bluuebunny/crossref_metadata_2025 huggingface dataset:
Benchmarking Imputed Low Coverage Genomes in a Human Population Genetics Context
Authors: Purnomo Gludhug A. , Teixeira João C. , Sudoyo Herawati , Llamas Bastien , Tobler Raymond
Published: June 2024

Ongoing advances in population genomic methodologies have recently made it possible to study millions of loci across hundreds of genomes at a relatively low cost, by leveraging a combination of low-coverage shotgun sequencing and innovative genotype imputation methods. This approach has the potential to provide economical access to genotype information that is similar to most widely used low-cost genotyping approach – i.e. SNP panels – while avoiding potential issues related to loci being ascertained in distantly related populations. Nonetheless, adoption of imputation methods has been constrained by the lack of suitable reference panels of phased genomes, as performance degrades when panel individuals are distantly related to the target populations. Recent advances in imputation algorithms now allow genetic information from the target population to be used in the imputation process, however, potentially mitigating the lack of a suitable reference panel. Here we assess the performance of the recently released GLIMPSE imputation software on a set of 250 low coverage genomes (∼3x) from populations from Island Southeast Asia and Near Oceania that are poorly represented in publicly available datasets, comparing the use of imputed genotypes against other common genotype calling methods for a range of standard population genomic analyses. We find that imputation performance and inference both greatly improved when genetic information from the 250 target individuals was leveraged, with comparable results to pseudo-haploid calls that trade off improved precision with reduced accuracy. Our study shows that imputed genotypes are a cost effective and robust basis for population genomic studies of groups, especially those that are poorly represented in publicly available data.
Risk factors for atopic and non-atopic asthma in school-aged children from high-, and low-and-middle-income countries
Authors: Rutter Charlotte E , Mpairwe Harriet , Figueiredo Camila A , Njoroge Mary , Robertson Steven , Ali Hajar , Brooks Collin , Douwes Jeroen , Cooper Philip J , Chico Martha , Romero-Sandoval Natalia , Cruz Alvaro A , Tumwesige Pius , Barreto Mauricio L , Pearce Neil , Pembrey Lucy ,   the CAMERA Study Group
Published: June 2024

Background

It is well established that there are different asthma phenotypes, but whereas determinants of atopic asthma are well studied, little is known about non-atopic asthma. We compared risk factors for atopy, atopic asthma (AA) in atopics, and non-atopic asthma (NAA) in non-atopics, in children in a wide variety of countries.

Methods

Using four studies, across 23 countries, we assessed asthma status and atopy (skin prick tests) for children aged 6-17, plus risk factors from housing, heating, pets, family, diet, and air-quality categories. Using mixed effects logistic regression models we assessed 4 pathways to asthma: Pathway 1: comparing NAA with non-atopic non-asthma (risk factors for NAA); Pathway 2: comparing atopic non-asthma with non-atopic non-asthma (risk factors for atopy); Pathway 3: comparing AA with atopic non-asthma (risk factors for AA); Pathway 4: comparing AA with non-atopic non-asthma (risk factors for atopy and AA together).

Results

Our final sample of 32741 children comprised 67% with neither atopy nor asthma, 15% with atopybut without asthma, 8% with AA and 10% with NAA. Risk factors were similar for AA in atopic children and NAA in non-atopic children (Pearson’s correlation = 0.81, 95% confidence interval = [0.68, 0.94]). In contrast, risk factors for atopy in children without asthma differed from those for AA in atopic children (−0.06, [−0.29, 0.17]).

Discussion

These findings indicate that although atopy increases the risk of asthma, the risk factors for subsequently developing asthma are generally the same in those with and without atopy. This raises important questions about the role of atopy in asthma, particularly whether it is an inherent part of the aetiological process or is coincidental.

Key messages

What is already known on this topic

It is well established that there are different phenotypes of asthma but little is known about risk factors for non-atopic asthma.

What this study adds

Using a novel approach, we found that lifestyle and environmental risk factors for developing asthma are generally similar in atopic children and non-atopic children but the risk factors for atopy are quite different.

How this study might affect research, practice or policy

Our findings suggest that atopy and asthma may be coincidental in a large proportion of children who are defined as having atopic asthma. This has important implications for our understanding of the causes and mechanisms of different asthma phenotypes, and therefore prevention and treatment of asthma.
Factors influencing uptake of COVID-19 diagnostics in Sub-Saharan Africa: a rapid scoping review
Authors: Phiri Mackwellings Maganizo , Dunkley Yasmin , Di Giacomo Elizabeth , Lora Wezzie , Kumwenda Moses , Kabonga Itai , Isere Elvis , Bimba John , Sibanda Euphemia , Choko Augustine , Hatzold Karin , Corbett Liz , Desmond Nicola
Published: June 2024

Background

Diagnostics are critical for preventing COVID-19 transmission, enabling disease management and engagement with care. However, COVID-19 testing uptake remained low in low- and middle- income countries in Sub-Saharan Africa (SSA) during the recent pandemic, due to issues of supply, access and acceptability. Early studies conducted outside of the region provide insight into uptake of COVID-19 testing, however there has been no systematic research within the region. The aim of this scoping review is to investigate factors influencing uptake of COVID-19 testing in different settings across SSA.

