bluuebunny/crossref_metadata_2025 huggingface dataset:
Social influences complement environmental cues to stimulate migrating juvenile salmon
Authors: Kururvilla Maria , Quinn Thomas P. , Anderson Joseph H. , Scheuerell Mark D. , Miller Erika M. , Berger Andrew G. , Okasaki Connie , McMillan John R. , Pess George R. , Westley Peter A.H. , Berdahl Andrew M.
Published: June 2024

Background

The large-scale seasonal migrations undertaken by many species require complex navigational and timing decisions. Animals migrating in groups might benefit from collective decision making, especially if the environment is noisy (i.e., has high degree of local variation rather than smooth gradients in, for example, salinity or temperature), unpredictable, or the migrants cannot rely on individually acquired information. We focus on juvenile salmon whose migration from fresh water to the ocean is timed to match suitable conditions for growth and survival. While the environmental and physiological factors that influence the timing of migration have been well studied, the influence of social interactions on migration timing is poorly understood.

Method

We compiled juvenile salmon data, collected at trap over 19 years, during their downstream seaward migration in three rivers in Washington state along with a suite of relevant environmental time series. We developed state space statistical models to estimate the influence of hatchery-produced salmon to stimulate the downstream migration of wild salmon, while also incorporating potential environmental stimuli.

Results

Our results are consistent with the “pied-piper” hypothesis that large numbers of migrating hatchery-origin salmon provide a social cue stimulating migration of co-occurring wild salmon. The number of hatchery salmon counted at the trap was a strong predictor of the number of wild sub-yearling Chinook salmon in the Dungeness and Puyallup rivers and on yearling coho salmon in the Puyallup and Skagit rivers. Migration timing was also influenced by a suite of physical factors related to temperature, river flow, photoperiod, and lunar phase.

Conclusions

Our findings highlight the potential for social cues to affect migration timing of downstream migrating salmon, in concert with environmental factors. Incorporating social information into timing decisions may allow animals to benefit from collective decision making strategies and better time their migrations. Moreover, understanding the effects of large-scale hatchery releases on wild salmon migration may provide valuable insights for planning the timing and duration of hatchery releases.
Chromosome-scaleSalvia hispanicaL. (Chia) genome assembly reveals rampantSalviainterspecies introgression
Authors: Brose Julia , Hamilton John P. , Schlecht Nicholas , Zhao Dongyan , Mejía-Ponce Paulina M. , Pérez Arely Cruz , Vaillancourt Brieanne , Wood Joshua C. , Edger Patrick P. , Montes-Hernandez Salvador , Orozco de Rosas Guillermo , Hamberger Björn , Jaramillo Angélica Cibrian , Buell C. Robin
Published: June 2024

Salvia hispanicaL. (Chia), a member of the Lamiaceae, is an economically important crop in Mesoamerica, with health benefits associated with its seed fatty acid composition. Chia varieties are distinguished based on seed color including mixed white and black (Chia pinta) and black (Chia negra). To facilitate research on Chia and expand on comparative analyses within the Lamiaceae, we generated a chromosome-scale assembly of a Chia pinta accession and performed comparative genome analyses with a previously published Chia negra genome assembly. The Chia pinta and negra genome sequences were highly similar as shown by a limited number of single nucleotide polymorphisms and extensive shared orthologous gene membership. There is an enrichment of terpene synthases in the Chia pinta genome relative to the Chia negra genome. We sequenced and analyzed the genomes of 20 Chia accessions with differing seed color and geographic origin revealing population structure withinS. hispanicaand interspecific introgressions ofSalviaspecies. As the genusSalviais polyphyletic, its evolutionary history remains unclear. Using large-scale synteny analysis within the Lamiaceae and orthologous group membership, we resolved the phylogeny ofSalviaspecies. This study and its collective resources further our understanding of genomic diversity in this food crop and the extent of inter-species hybridizations inSalvia.

