The crystal structure of AVR-Pii in complex with OsExo70F2 reveals that the effector binds to a conserved hydrophobic pocket in Exo70, defining a new effector/target binding interface. Structure-guided and random mutagenesis validates the importance of AVR-Pii residues at the Exo70 binding interface to sustain protein association and disease resistance in rice when challenged with fungal strains expressing effector mutants. Further, the structure of AVR-Pii defines a novel Zinc- finger effector fold (ZiF) distinct from the MAX fold previously described for the majority of characterized M. oryzae effectors. Our data suggests that blast fungus ZiF effectors bind a conserved Exo70 interface to manipulate plant exocytosis and that these effectors are also baited by plant immune receptors, pointing to new opportunities for engineering disease resistance.

Significance statement

Plant diseases destroy ∼20-30% of annual crop production, contributing to global food insecurity. Discovering how pathogen effectors target host proteins to promote virulence is essential for understanding pathogenesis and can be used for developing disease resistant crops. Here, we reveal the structural basis of how an effector from the blast pathogen (AVR-Pii) binds a specific host target (rice Exo70), and how this underpins immune recognition. This has implications for understanding the molecular mechanisms of blast disease and for the engineering of new recognition specificities in plant immune receptors to confer resistance to a major crop pathogen.
An integrated approach to study chromatin and transcriptional dynamics throughout the cell cycle without pharmacological inhibition
Authors: Shlyueva Daria , Teed-Singer Sarah , Zhan Yingqian , Koche Richard , Helin Kristian
Published: June 2022

The cellular and nuclear states are constantly changing and closely linked to DNA replication and cell division, defining cell cycle phases. Pharmacological inhibition is a widely used strategy to enrich for specific phases to study them in isolation. However, chemical-induced cell cycle synchronization may influence chromatin openness and gene expression compared to unperturbed cell cycle states. Here, we use different synchronization methods to obtain G1, S and G2/M phases from mouse embryonic stem cells (mESCs) and profile their chromatin accessibility and post- translational modifications as well as steady and nascent transcripts levels. We demonstrate that synchronization with thymidine and nocodazole leads to dramatic changes in chromatin compaction and gene expression, which only partially resemble bona fide cell cycle-dependent differences. Blocking with CDK1 inhibitor results in efficient synchronization and evokes moderate changes in chromatin accessibility, resembling G2/M phase. Correlative analysis suggests that cell cycle-specific variations in chromatin openness in unperturbed mESCs are mediated by CDK1 substrates and CTCF. This integrated strategy can be applied to most cultured cell lines under any conditions and holds the potential to further our understanding of cell cycle- dependent susceptibility to external cues and chromatin regulation.
Neonatal hepatic myeloid progenitors expand and propagate liver inflammation in mice
Authors: Alkhani Anas , Korsholm Cathrine , Mohamedaly Sarah , Levy Claire S. , Duwaerts Caroline C. , Pietras Eric M. , Nijagal Amar
Published: June 2022

Background and Aims

Biliary atresia is a rapidly progressive pediatric inflammatory disease of the liver that leads to cirrhosis and necessitates liver transplantation. The rapid progression from liver injury to fulminant liver failure in children with biliary atresia suggests that factors specific to the perinatal hepatic environment are important for disease propagation. Hematopoietic stem and progenitor cells (HSPCs) serve as central hubs of inflammation and rely on inflammatory signals for their emigration from the liver to the bone marrow in neonatal mice. We hypothesized that HSPCs are critical for the propagation of perinatal liver inflammation (PLI).

Methods

Newborn BALB/c mice were injected intraperitoneally with 1.5×106 focus forming units of Rhesus Rotavirus (RRV) to induce PLI or with PBS as control. Livers from RRV- and PBS-injected mice were compared using histology and flow cytometry. To determine the effects of HSPCs on perinatal inflammation, RRV-infected neonatal mice were injected with anti-CD47 and anti-CD117 to deplete HSPCs.