Methods

Inclusion criteria was any study employing qualitative or mixed methodologies, addressing uptake of COVID-19 testing conducted in SSA. MEDLINE, PubMed, Google Scholar, Web of Science, and Africa-Wide Information were searched.Thematic content analysis was conducted across all included articles until saturation was attained.

Results

In total 2994 articles were identified and fourteen reviewed. Structural, social, epidemiological, informational, and political elements affected how publics interacted with COVID-19 testing. Coverage was limited by insufficient diagnostic capabilities caused by a shortage of laboratory resources and trained personnel. False information spread through social media led to testing misperceptions and apprehension. Testing hesitancy was ascribed to fear of restrictive measures and the possibility of social harms if positive. Facility-based testing was physically inaccessible and perceived as lacking privacy, whereas self-testing distributed by the community removed lengthy distances and prevented stigma. Perceptions that COVID-19 was not severe and low numbers of confirmed cases in comparison to other settings undermined public urgency for testing. Low testing frequency led to low-rate assumptions, which in turn generated denial and othering narratives. Politicians’ acceptance or denial of COVID-19 affected the mobilization of the health system, and their model actions—such as testing openly—promoted public confidence and involvement in interventions.

Conclusions

This review emphasizes the necessity of strong political commitments to enhancing health systems for future pandemic preparedness. Response plans should consider contextual elements that affect how people react to interventions and perceive health emergencies. Community-driven self-testing distribution could enhance the uptake of diagnostics through addressing socio-economic constraints impacting facility-delivered testing.
Unveiling how herpetofauna cope with land-use changes— insights from forest-cashew-rice landscapes in West Africa
Authors: dos Reis-Silva Francisco , Pizzigalli Cristian , Seck Sambu , Cabeza Mar , Rainho Ana , Rocha Ricardo , Palmeirim Ana Filipa
Published: June 2024

Agricultural-induced land-use change comprises a key driver of biodiversity loss across tropical forests. Guinea-Bissau, in West Africa, was formerly occupied by native forest-savanna mosaics. While savannas have long gave place to traditional rice agroecosystems, forests are now being transformed into cashew monocultures at unprecedented rates. The ecological impact of such rapid change is largely unknown. Here, we examined how rarefied species richness, abundance, and composition of amphibians and reptiles varied across forest remnants, cashew orchards and rice paddies in northern Guinea-Bissau. To do so, visual encounter surveys were carried across 21 sampling sites, seven in each habitat type. A total of 703 amphibian and 266 reptile encounters was recorded from nine and 14 taxa, respectively. The results show class-specific responses to habitat type. Amphibian diversity in forest remnants and cashew orchards remained similar, but rice paddies harboured higher abundance and distinct composition compared to forest remnants. Reptile abundance was highest in cashew orchards, which comprised a distinct species composition, when compared to forest remnants. Rice paddies sustained lower reptile richness and abundance. Overall, our results do not support the expected detrimental impacts of cashew expansion, which might be due to the still high heterogeneity of habitat types within the landscape. Rice paddies proved particularly important for amphibians, and for open-habitat reptiles, boosting the landscape-scale species diversity. In face of the eminent habitat conversion, maintaining heterogeneous landscapes, including the persistence of both forest remnants and rice paddies, is critical to minimize biodiversity loss in West Africa.
Structural basis of dual BACH1 regulation by SCFFBXO22and SCFFBXL17
Authors: Goretzki Benedikt , Khoshouei Maryam , Penner Patrick , Stephan Christine , Argoti Dayana , Dierlamm Nele , Rada Jimena Maria , Kapps Sandra , Thiel Zacharias , Mutlu Merve , Furkert David , Müller Catrin Swantje , Freuler Felix , Haenni Simon , Tenaillon Laurent , Knapp Britta , Hinniger Alexandra , Hoppe Philipp , Gutmann Sascha , Ryzhakov Grigory , Schmidt Enrico , Iurlaro Mario , Fernández César
Published: June 2024

BTB and CNC homolog 1 (BACH1) is a master transcriptional regulator of the cellular oxidative stress response and pro-metastatic oncogene. Post-translational stability of BACH1 is tightly regulated by distinct F-box ubiquitin ligases, including SCFFBXO22and SCFFBXL17. However, the molecular details have been elusive. Here, we reveal a structural switch in FBXO22 that controls the recognition of a three-dimensional degron in the BACH1 BTB domain, thus explaining its specificity for dimeric BACH1. We describe how cancer-associated mutations in FBXO22 modulate binding and ubiquitylation of BACH1. Further, we reveal that cancer-related mutations or cysteine-modifications destabilize the BTB domain and redirect BACH1 to FBXL17, where it is recognized as a monomer. This explains how complementary ligases post-translationally regulate BACH1 depending on the state of its BTB domain. Our findings provide mechanistic insights into the regulation of the oxidative stress response and may spur therapeutic strategies to targeting oxidative stress-related disorders and metastatic cancers.
Defective interferon signaling in the circulating monocytes of type 2 diabetic mice
Authors: Omodaka Shunsuke , Kato Yuya , Sato Yoshimichi , Falcone-Juengert Jaime , Zhang Hongxia , Kanoke Atsushi , Eckalbar Walter L. , Endo Hidenori , Hsieh Christine L. , Aran Dvir , Liu Jialing
Published: June 2024