PLAIN LANGUAGE SUMMARY

Chia pinta is an economically important crop due to the high fatty acid present in the seeds. There are multiple types of Chia based on the seeds color including mixed which and black (Chia pinta), black (Chia negra), and white (Chia blanca). We generated a genome assembly of Chia pinta and compared it to existing genome assemblies. While the assemblies are highly similar there are key differences in terpene synthase composition between Chia pinta and Chia negra. We also sequenced 20 other Chia accessions with different seed color and geographic origin to determine a population structure within Chia. We generated genomic resources to further our understanding of this food crop.

ABBREVIATIONS

BGC Biosynthetic gene cluster

BUSCO Benchmarking Universal Single Copy Orthologs GO Gene ontology

SNP Single nucleotide polymorphism TIR Terminal inverted repeat

TPS Terpene synthase

WGS Whole genome shotgun
The C-terminal regulatory domain of IPMS enzyme maintains leucine homeostasis by bypassing a hidden negative feedback loop in plants
Authors: Varghese Mohan , Kumar Roshan , Sharma Aprajita , Lone Asif , Gershenzon Jonathan , Bisht Naveen C
Published: June 2024

In the leucine biosynthesis pathway, homeostasis is achieved through a feedback regulatory mechanism facilitated by binding of the end-product Leu at the C-terminal regulatory domain of the first committed enzyme, isopropylmalate synthase (IPMS).In-vitrostudies showed that removal of the regulatory domain abolishes the feedback regulation on plant IPMS while retaining its catalytic activity. However, the physiological consequences and underlying molecular regulation upon removal of the IPMS C-terminal domain on the Leu flux have not been previously explored in plants. Here, we show that in the absence of its regulatory domain, an unexpected alternative regulatory loop acts to control plant IPMS catalysis. Removal of IPMS regulatory domain using CRISPR/Cas9 significantly reduced the formation of end-product Leuin-planta, but increased the levels of Leu pathway intermediates. Additionally, delayed growth was observed when IPMS devoid of regulatory domain was introduced intoIPMS-null mutants of E.coliandArabidopsis. Combining the metabolomic and biochemical analysis, we found that the Leu pathway intermediate, α-ketoisocaproate, was a competitive inhibitor of IPMS with a truncated regulatory domain. Thus, we demonstrate that the C-terminal regulatory domain of IPMS is biologically favored since it maintains Leu homeostasis while bypassing the possibility of competitive inhibition by a pathway intermediate.

Significance

Till date it was known that the limited profile of essential amino acid-leucine in plants, is majorly due to the feedback inhibition of its pathway enzyme, IPMS, by the binding of accumulating leucine at its regulatory domain. So, can we increase the leucine pool in plants by removing the IPMS regulatory domain? Herein we show that, the targeted removal of this domain under native condition had led to low leucine pool and compromised growth phenotype but observed an accumulation in the leucine pathway intermediates. We uncover a hidden function of the IPMS regulatory domain to avoid an intermediate inhibition on IPMS activity, which could limit the end-product. The study brings an unknown regulatory checkpoint in maintaining leucine homeostasis in plants.
CNVizard – a lightweight streamlit application for an interactive analysis of copy number variants
Authors: Krause Jeremias , Classen Carlos , Dey Daniela , Lausberg Eva , Kessler Luise , Eggermann Thomas , Kurth Ingo , Begemann Matthias , Kraft Florian
Published: June 2024

Methods to call, analyze and visualize copy number variations (CNVs) from massive parallel sequencing data have been widely adopted in clinical practice and genetic research. To enable a streamlined analysis of CNV data, comprehensive annotation and good visualization are indispensable. The ability to detect single exon CNVs is another important feature for genetic testing. Nonetheless, most available open-source tools come with limitations in at least one of these areas. One drawback is that available tools deliver data in an unstructured and static format which requires subsequent visualization and formatting efforts. Here we present CNVizard, a lightweight streamlit app which requires minimal computational knowledge, and which is compatible with widely used CNV processing tools (CNVkit and AnnotSV). CNVizard can process short- and long-read sequencing data and provides an intuitive webapp-like experience enabling an interactive visualization of CNV data.
Non-destructive viability assessment of cancer cell spheroids using dynamic optical coherence tomography with trypan blue validation
Authors: Tan Ko Hui , Ang Joel Lang Yi , Yong Alexander Si Kai , Lim Stefanie Zi En , Kng Jessica Sze Jia , Liang Kaicheng
Published: June 2024