Results

RRV-induced PLI led to a significant increase in the number of common myeloid progenitors (Flt3+ CMPs: PBS=4426±247.2 vs RRV=9856±2009, p=0.0316; Flt3- CMPs: PBS=3063±254.9 vs RRV=9743±1539, p=0.0012). We corroborated these findings by observing a significant increase in CD34+ hematopoietic progenitors/cm2 in histological sections of RRV-infected livers (PBS=4.977±2.573 vs RRV=27.09±12.49, p=0.0075). Elimination of progenitors through antibody-mediated myeloablation rescued animals from PLI and significantly increased survival (RRV+isotype control 55.56% vs RRV+myeloablation 94.12%, Chi-test=0.01).

Conclusions

These data demonstrate that RRV causes expansion of HSPCs and propagates PLI. Targeting of HSPCs may be useful in preventing and treating neonatal inflammatory diseases of the liver like biliary atresia.

SYNOPSIS

Hematopoietic progenitors reside in juvenile mouse livers even after the main site of hematopoiesis has shifted to the bone marrow. These progenitors are critical for the pathogenesis of perinatal liver inflammation as myeloablation rescues animals from disease.
Direct Generation of Protein Conformational Ensembles via Machine Learning
Authors: Janson Giacomo , Valdes-Garcia Gilberto , Heo Lim , Feig Michael
Published: June 2022

Dynamics and conformational sampling are essential for linking protein structure to biological function. While challenging to probe experimentally, computer simulations are widely used to describe protein dynamics, but at significant computational costs that continue to limit the systems that can be studied. Here, we demonstrate that machine learning can be trained with simulation data to directly generate physically realistic conformational ensembles of proteins without the need for any sampling and at negligible computational cost. As a proof-of-principle a generative adversarial network based on a transformer architecture with self-attention was trained on coarse-grained simulations of intrinsically disordered peptides. The resulting model, idpGAN, can predict sequence-dependent ensembles for any sequence demonstrating that transferability can be achieved beyond the limited training data. idpGAN was also retrained on atomistic simulation data to show that the approach can be extended in principle to higher-resolution conformational ensemble generation.
aiCRISPRL: An Artificial Intelligence Platform for Stem Cell and Organoid Simulation with Extensive Gene Editing Capabilities
Authors: Danter WR
Published: June 2022

CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated nuclease 9) provides powerful gene-editing tools that are applicable for gene therapy of a variety of diseases including, but not limited to cancer, rare diseases, and heart disease. In the current study, we first re-examined our artificial stem cell and organoid simulations that were generated by our literature validated DeepNEU AI platform from the perspective of gene-editing. We then evaluated the aiCRISPRL (aiCRISPR-Like) application of the DeepNEU platform by directly comparing the CRISPR-Cas9 gene-editing approach with the DeepNEU derived aiCRISPRL capabilities using artificial simulated HeLa cells (aiHeLa). To accomplish this, we evaluated the aiCRISPRL like capabilities of DeepNEU to introduce a series of specific mutations into the MutS homolog 2 (MSH2) gene to assess DNA Mismatch Repair (MMR). This approach permits a comparative assessment of CRISPR-Cas9 and aiCRISPRL technologies following the introduction of specific MSH2 mutations. When combined with our previous body of gene editing research, the current data indicates that aiCRISPRL is an advanced AI platform technology that can be used for rapid prototyping and multiple scenario simulation in genomic research to complement wet-lab based gene-editing technologies.
A wheat chromosome segment substitution line series supports characterisation and use of progenitor genetic variation
Authors: Horsnell Richard , Leigh Fiona J , Wright Tally IC , Burridge Amanda J , Ligeza Aleksander , Przewieslik-Allen Alexandra M. , Howell Philip , Uauy Cristobal , Edwards Keith J. , Bentley Alison R
Published: June 2022

Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat chromosome segment substitution lines generated to systematically capture genetic variation from tetraploid (Triticum turgidum ssp dicoccoides) and diploid (Aegilops tauschii) progenitor species. Generated in a common genetic background over four generations of backcrossing, the material is a base resource for the mapping and characterisation of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterised using a high- density genotyping array and a range of agronomic and grain traits assessed to demonstrate the the potential use of the populations for trait localisation in wheat.
ExplorePipolin: reconstruction and annotation of bacterial mobile elements from draft genomes
Authors: Chuprikova L. , Mateo-Cáceres V. , de Toro M. , Redrejo-Rodríguez M.
Published: June 2022

Motivation

Detailed and accurate analysis of mobile genetic elements (MGEs) in bacteria is essential to deal with the current threat of multiresistant microbes. The overwhelming use of draft, contig-based genomes hinder the delineation of the genetic structure of these plastic and variable genomic stretches, as in the case of pipolins, a superfamily of MGEs that spans diverse integrative and plasmidic elements, characterized by the presence of a primer-independent DNA polymerase.