Type 2 diabetes mellitus (T2DM) is associated with poor outcome after stroke. Peripheral monocytes play a critical role in the secondary injury and recovery of damaged brain tissue after stroke, but the underlying mechanisms are largely unclear. To investigate transcriptome changes and molecular networks across monocyte subsets in response to T2DM and stroke, we performed single-cell RNA-sequencing (scRNAseq) from peripheral blood mononuclear cells and bulk RNA-sequencing from blood monocytes from four groups of adult mice, consisting of T2DM modeldb/dband normoglycemic controldb/+mice with or without ischemic stroke. Via scRNAseq we found that T2DM expands the monocyte population at the expense of lymphocytes, which was validated by flow cytometry. Among the monocytes, T2DM also disproportionally increased the inflammatory subsets with Ly6C+ and negative MHC class II expression (MO.6C+II−). Conversely, monocytes from control mice without stroke are enriched with steady-state classical monocyte subset of MO.6C+II+ but with the least percentage of MO.6C+II− subtype. Apart from enhancing inflammation and coagulation, enrichment analysis from both scRNAseq and bulk RNAseq revealed that T2DM specifically suppressed type-1 and type-2 interferon signaling pathways crucial for antigen presentation and the induction of ischemia tolerance. Preconditioning by lipopolysaccharide conferred neuroprotection against ischemic brain injury indb/+but not indb/dbmice and coincided with a lesser induction of brain Interferon-regulatory-factor-3 in the brains of the latter mice. Our results suggest that the increased diversity and altered transcriptome in the monocytes of T2DM mice underlie the worse stroke outcome by exacerbating secondary injury and potentiating stroke-induced immunosuppression.

Significance Statement

The mechanisms involved in the detrimental diabetic effect on stroke are largely unclear. We show here, for the first time, that peripheral monocytes have disproportionally altered the subsets and changed transcriptome under diabetes and/or stroke conditions. Moreover, genes in the IFN-related signaling pathways are suppressed in the diabetic monocytes, which underscores the immunosuppression and impaired ischemic tolerance under the T2DM condition. Our data raise a possibility that malfunctioned monocytes may systemically and focally affect the host, leading to the poor outcome of diabetes in the setting of stroke. The results yield important clues to molecular mechanisms involved in the detrimental diabetic effect on stroke outcome.
Genome-wide association mapping for growth rate at fluctuating and extreme temperatures
Authors: Räsänen Emmi , Liukkonen Martta , Summanen Pauliina A. M. , Ketola Tarmo , Kronholm Ilkka
Published: June 2024

Constant temperatures and fluctuations of varying frequency affect fitness differently, which has led to suggestions of distinct genetic architectures and adaptation strategies between constant and fluctuating thermal environments. However, very little is known about the possible fitness trade-offs and genetic constraints underlying thermal adaptation and how they affect species' ability to confront climatic changes. We addressed this gap in knowledge by integrating quantitative genetics and genome-wide association mapping in the filamentous fungusNeurospora crassa. Growth rates were measured for 434 strains under fast and slow frequency fluctuations, at high and low temperature range with respect to the species' tolerance, and at constant mean and extreme temperatures of these ranges. We found strong genetic correlations between fast and slow frequency fluctuations, and between fluctuations and their mean temperatures, but not with the highest extreme temperature. Positive correlations were supported by high heritability values, pointing that inN. crassathere are no significant trade-offs or genetic constraints in adaptation when variance in temperature increases. Altogether, our results indicated clearly polygenic basis of thermal tolerance, with most of the variation in overall performance (83 %), and clearly less in hot-cold trade-off (8 %), or heat stress tolerance (4 %). Interestingly, GWAS discovered many SNPs associated with growth rate only at constant temperatures or at fast and slow fluctuations at high and low thermal range. However, the cellular functions of the associated genes were overlapping, and no opposite allelic effects were found between treatments. Hence, large-effect loci indicated no trade-offs, but a shared physiology across temperatures, probably owing to the general stress response or individual's overall fitness.
OsAAI1-OsMADS25 module orchestrates root morphogenesis by fine-tuning IAA in drought stressed rice
Authors: Xu Ning , Luo Rui , Long Qing , Man Jianmin , Yin Jiaxi , Liao Haimin , Jiang Meng
Published: June 2024