3D cell cultures are widely used in biomedical research for the recapitulation ofin vivomicroenvironments. Viability assessment and monitoring of these intricate conformations remain an open problem as standard cell viability protocols based on colorimetry or microscopy are not directly applicable to intact 3D samples. Optical coherence tomography (OCT) has been explored extensively for subsurface structural and quasi-functional analysis of 3D cell cultures and tissue. Recent studies of dynamic OCT as a source of cellular contrast have found qualitative associations with necrosis in cell spheroids, suggesting potential as a viability marker. We present empirical and validated evidence for dynamic OCT as a quantitative indicator of cell viability in 3D cultures. We analysed over 240 MCF-7 cancer cell spheroids with dynamic OCT and corresponding viability measurements using the trypan blue exclusion assay. Significant effects of common reagents Dimethyl sulfoxide (DMSO) and Phosphate-Buffered Saline (PBS) on OCT readouts were noted. We proposed a regression-based OCT brightness normalisation technique that removed reagent-induced OCT intensity biases and helped improve correspondence to the viability assay. These results offer a quantitative biological foundation for further advances of dynamic OCT as a novel non-invasive modality for 3D culture monitoring.
GSEA and co-expression network approach to identify molecular processes affected in Porto-sinusoidal Vascular Disease
Authors: Iyer Aishwarya , Kutmon Martina , Evelo Chris T. , Doornbos Cenna , Ehrhart Friederike
Published: June 2024

Background & Aims

Porto-sinusoidal vascular disease (PSVD) is a complex rare liver disease characterized by the absence of cirrhosis with or without the presence of portal hypertension or histological lesions. Given the knowledge gaps in the mechanisms involved in this disease with unknown etiology, we used omics-based approaches to further elucidate the pathways affected in PSVD thereby facilitating an improvement in the prognosis, diagnosis, and treatment options for these patients.

Methods

For this study we used a microarray dataset (GEO:GSE77627) of 11 histologically normal liver biopsies and 18 PSVD liver biopsies. First approach, differential gene expression analysis was performed and next gene set enrichment analysis was used to identify enriched biological pathways. A network-based approach of weighted gene coexpression analysis was implemented to identify modules of interconnected genes related to the diagnosis of the patients. We further studied the pathways enriched in these modules to allow identification of processes explaining the mechanisms involved in PSVD, while the gene network could also be used to understand the connections between the processes.

Results

Gene set enrichment of differentially expressed genes indicated an increase in signaling and cell-cycle related processes and a decrease in metabolism-related processes. Coexpression network and module analysis further validated these results by elucidating connections between GPCR signaling, energy metabolism and cell-migration related processes. Furthermore, an additional connection between fibrin clot formation processes, inflammation and immune response and cell cycle and respiration processes was identified.

Conclusion

Signaling and metabolism-related processes are deregulated in PSVD patients. Furthermore, two triangular connections (GPCR signaling-energy metabolism-cell migration and fibrin-clot formation-inflammation and immune response - cell -cycle and respiration) revealed unique unknown connections involved in PSVD etiology.