Results

ExplorePipolin is a Python-based pipeline that screens for the presence of the element and performs its reconstruction and annotation. The pipeline can be used on virtually any genome from diverse organisms and of diverse quality, obtaining the highest-scored possible structure, and reconstructed out of different contigs if necessary. Then, predicted pipolin boundaries and pipolin encoded genes are subsequently annotated using a custom database, returning the standard file formats suitable for comparative genomics of this mobile element.

Availability

All code is available and can be accessed here: github.com/pipolinlab/ExplorePipolin

Contact

modesto.redrejo@uam.es
Reduction of a heme cofactor initiates N-nitroglycine degradation by NnlA
Authors: Strickland Kara A. , Holland Ashley A. , Trudeau Alan , Szlamkowicz Ilana , Beazley Melanie J. , Anagnostopoulos Vasileios A. , Graham David E. , Caranto Jonathan D.
Published: June 2022

The NnlA enzyme from Variovorax sp. strain JS1663 degrades the linear nitramine N-nitroglycine (NNG)—a natural product produced by some bacteria—to glyoxylate and nitrite (NO2−). Ammonium (NH4+) was predicted as the third product of this reaction. A source of non-heme FeII was shown to be required for initiation of NnlA activity. However, it was unclear if this FeII was being used as a metallocofactor or a reductant. This study reveals that NnlA contains a b-type heme cofactor. Reduction of this heme is required to initiate NnlA activity. Reduction can occur either by addition of a non-heme FeII source or by reduction with dithionite. Therefore, FeII is not an essential substrate for holoenzyme activity. Data are presented showing that reduced NnlA (FeII-NnlA) can catalyze at least 100 turnovers. In addition, this catalysis occurred in the absence of O2. Finally, NH4+ was verified as the third product, accounting for the complete nitrogen mass balance. Size exclusion chromatography showed that NnlA is a dimer in solution. Additionally, FeII-NnlA is oxidized by O2 and NO2− and binds carbon monoxide (CO) and nitric oxide (NO). These are characteristics shared with PAS domains; NnlA was previously shown to exhibit homology with such domains. Providing further evidence, a structural homology model of NnlA was generated based on the structure of the PAS domain from Pseudomonas aeruginosa Aer2. The structural homology model suggested His73 is the axial ligand of the NnlA heme. Site-directed mutagenesis of His73 to alanine decreased the heme occupancy of NnlA and eliminated NNG activity, providing evidence that the homology model is valid. We conclude that NnlA forms a homodimeric heme-binding PAS domain protein that requires reduction for initiation of the activity.

Importance

Linear nitramines are potential carcinogens. These compounds result from environmental degradation of high-energy cyclic nitramines and as by-products of carbon capture technologies. Mechanistic understanding of the biodegradation of linear nitramines is critical to inform approaches for their remediation. The best understood biodegradation of a linear nitramine is NNG degradation by NnlA from Variovorax sp. strain JS 1663; however, it is unclear why non-heme iron was required to initiate enzymatic turnover. This study shows that non-heme iron is unnecessary. Instead, our study reveals that NnlA contains a heme cofactor, the reduction of which is critical for activating NNG degradation activity. These studies constrain the proposals for NnlA reaction mechanisms, thereby informing mechanistic studies of degradation of anthropogenic nitramine contaminants. In addition, these results will future work to design biocatalysts to degrade these nitramine contaminants.
Demographic history and genetic structure in pre-Hispanic Central Mexico
Authors: Villa-Islas Viridiana , Izarraras-Gomez Alan , Larena Maximilian , Campos Elizabeth Mejía Perez , Sandoval-Velasco Marcela , Rodríguez-Rodríguez Juan Esteban , Bravo-Lopez Miriam , Moguel Barbara , Fregel Rosa , Tretmanis Jazeps Medina , Velázquez-Ramírez David Alberto , Herrera-Muñóz Alberto , Sandoval Karla , Nieves-Colón Maria A. , Zepeda Gabriela , Villanea Fernando A , Medina Eugenia Fernández Villanueva , Aguayo-Haro Ramiro , Valdiosera Cristina , Ioannidis Alexander , Moreno-Estrada Andrés , Jay Flora , Huerta-Sanchez Emilia , Sánchez-Quinto Federico , Ávila-Arcos María C.
Published: June 2022