Indole-3-acetic acid (IAA) plays a critical role as a plant hormone in regulating the growth and development of the root system in plants, particularly in enhancing their ability to withstand abiotic stress. In this study, we found that overexpression ofOsAAI1promoted the growth of rice root system. The length of primary root, the number of lateral roots, the density of lateral roots, and the number of adventitious roots of overexpression ofOsAAI1(OE19) were significantly better than those of the wild type (ZH11) and the mutant line (osaai1), and the IAA content of OE19 was significantly higher than those of ZH11 andosaai1. We also found that exogenous application of IAA could compensate for the root growth defect caused by theosaai1mutation. OE19 had the highest number and widest distribution of total roots under the water-cut drought treatment, and exogenous application of IAA attenuated the growth inhibitory effect of drought stress onosaai1. Our study also revealed that OsAAI1 interacts with the MADS-box family transcription factor OsMASD25. Additionally, the application of IAA helped alleviate the growth inhibitory effects of drought stress onosmads25.Importantly, OsMADS25 interaction with OsAAI1 was found to enhance the transcriptional expression of its downstream target genesLAX1andOsBAG4, which are crucial genes in rice’s response to drought stress. These findings suggest that OsAAI1 and OsMADS25 are crucial in rice’s drought acclimation process by regulating downstream gene expression and influencing the IAA signaling pathway.

Author summary

The root system is a crucial organ for crop plants as it facilitates the absorption of water and nutrients, contributing to their drought resistance. Indole-3-acetic acid (IAA) plays a pivotal role in the growth of various types of roots in plants. Under drought stress conditions, changes in IAA levels and transport can impact the morphology of plant roots. This research illustrates that OsAAI1 positively influences rice root development and enhances the plant’s response to drought stress through the auxin signaling pathway. The study reveals a physical interaction between OsAAI1 and the transcription factor OsMADS25. This interaction boosts the expression of the auxin synthesis geneOsYUC4and suppresses the auxin inhibitory factorOsIAA14, thereby promoting the auxin signaling pathway, stimulating rice root growth, and enhancing the plant’s ability to withstand drought. Furthermore, the interaction between OsAAI1 and OsMADS25 has been found to also positively affect the expression of the genesLAX1andOsBAG4, which is associated with activated drought resistance in rice plants.
Post-flowering photoperiod sensitivity of soybean in pod-setting responses
Authors: Sun Zhihui , Yuan LiMei , Wang Yulin , Fang Ran , Lin Xiaoya , Li Haiyang , Chen Liyu , Wu Yichun , Huang Xin , Kong Fanjiang , Liu Baohui , Lu Sijia , Kong Lingping
Published: June 2024

The development of soybean (Glycine max) is regulated by photoperiod, with genes related to photoperiod sensitivity primarily focused on flowering time. However, their roles in post-flowering reproductive development and the mechanisms by which photoperiod affects them are not yet determined. In this study, we found that pod formation is sensitive to photoperiod. Long-day (LD) conditions tend to extend the time from flowering to pod formation (R1 to R3 stage), and the first wave of flowers tends to fall off. Additionally, photoperiod affects pistil morphology; under short-day (SD) conditions, the stigma has a curved hook-like structure that facilitates better interaction with the filaments when pollen is released, ultimately influencing the timing of pod formation. Photoperiod-insensitive mutants, lackingE1family andEvening Complexgenes, showed no difference in pod formation time under LD or SD conditions. Hormone content analysis and transcriptome data analysis indicated that various hormones, ROS signals, and the application of sucrose solutionin vitromight influence floral organ abscission.

Highlight

Photoperiod sensitivity after flowering affects the pod-setting time in soybean.
Direct prediction of intermolecular interactions driven by disordered regions
Authors: Ginell Garrett M. , Emenecker Ryan. J , Lotthammer Jeffrey M. , Usher Emery T. , Holehouse Alex S.
Published: June 2024

Intrinsically disordered regions (IDRs) are critical for a wide variety of cellular functions, many of which involve interactions with partner proteins. Molecular recognition is typically considered through the lens of sequence-specific binding events. However, a growing body of work has shown that IDRs often interact with partners in a manner that does not depend on the precise order of the amino acid order, instead driven by complementary chemical interactions leading to disordered bound-state complexes. Despite this emerging paradigm, we lack tools to describe, quantify, predict, and interpret these types of structurally heterogeneous interactions from the underlying amino acid sequences. Here, we repurpose the chemical physics developed originally for molecular simulations to develop an approach for predicting intermolecular interactions between IDRs and partner proteins. Our approach enables the direct prediction of phase diagrams, the identification of chemically-specific interaction hotspots on IDRs, and a route to develop and test mechanistic hypotheses regarding IDR function in the context of molecular recognition. We use our approach to examine a range of systems and questions to highlight its versatility and applicability.
HAdV-5 infection dysregulates cysteine, purine, and unsaturated fatty acid metabolism in fibroblasts
Authors: Sanchez Bailey-J C. , Ortiz Rudy M. , Grasis Juris A.
Published: June 2024