Impact and implications

PSVD is a complex rare liver disease with significant knowledge gaps in the understanding of the mechanisms and pathways affected at the molecular level. In this study, we use publicly available transcriptomics data and bioinformatics tools to elucidate pathways affected in PSVD patients. In this study, we found potential novel relations between pathways with the two triangular connections (GPCR signaling-energy metabolism-cell migration and fibrin-clot formation-inflammation and immune response - cell -cycle and respiration). These newfound connections between pathways might shed light on the etiology of this disease and help researchers develop effective diagnosis and prognosis for patients suffering from PSVD.
Tumor microenvironment acidosis favors pancreatic cancer stem cell properties andin vivometastasis
Authors: Rolver Michala G. , Roda Juan C. , Dai Yifan , Flinck Mette , Ialchina Renata , Hindkær Julie , Dyhr Rigmor T. , Bodilsen August N. , Prasad Nanditha S. , Baldan Jonathan , Yao Jiayi , Sandelin Albin , Arnes Luis , Pedersen Stine F.
Published: June 2024

The acidic tumor microenvironment favors cancer aggressiveness via incompletely understood pathways. Here, we asked whether acidic environments select for cancer stem cell (CSC) properties. Bulk RNA-seq of Panc-1 human pancreatic cancer cells adapted to extracellular pH 6.5 revealed upregulation of CSC markers including CD44, EpCam, Nestin and aldehyde dehydrogenases, and CSC pathway enrichment. We therefore assessed CSC characteristics of acid-adapted (AA) and non-adapted (Ctrl) PaTu8988s and MiaPaca-2 pancreatic cancer cells. Compared to Ctrl, AA cells exhibited increased ALDH- and β-catenin activity and pancreatosphere-forming efficiency, classical CSC characteristics. Panc-1, PaTu8988s and MiaPaCa-2 AA cells differed in CSC marker expression, and AA cells did not exhibit typical flow cytometric CSC populations. However, single-nucleus sequencing identified the acid adaptation-induced emergence of a population with clear CSC characteristics. Finally, in an orthotopic mouse model, AA Panc-1 cells drove strongly increased aggressiveness and liver metastasis compared to Ctrl cells.

We conclude that acid-adaptation of pancreatic cancer cells leads to enrichment of a CSC phenotype with unusual traits, providing new insight into how acidic tumor microenvironments favor cancer aggressiveness.
Sphingomyelins in mosquito saliva modify the host lipidome to enhance transmission of flaviviruses by promoting viral protein levels
Authors: Medkour Hacène , Pruvost Lauryne , Miot Elliott , Gong Xiaoqian , Vaissayre Virginie , Boutinaud Pascal , Revel Justine , Hitakarun Atitaya , Sornjai Wannapa , Zoladek Jim , Smith R. Duncan , Nisole Sébastien , Nolte-‘t Hoen Esther , Bertrand-Michel Justine , Missé Dorothée , Marti Guillaume , Pompon Julien
Published: June 2024

Mosquito saliva plays a determining role in flavivirus transmission. Here, we discover and elucidate how salivary lipids enhance transmission. Building upon our discovery of salivary extracellular vesicles (EV), we determined that lipids within mosquito EVs, and neither within human EVs nor virions, enhance infection for flaviviruses in primary cell types relevant for transmission. Mechanistically, mosquito EV-lipids specifically promote viral protein levels by reducing ER-associated degradation. Infection enhancement is caused by sphingomyelins within mosquito salivary EVs that elevate sphingomyelin concentration within host cells. Transmission assays showed that mosquito EV-lipids exacerbate disease severity. Our study reveals that EV-associated sphingomyelins within mosquito saliva enhance transmission for multiple flaviviruses by reconfiguring the host lipidome to promote viral protein levels and the resulting skin infection. Our findings open a new dimension centered on lipids in the interplay between hosts, mosquitoes and flaviviruses that determine transmission, unveiling lipids as a new pan-flavivirus target.

Highlights

Lipids within mosquito extracellular vesicles (EVs) enhance infection in primary skin and immune cells for multiple flaviviruses.

Mosquito EV-lipids increase flaviviral protein levels by dampening ER-associated degradation.

Sphingomyelins within salivary EVs are responsible for the infection enhancement by altering host lipidome.