Aridoamerica and Mesoamerica are two distinct cultural areas that hosted numerous pre-Hispanic civilizations between 2,500 BCE and 1,521 CE. The division between these regions shifted southward due to severe droughts ca. 1,100 years ago, allegedly driving demographic changes and population replacement in some sites in central Mexico. Here, we present shotgun genome-wide data from 12 individuals and 26 mitochondrial genomes from eight pre-Hispanic archaeological sites across Mexico, including two at the shifting border of Aridoamerica and Mesoamerica. We find population continuity spanning the climate change episode and a broad preservation of the genetic structure across present-day Mexico for the last 2,300 years. Lastly, we identify a contribution to pre-Hispanic populations of northern and central Mexico from an ancient unsampled ‘ghost’ population.
Beyond Drift Diffusion Models: Fitting a broad class of decision and RL models with HDDM
Authors: Fengler Alexander , Bera Krishn , Pedersen Mads L. , Frank Michael J.
Published: June 2022

Computational modeling has become a central aspect of research in the cognitive neurosciences. As the field matures, it is increasingly important to move beyond standard models to quantitatively assess models with richer dynamics that may better reflect underlying cognitive and neural processes. For example, sequential sampling models (SSMs) are a general class of models of decision making intended to capture processes jointly giving rise to reaction time distributions and choice data in n-alternative choice paradigms. A number of model variations are of theoretical interest, but empirical data analysis has historically been tied to a small subset for which likelihood functions are analytically tractable. Advances in methods designed for likelihood-free inference have recently made it computationally feasible to consider a much larger spectrum of sequential sampling models. In addition, recent work has motivated the combination of SSMs with reinforcement learning (RL) models, which had historically been considered in separate literatures. Here we provide a significant addition to the widely used HDDM Python toolbox and include a tutorial for how users can easily fit and assess a (user extensible) wide variety of SSMs, and how they can be combined with RL models. The extension comes batteries included, including model visualization tools, posterior predictive checks, and ability to link trial-wise neural signals with model parameters via hierarchical Bayesian regression.
Host genetic variants regulates CCR5 expression on immune cells: a study in people living with HIV and healthy controls
Authors: dos Santos Jéssica C. , Zhang Zhenhua , van Eekeren Louise E. , Fok Ezio T. , Vadaq Nadira , van de Wijer Lisa , van der Heijden Wouter A. , Koeken Valerie A. C. M. , Koenen Hans J.P.M. , Mhlanga Musa , Netea Mihai G. , van der Ven André J. , Li Yang
Published: June 2022

C-C chemokine receptor 5 (CCR5) is the main HIV co-receptor affecting susceptibility and disease course. Quantitative trait loci (QTL) mapping analysis was performed to assess genetic variants associated with CCR5 expression on circulating immune cells in 209 PLHIV using ART and 304 healthy controls, all of Western European ancestry. The proportions of CCR5 positive cells and CCR5 mean fluorescence intensity (MFI) were assessed by flow cytometry in monocytes and CD4+ and CD8+ T cell subsets using flow cytometry. We identified the rs60939770, which is an intergenic variant in cis-region to CCR5 gene not in linkage disequilibrium with CCR5d32, related to the proportion of CCR5+ memory T regulatory cells, both in PLHIV and healthy controls. Two genome-wide significant loci, in linkage equilibrium with CCR5d32, were found to be associated with CCR5 MFI of multiple subsets of mostly differentiated memory T cells in both groups. The expression of nearby chemokines receptors (CCR1, CCR2, CCR3, CCRL2), existing in the same the same topologically associating domain, were also influenced by these genetic variants. Furthermore, we show the genetic variants which modulate CCR5 surface expression affect the production of other inflammatory mediators, including monocyte- and lymphocyte-derived cytokines as well as CCL4 and IL-8. Our data indicate that the genetic regulation of CCR5 expression is cell-specific and affects the production of various inflammatory mediators.