Viral infections can cause cellular dysregulation of metabolic reactions. Viruses alter host metabolism to meet their replication needs. The impact of viruses on specific metabolic pathways is not well understood, even for a well-studied virus-like human adenovirus. Adenoviral infection is known to affect cellular glycolysis and respiration, however, global effects on cellular metabolic pathways in response to adenoviral infection are lacking, particularly in normally quiescent structural cells, such as fibroblasts. Further, few studies have employed an untargeted approach with an emphasis on viral dosage and duration of infection. To address this, we employed untargeted metabolomics to quantify the dynamic metabolic shifts in fibroblasts infected with human adenovirus serotype 5 (HAdV-5) at three dosages (0.5, 1.0, and 2.0 multiplicity of infection [MOI]) and across four time points (6, 12, 24, and 36 h post-infection [HPI]). The greatest differences in individual metabolites were observed at 6– and 12-hours post-infection. In addition to its effects on glycolysis and respiration, adenoviral infection downregulated cysteine and unsaturated fatty acid metabolism, while upregulated purine metabolism. These results reveal the specific metabolic pathways that are perturbed by adenoviral infection and the associated dynamic shifts in metabolism, suggesting that viral infections alter energetics via profound changes in protein, lipid, and nucleic acid metabolism. The results revealed previously unconsidered metabolic pathways disrupted by HAdV-5 that can alter cells, even in non-excitable structural cells, such as fibroblasts.

Importance

Human adenoviruses overtake the DNA replication machinery of the infected host, rewiring mitotic events and leading to effects on cellular respiration and glycolysis. Fibroblast lineages are normally quiescent cells that display a repertoire of responses to certain agonists. While metabolism often begins with glucose breakdown in the form of aerobic glycolysis, additional pathways are important for the overall functioning of the cell. Data on shifts in the metabolism of fibroblast cells in response to human adenoviral infection are lacking. We used an untargeted metabolomic approach to better understand the dynamic metabolic changes in human kidney cells in response to three viral dosages across four time points post infection. Profound shifts were observed for the cysteine, purine, and unsaturated fatty acid metabolites. This analysis provides a global perspective and highlights previously underappreciated aspects of how human adenoviruses alter host metabolism.
Discovery of Novel Long Non-Coding RNAs with potential role in zebrafish brain regeneration
Authors: Kohli Surbhi , Abhilash Dasari , Hemlata  , Srivastava Priyanka P. , Kumar Vishantan , Minocha Shilpi , Gupta Ishaan
Published: June 2024

Understanding brain regeneration mechanisms is vital for treating neurological conditions. Zebrafish (Danio rerio) are an excellent model due to their genetic similarity to humans and strong regenerative abilities. In this study, we identified novel long non-coding RNAs (lncRNAs) in the regenerating zebrafish brain following traumatic brain injury (TBI). RNA sequencing data of the zebrafish telencephalon from the BioStudies database was analyzed for novel long non-coding RNA expression (lncRNA) at control, one day post-lesion (early wound healing), three days post-lesion (cell proliferation), and 14 days post-lesion (differentiation). We identified 689 potential lncRNAs using HISAT2, StringTie, FEELnc, and PhastCon analysis tools. Principal component analysis (PCA) of identified lncRNAs revealed a distinct expression profile at 1-day post-lesion, indicating their significant role in early wound healing.

Weighted Gene Co-expression Network Analysis (WGCNA) identified two modules (brown and turquoise) showing unique expression patterns critical to brain regeneration. Pathway enrichment analysis linked brown module lncRNAs to peptide biosynthesis, cellular amide metabolism, and ribosome biogenesis. In contrast, turquoise module lncRNAs were associated with ion transmembrane transport and cell adhesion pathways. qPCR validation confirmed co-expression patterns of selected lncRNAs and correlated genes, emphasizing their regulatory roles. This study demonstrates that lncRNAs play crucial roles in zebrafish brain regeneration by modulating gene expression during the early wound healing stage. These insights offer potential therapeutic applications of lncRNAs in neuroregenerative medicine.
Cognitive behavioral phenotyping ofDSCAMheterozygosity as a model for autism spectrum disorder
Authors: Neff Ryan C. , Stangis Katherine A. , Beniwal Ujjawal , Hergenreder Ty , Ye Bing , Murphy Geoffrey G.
Published: June 2024

It is estimated that 1 in 36 children are affected by autism spectrum disorder (ASD) in the United States, which is nearly a twofold increase from a decade ago. Recent genetic studies have identifiedde novoloss-of-function (dnLoF) mutations in theDown Syndrome Cell Adhesion Molecule (DSCAM)as a strong risk factor for ASD. Previous research has shown thatDSCAMablation confers social interaction deficits and perseverative behaviors in mouse models. However, it remains unknown to what extentDSCAMunderexpression captures the full range of behaviors, specifically cognitive phenotypes, presented in ASD. Here, we conducted a comprehensive cognitive behavioral phenotyping which revealed that loss of one copy ofDSCAM, as in theDSCAM2J+/− mice, displayed hyperactivity, increased anxiety, and motor coordination impairments. Additionally, hippocampal-dependent learning and memory was affected, including working memory, long-term memory, and contextual fear learning. Interestingly, implicit learning processes remained intact. Therefore,DSCAMLoF produces autistic-like behaviors that are similar to human cases of ASD. These findings further support a role forDSCAMdnLoF mutations in ASD and suggestDSCAM2J+/− as a suitable model for ASD research.