Author Summary

CCR5 plays a important role in the acquisition of HIV and it is associated to immune activation in people living with HIV (PLHIV). Using samples of cohorts composed of healthy individuals and PLHIV, we sought to map genomic regions that influence CCR5 expression on monocytes and subsets of CD4+ and CD8+ cells. We identified distinct genetic variants that are associated with CCR5 cell proportions or mean fluorescence intensity in subpopulations of T cells with memory functions in both healthy and PLHIV. The genetic variants also influenced the expression of other nearby chemokine receptors and the production of inflammatory mediators. Thus, we demonstrated that the genetic regulation of CCR5 expression is cell-type specific and may impact HIV susceptibility and disease progression.
In silico EsxG·EsxH Rational Epitope Selection: Candidate Epitopes for Vaccine Design against Pulmonary Tuberculosis
Authors: Martinez-Olivares Constanza Estefania , Hernández-Pando Rogelio , Mixcoha Edgar
Published: June 2022

Rational design of new vaccines against pulmonary tuberculosis is imperative. EsxG·EsxH complex is involved in metal uptake, drug resistance, and immune response evasion. These characteristics make it an ideal target for rational vaccine development. The aim of this study is to show the rational design of epitope-based peptide vaccines by using bioinformatics and structural vaccinology tools. A total of 4.15 µs of Molecular Dynamics simulations were carried out to describe the behavior in solution of heterodimer, single epitopes, and epitopes loaded into MHC-II complexes. In order to predict T and B cell epitopes for antigenic activation, bioinformatic tools were used. Hence, we propose three epitopes with the potential to design pulmonary tuberculosis vaccines. The possible use of the proposed epitopes includes subunit vaccines, as a booster in BCG vaccination to improve its immune response, as well as the generation of antibodies that interfere with the mycobacterium tuberculosis homeostasis, affecting its survival.
Pathogenic Rickettsia species evade autophagosomal maturation and reduce anti-microbicidal pro-inflammatory IL-1 responses to support their intracellular survival
Authors: Voss Oliver H. , Gaytan Hodalis , Rahman M. Sayeedur , Azad Abdu F.
Published: June 2022

Species of genus Rickettsia are obligate intracellular bacterial parasites of a wide range of arthropod and vertebrate hosts. Some Rickettsia species are responsible for several serious human diseases. One fascinating feature of these stealthy group of pathogens is their ability to exploit host cytosolic defense responses to their benefits. However, the precise mechanism by which pathogenic Rickettsia elude host immune defense responses remains to be determined. Here, we observed that pathogenic R. typhi and R. rickettsii, but not non-pathogenic R. montanensis become ubiquitinated and induce autophagy upon entry into bone-marrow-derived macrophages. Moreover, unlike R. montanensis, R. typhi, and R. rickettsii colocalized with LC3B but not with Lamp2 upon host cell entry. Finally, we observed that pathogenic but not non-pathogenic Rickettsia reduce pro-inflammatory IL-1 responses. In sum, we identified a previously unappreciated pathway by which pathogenic, but not non-pathogenic, Rickettsia become ubiquitinated and induced autophagy, but avoided autophagolysosomal destruction as well as inflammasome-mediated anti-microbicidal IL-1 cytokine responses to establish an intracytosolic niche in macrophages.
Cohort Profile: Longitudinal population-based study of COVID-19 in UK adults (COVIDENCE UK)
Authors: Holt Hayley , Relton Clare , Talaei Mohammad , Symons Jane , Davies Molly R , Jolliffe David A , Vivaldi Giulia , Tydeman Florence , Williamson Anne E , Pfeffer Paul E , Orton Christopher , Ford David V , Davies Gwyneth A , Lyons Ronan A , Griffiths Christopher J , Kee Frank , Sheikh Aziz , Breen Gerome , Shaheen Seif O , Martineau Adrian R
Published: June 2022

Background

Coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is estimated to have caused more than 18 million deaths worldwide as of end-May 2022.