Summary Statement

Autism spectrum disorder represents a growing patient population. Loss of one copy of theDSCAMgene provides a promising mouse model that reproduces autistic-like behaviors for research and therapeutic testing.
Mechanism of how the universal module XMAP215 γ-TuRC nucleates microtubules
Authors: McManus Collin T. , Travis Sophie M. , Jeffrey Philip D. , Zhang Rui , Petry Sabine
Published: June 2024

It has become increasingly evident in recent years that nucleation of microtubules from a diverse set of MTOCs requires both the γ-tubulin ring complex (γ-TuRC) and the microtubule polymerase XMAP215. Despite their essentiality, little is known about how these nucleation factors interact and work together to generate microtubules. Using biochemical domain analysis of XMAP215 and structural approaches, we find that a sixth TOG domain in XMAP215 binds γ-TuRCviaγ-tubulin as part of a broader interaction involving the C-terminal region. Moreover, TOG6 is required for XMAP215 to promote nucleation from γ-TuRC to its full extent. Interestingly, we find that XMAP215 also depends strongly on TOG5 for microtubule lattice binding and nucleation. Accordingly, we report a cryo-EM structure of TOG5 bound to the microtubule lattice that reveals promotion of lateral interactions between tubulin dimers. Finally, we find that while XMAP215 constructs’ effects on nucleation are generally proportional to their effects on polymerization, formation of a direct complex with γ-TuRC allows cooperative nucleation activity. Thus, we propose that XMAP215’s C-terminal TOGs 5 and 6 play key roles in promoting nucleation by promoting formation of longitudinal and lateral bonds in γ-TuRC templated nascent microtubules at cellular MTOCs.
Integration of Biological Data via NMF for Identification of Human Disease-Associated Gene Modules through Multi-label Classification
Authors: Alberuni Syed , Ray Sumanta
Published: June 2024

Extensive evidence recognizes that proteins associated with several diseases frequently interact with each other. This leads to develop different network-based methods for uncovering the molecular workings of human diseases. These methods are based on the idea that protein interaction networks act as maps, where diseases manifest as localized perturbations within a neighborhood. Identifying these areas, known as disease modules, is essential for in-depth research into specific disease characteristics. While many computational methods have been developed the underlying connectivity patterns within these modules still yet to be explored. This work aim to fill this gap by integrating multiple biological data sources through non-negative matrix factorization (NMF) technique. We leverage two biological sources of information, protein-protein interactions (PPIs) and Gene Ontology data to find connections between novel genes and diseases. The data sources are first converted into networks, which are then clustered to obtain modules. Two types of modules are then integrated through NMF-based technique to obtain a set of meta-modules which preserve the essential characteristics of interaction patterns and functional similarity information among the proteins/genes. We assign multiple labels to each meta-module based on the statistical and biological properties they shared with the disease dataset. A multi-label classification technique is utilized to assign new disease labels to genes within each meta-modules. A total of 3131 gene-disease associations are identified, which are also validated through a literature survey, gene ontology and pathway-based analysis.
Perturbative computations of neutron-proton scattering observables using renormalization-group invariant chiral effective field theory up to
N3LO
Authors: Thim Oliver , Ekström Andreas , Forssén Christian
Published: June 2024

We predict neutron-proton scattering cross sections and polarization observables up to next-to-next-to-next-to-leading order in a renormalization-group invariant description of the strong nucleon-nucleon interaction. Low-energy constants are calibrated to phase shifts, subleading corrections are computed in distorted-wave perturbation theory, and we employ momentum-cutoff values 500 and 2500 MeV. We find a steady order-by-order convergence and realistic descriptions of scattering observables up to a laboratory scattering energy of approximately 100 MeV. We also compare perturbative and nonperturbative calculations for phase shifts and cross sections and quantify how unitarity is gradually restored at higher orders. The perturbative approach offers an important diagnostic tool for any power counting and our results suggest that the breakdown scale in chiral effective field theory might be significantly lower than estimates obtained in nonperturbative calculations.

Published by the American Physical Society
2024
Gravitational waves and tadpole resummation: Efficient and easy convergence of finite temperature QFT
Authors: Curtin David , Roy Jyotirmoy , White Graham
Published: June 2024

We demonstrate analytically and numerically that “optimized partial dressing” (OPD) thermal mass resummation, which uses gap equation solutions inserted into the tadpole, efficiently tames finite-temperature perturbation theory calculations of the effective thermal potential, without necessitating use of the high-temperature approximation. An analytical estimate of the scale dependence for OPD resummation, standard Parwani resummation (Daisy resummation), and dimensional reduction shows that OPD has similar scale dependence to dimensional reduction, greatly improving Parwani resummation. We also elucidate how to construct and solve the gap equation for realistic numerical calculations, and demonstrate OPD’s improved accuracy for a toy scalar model. OPD’s improved accuracy is most physically significant when the high-temperature approximation breaks down, rendering dimensional reduction unusable and Parwani resummation highly inaccurate, with the latter underestimating the maximal gravitational wave amplitude for the model by 2 orders of magnitude compared to OPD. Our work highlights the need to bring theoretical uncertainties under control even when analyzing broad features of a model. Given the simplicity of the OPD compared to two-loop dimensional reduction, as well as the ease with which this scheme handles departures from the high-temperature expansion, we argue this scheme has great potential in analyzing the parameter space of realistic beyond the Standard Model models.