Methods

COVIDENCE UK is a longitudinal population-based study that investigates risk factors for, and impacts of, COVID-19 in UK residents aged ≥16 years. A unique feature is the capacity to support trial-within-cohort studies to evaluate interventions for prevention of COVID-19 and other acute respiratory illnesses. Participants complete a detailed online baseline questionnaire capturing self-reported information relating to their socio-demographic characteristics, occupation, lifestyle, quality of life, weight, height, longstanding medical conditions, medication use, vaccination status, diet and supplemental micronutrient intake. Follow-up on-line questionnaires capturing incident symptoms of COVID-19 and other acute respiratory infections, incident swab test-confirmed COVID-19, doses of SARS-CoV-2 vaccine received, and quality of life are completed at monthly intervals.

Results

The study was launched on 1st May 2020 and closed to recruitment on 6th October 2021. A total of 19,981 participants enrolled and consented to 5-year follow-up with medical record linkage. Their mean age was 59.1 years (range 16.0 to 94.4 years), 70.2% were female, and 93.7% identified their ethnic origin as White. Analyses conducted to date have provided key insights into risk factors for SARS-CoV-2 infection and COVID-19 disease, determinants of SARS-CoV-2 vaccine immunogenicity and efficacy, and impacts of COVID-19 on health economic outcomes. The cohort has also supported conduct of a Phase 3 randomised trial-within-cohort study (CORONAVIT) evaluating implementation of a test-and-treat approach to correcting sub-optimal vitamin D status on incidence and severity of acute respiratory infections, including COVID-19.

Conclusions

The COVIDENCE UK dataset represents a valuable resource containing granular information on factors influencing susceptibility to, and impacts of, COVID-19 in UK adults. Researchers wishing to access anonymised participant-level data should contacting the corresponding author for further information.
Metformin, empagliflozin and their combination modulate ex-vivo macrophage inflammatory gene expression
Authors: Arefin Adittya , Gage Matthew C.
Published: June 2022

Type-2 Diabetes Mellitus is a complex, chronic illness characterized by persistent high blood glucose levels. Patients can be prescribed anti-diabetes drugs as single agents or in combination depending on the severity of their condition. Metformin and empagliflozin are two commonly prescribed anti-diabetes drugs which reduce hyperglycemia, however their direct effects on macrophage inflammatory responses alone or in combination are unreported. Here we show that metformin and empagliflozin elicit proinflammatory responses on mouse bone-marrow derived macrophages with single agent challenge, which are modulated when added in combination. In-silico docking experiments suggested that empagliflozin can interact with both TLR2 and DECTIN1 receptors and we observed that both empagliflozin and metformin increase expression of Tlr2 and Clec7a. Thus, findings from this study suggest that metformin and empagliflozin as single agents or in combination can directly modulate inflammatory gene expression in macrophages and upregulate the expression of their receptors.
Clock and riboswitch control of THIC in tandem are essential for appropriate gauging of TDP levels under light/dark cycles in Arabidopsis
Authors: Noordally Zeenat , Land Lara , Trichtinger Celso , Dalvit Ivan , de Meyer Mireille , Wang Kai , Fitzpatrick Teresa B.
Published: June 2022

Metabolic homeostasis is regulated by enzyme activities but the importance of regulating their corresponding coenzyme levels is unexplored. The organic coenzyme thiamine diphosphate (TDP) is supplied as needed and controlled by a riboswitch sensing mechanism in plants through the circadian regulated THIC gene. Riboswitch disruption leads to loss of time-of-day regulation of THIC expression, negatively impacting plant fitness. Pathway precursor balancing combined with enhancing the biosynthesis pathway demonstrate the importance of the riboswitch in gauging TDP levels and indicate that TDP impacts the clock in Arabidopsis. Altering the phase of THIC expression to be synchronous with TDP transporters disrupts the precision of the riboswitch suggesting that temporal separation of these processes is important. All defects are bypassed by growing plants under continuous light conditions highlighting the need to control levels of this coenzyme under diel cycles. Thus, consideration of coenzyme homeostasis within the well-studied domain of metabolic homeostasis is highlighted.
Identifying critical success factors for the General Data Protection Regulation implementation in higher education institutions
Authors: Fernandes José , Machado Carolina , Amaral Luís
Published: June 2022