Published by the American Physical Society
2024
Microlensing signatures of extended dark objects using machine learning
Authors: Crispim Romao Miguel , Croon Djuna
Published: June 2024

This paper presents a machine learning-based method for the detection of the unique gravitational microlensing signatures of extended dark objects, such as boson stars, axion miniclusters and subhalos. We adapt MicroLIA, a machine learning-based package tailored to handle the challenges posed by low-cadence data in microlensing surveys. Using realistic observational time stamps, our models are trained on simulated light curves to distinguish between microlensing by pointlike and extended lenses, as well as from other object classes which give a variable magnitude. We focus on boson stars and Navarro-Frenk-White (NFW) subhalos and show that the former, which are examples of objects with a relatively flat mass distribution, can be confidently identified for 0.8≲r/rE≲3. Intriguingly, we also find that more sharply peaked structures, such as NFW subhalos, can be distinctly recognized from point lenses under regular observation cadence. Our findings significantly advance the potential of microlensing data in uncovering the elusive nature of extended dark objects. The code and dataset used are also provided.

Published by the American Physical Society
2024
Gravitational waves produced by domain walls during inflation
Authors: An Haipeng , Yang Chen
Published: June 2024

We study the properties of the stochastic gravitational-wave background (SGWB) produced by domain walls (DWs) during inflation without forming a network. We numerically simulate the DW production caused by a second-order phase transition and calculate the SGWB spectrum using a 1000×1000×1000 lattice. We show that the SGWB can be observed directly by future terrestrial and space gravitational-wave detectors and through the B-mode spectrum in the cosmic microwave background. With numerical simulations, we derive an empirical formula for the strength and qualitative features of the SGWB spectrum. The details of the SGWB spectrum also contain information about the later evolution of the Universe.

Published by the American Physical Society
2024
Molecular motor in a box: Attractors, repellers, and ratchets in chromatin
Authors: Klempahn Sophie , Blossey Ralf , Schiessel Helmut
Published: June 2024

The spatiotemporal organization of eukaryotic DNA is controlled by an intricate combination of passive (thermally activated) and active (ATP-consuming) processes. Based on recent experimental insights into the mechanochemical cycle of chromatin remodelers, molecular machines that actively control nucleosome positions, we introduce a model to study the competition between active and passive mechanisms at the most basic layer of DNA packaging, the wrapping of DNA into nucleosomes. Depending on the level of remodeler activity, the positions of nucleosomes are controlled by either the bending or the stretching energy of the wrapped DNA involved. Since these energies are highly sequence dependent, DNA guides its own packaging. However, since this dependence differs for the two deformation modes, active processes can drive nucleosomes from their equilibrium positions. Furthermore, for repetitive DNA sequences, such as telomeres, we find thermal ratchets that propel nucleosomes in a preferred direction.

Published by the American Physical Society
2024
How “inspired” are customers to order from mobile food delivery apps? Soliciting the stimulus-organism-response (S-O-R) paradigm
Authors: Malik Nida , Abbasi Amir Zaib , Sohail M. Sadiq , Abbasi Ghazanfar Ali , Ting Ding Hooi
Published: May 2024

Purpose

There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise in demand for products from the gourmet industry, little is known regarding the factors that inspire customers to order from online FDAs, subsequently influencing customers’ satisfaction. Considering the knowledge gap, this study utilizes the stimulus-organism-response (S-O-R) model to conceptualize the factors: stimuli (eWOM, online reviews and online deals as external stimuli, and late-night craving and convenience as internal stimuli) that determine the organism level (i.e. customers’ inspiration) to subsequently generate the response (i.e. customers’ satisfaction).

Design/methodology/approach

We collected the data from 388 users and analyzed it via partial least squares – structural equation modeling (PLS-SEM).

Findings

The results reveal that online reviews, deals, late-night food cravings and convenience positively determine customers’ inspiration and satisfaction. In contrast, eWOM fails to impact customers’ inspiration directly and indirectly, affecting customers’ satisfaction through inspiration. Besides, customers’ inspiration positively mediates the relationship between stimuli (e.g. online reviews, online deals, late-night cravings and convenience) and customers’ satisfaction.

Originality/value

This study is novel in that it explores the impact of internal (late-night craving and convenience) and external (eWOM, online reviews and online deals) stimuli on customer inspiration and subsequently predicts customer satisfaction. We also expand prior studies on food delivery apps by studying customer inspiration as a mediating mechanism between internal and external stimuli and customer satisfaction.
Size-dependent finite element analysis of FGMs in thermal environment based on the modified couple stress theory
Authors: Wang Songhao , Qian Zhenghua , Shang Yan
Published: June 2024

Purpose

The paper aims to the size-dependent analysis of functionally graded materials in thermal environment based on the modified couple stress theory using finite element method.

Design/methodology/approach

The element formulation is developed within the framework of the penalty unsymmetric finite element method (FEM) in that the C1 continuity requirement is satisfied in weak sense and thus, C0 continuous interpolation enhanced by independent nodal rotation is employed as the test function. Meanwhile, the trial function is designed based on the stress functions and the weighted residual method. Besides, the special Gauss quadrature scheme is employed for integrals of matrices in accordance with the graded variation of the material properties.

Findings

The numerical results reveal that in thermal environment, functionally graded materials exhibit better bending performance compared to homogeneous materials, Moreover, the findings also indicate that with an increase in MLSP, the natural frequencies of out-of-plane modes gradually increase, while the natural frequencies of in-plane modes show much less variation, leading to a mode switch phenomenon.

Originality/value

The work provides an efficient numerical tool for analyzing and designing the functionally graded structures in thermal environment in practical engineering applications.
An approach based on open research knowledge graph for knowledge acquisition from scientific papers
Authors: Jiomekong Azanzi , Tiwari Sanju
Published: June 2024

Purpose

This paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.

Design/methodology/approach

Action research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.

Findings

To extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.

Originality/value

This approach is currently used to document “food information engineering,” “tabular data to knowledge graph matching” and “question answering” research problems and the “neurosymbolic AI” domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.
The relationship between conscientiousness, openness to experience, knowledge-hiding behavior and job performance of employees
Authors: Nguyễn Nam Kim , Nguyễn Nga Thị Ha˘̀ng
Published: June 2024

Purpose

Knowledge-hiding behavior can lead to adverse consequences for individuals and organizations. Therefore, the purpose of this study is to examine the relationship between personality traits, knowledge-hiding behavior and job performance in the banking sector in Vietnam.

Design/methodology/approach

This study used a quantitative approach to test the proposed research model using a linear structural modeling method. Data were collected from 291 employees working in commercial banks in Vietnam using a direct survey instrument.

Findings

The conscientiousness personality trait exhibits a negative relationship with explicit knowledge-hiding behavior but demonstrates a positive association with tacit knowledge-hiding behavior. Openness to experience is negatively correlated with both explicit and tacit knowledge-hiding behaviors. Explicit knowledge-hiding behavior is negatively related to job performance, whereas tacit knowledge-hiding behavior has a positive relationship with job performance. Knowledge-hiding behavior played an intermediary role in the relationship between conscientiousness and job performance.

Originality/value

The extent to which employees engage in knowledge hiding depends on whether the knowledge is explicit or tacit. The impact of knowledge hiding on job performance is contingent upon the nature of hidden knowledge, whether explicit or tacit, and can either diminish or enhance job performance.
AI based optimal analysis of electro-osmotic peristaltic motion of non-Newtonian fluid with chemical reaction using artificial neural networks and response surface methodology
Authors: Zeeshan Ahmed , Asghar Zaheer , Rehaman Amad ur
Published: June 2024

Purpose

The present work is devoted to investigating the sensitivity analysis of the electroosmotic peristaltic motion of non-Newtonian Casson fluid with the effect of the chemical reaction and magnetohydrodynamics through the porous medium. The main focus is on flow efficiency quantities such as pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. This initiative is to bridge the existing gap in the available literature.

Design/methodology/approach

The governing equations of the problem are mathematically formulated and subsequently simplified for sensitivity analysis under the assumptions of a long wavelength and a small Reynolds number. The simplified equations take the form of coupled nonlinear differential equations, which are solved using the built-in Matlab routine bvp4c. The response surface methodology and artificial neural networks are used to develop the empirical model for pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall.

Findings

The empirical model demonstrates an excellent fit with a coefficient of determination reaching 100% for responses, frictional forces on the upper wall and frictional forces on the lower wall and 99.99% for response, for pressure rise per wavelength. It is revealed through the sensitivity analysis that pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall are most sensitive to the permeability parameter at all levels.

Originality/value

The objective of this study is to use artificial neural networks simulation and analyze the sensitivity of electroosmotic peristaltic motion of non-Newtonian fluid with the effect of chemical reaction.
Analyst teams and the assembly bonus
Authors: Brightbill Kathryn
Published: May 2024

Purpose

Analyst team forecasts are the most frequent form of earnings expectations available to investors, with teams issuing more than 70% of research reports in 2016. Prior research provides differing evidence on whether analyst teams issue higher or lower quality forecasts than individual analysts.

Design/methodology/approach

I use a sample of more than 17,000 hand-collected analyst reports representing 7,586 forecasts from 89 companies in three industries from 1994–2005.

Findings

I document that analyst teams benefit from an assembly bonus, and issue more accurate forecasts than individual analysts only in time periods when teams would be expected to benefit from an assembly bonus.

Practical implications

I outline multiple factors within the control of brokerage houses that impact teams’ relative forecast quality, such as the number of members in the team, how long the team has worked as a unit and the costliness of integrating information when forming a forecast.

Originality/value

Given the preponderance of analyst teams and the strength of market reaction to their forecasts, it is valuable to document factors both in the past and present likely to affect analyst teams’ relative forecast accuracy.