Purpose

On May 25, 2018, the General Data Protection Regulation (GDPR) became mandatory for all organizations that handle the personal data of European Union citizens. This exploratory study aims to determine the critical success factors (CSFs) related to implementing the GDPR in Portuguese public higher education institutions (HEIs).

Design/methodology/approach

This study adopts a multimethod methodology with qualitative and quantitative methods. A multiple case study was carried out in Portuguese public universities. As procedures for data collecting and analysis, semistructured interviews with 26 questions were conducted with the data protection officers of these universities during May and July 2019 to derive a set of CSFs. Next, the Delphi method has been applied to determine the ranking of the CSFs. The hierarchical clusters analysis has also been applied to determine the cluster with essential CSFs. To derive the CSF, the method by Caralli et al. (2004) has been applied.

Findings

This study has identified the list of 16 CSFs related to the implementation of GDPR in HEIs, among which we can highlight, for instance, empower workers on the GDPR; commit top management with the GDPR; implement the GDPR with the involvement of management and workers; create a culture for data protection; and create a decentralized team of pivots for data protection.

Research limitations/implications

It could have been more enriching in the CSF determination process if all Portuguese public universities had participated in this study. In fact, within their many similarities, universities are also very different in approaching privacy and data protection. New studies are needed to determine whether the CSFs identified apply equally to other organizations, namely, private HEIs with less bureaucracy.

Originality/value

Identifying CSFs related to GDPR implementation in Portuguese public universities is a new area of study. This paper is a contribution to its development.
Investigating the interconnectedness among elements of face-to-face tutorials in distance education
Authors: Somuah Beatrice Asante , Segbenya Moses , Arhin Vera , Ampofo Samuel Yaw
Published: June 2022

Purpose

Face-to-face tutorial sessions remain an integral part of the delivery mode of distance education in Ghana. It is sometimes used as the sole mode of delivery of educational content in some distance education institutions. This study, therefore, investigated the interconnectedness of elements of face-to-face tutorials among distance education students.

Design/methodology/approach

The study adopted the positivist approach and used descriptive research as a design. Simple random and stratified sampling techniques were used, and a sample of 1,491 students was drawn from a population of 44,001 across all regions of Ghana. Data were collected with a self-administered questionnaire and analysed with descriptive and inferential statistics.

Findings

The study found that collaborative learning, counselling, self-directed learning, motivation and critical thinking had strong interrelationships as elements of face-to-face tutorials.

Research limitations/implications

This quantitative study was limited to the views of students on the elements of face-to-face tutorials. It was envisaged, however, that the views of the tutors and administrators who conducted the face-to-face tutorials could have enriched the findings of the study. In addition, adopting a mixed design approach where both qualitative and quantitative data were collected from the participants could have given an in-depth and enriched perspective of the current study.

Practical implications

Management of distance education institutions need to focus on these important elements and their inter-relationships as they might lead to improved academic and social progress among students. In addition, institutions must also organise orientations and seminars for course facilitators and new students on the need to develop commitments towards the elements of face-to-face tutorials as requirement so as to succeed on their course of study.

Originality/value

This is a novel approach that will help improve the understanding of students on the importance of the activities they engage in during face-to-face tutorials. It would also help managers of institutions using face-to-face tutorials to focus on these important elements that might lead to improved academic work among students.
A multi-cycle and multi-echelon location-routing problem for integrated reverse logistics
Authors: Xu Xiaofeng , Liu Wenzhi , Jiang Mingyue , Lin Ziru
Published: June 2022

Purpose

The rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.

Design/methodology/approach

First, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.

Findings

There is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.

Practical implications

This study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.

Originality/value

This research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.