Co-injection of mosquito EV-lipids exacerbate disease severity.
Polyamine Depletion by D, L-alpha-difluoromethylornithine Inhibits Ewing Sarcoma Metastasis by Inducing Ferroptosis
Authors: Offenbacher Rachel , Jackson Kyle W. , Hayashi Masanori , Zhang Jinghang , Peng Da , Tan Yuqi , Stewart Tracy Murray , Ciero Paul , Foley Jackson , Casero Robert A. , Cahan Patrick , Loeb David M.
Published: June 2024

Abstract

Polyamine metabolism and signaling play important roles in multiple cancers but have not previously been studied in Ewing sarcoma. Here, we show that blocking polyamine synthesis with D, L-alpha-difluoromethylornithine (DFMO) causes a G1 cell cycle arrest, dose-dependent decreases in sarcosphere formation from Ewing sarcoma cell lines growing in non-adherent conditions and a decrease in clonogenic growth in soft agar. Further, we utilized our orthotopic implantation/amputation model of Ewing sarcoma metastasis to demonstrate that DFMO slowed primary tumor growth in addition to limiting metastasis. RNA sequencing demonstrated gene expression patterns consistent with induction of ferroptosis caused by polyamine depletion. Induction of ferroptosis was validated in vitro by demonstrating that ferrostatin-1, an inhibitor of ferroptosis, allows sphere formation even in the presence of DFMO. Collectively, these results reveal a novel mechanism by which DFMO prevents metastasis – induction of ferroptosis due to polyamine depletion. Our results provide preclinical justification to test the ability of DFMO to prevent metastatic recurrence in Ewing sarcoma patients at high risk for relapse.
A unifying model of species abundance distribution
Authors: Gao Yingnan , Abdullah Ahmed , Wu Martin
Published: June 2024

The species abundance distribution (SAD) is one of the most fundamental and best-studied macroecological patterns at the core of any biodiversity theory. Remarkably, almost every community investigated to date shows a hollow curve, indicative of the presence of many rare species and a few abundant species. While the precise nature of SAD is believed to reflect fundamental ecological processes underlying community assembly, ecologists have yet to identify a single model that comprehensively explains all SADs. Recent studies using large datasets suggested that logseries best describes animal and plant communities1,2while lognormal is the best model for microbes3, thereby challenging the notion of a unifying SAD model across the tree of life. Using a large dataset of ∼30,000 globally distributed communities spanning animals, plants and microbes from diverse environments, here we show that powerbend distribution, predicted by a maximum information entropy-based theory of ecology, emerges as a unifying model that accurately captures SADs of all life forms, habitats and abundance scales, supporting the existence of universal ecological principles. Our findings reject the notion of pure neutrality and support the idea that community assembly is driven by both random fluctuations and deterministic mechanisms, such as interspecific trait variation and resource competition. We also show that the previously estimated one trillion microbial species existing on Earth might be orders of magnitude off.
MPAC: a computational framework for inferring cancer pathway activities from multi-omic data
Authors: Liu Peng , Page David , Ahlquist Paul , Ong Irene M. , Gitter Anthony
Published: June 2024

Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cancer (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC uses network relationships encoded in pathways using a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to prioritize proteins with potential clinical relevance. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available athttps://bioconductor.org/packages/MPAC, enables similar multi-omic analyses on new datasets.
Strategies for addressing pseudoreplication in multi-patient scRNA-seq data
Authors: Malfait Milan , Gilis Jeroen , Van den Berge Koen , Assefa Alemu Takele , Verbist Bie , Clement Lieven
Published: June 2024

The rapidly evolving field of single-cell transcriptomics has provided a powerful means for understanding cellular heterogeneity. Large-scale studies with multiple biological samples hold promise for discovering differentially expressed biomarkers with a higher level of confidence through a better characterization of the target population. However, the hierarchical nature of these experiments introduces a significant challenge for downstream statistical analysis. Indeed, despite the availability of numerous differential expression methods, only a select few can accurately address the within-patient correlation of single-cell expression profiles. Furthermore, due to the high computational costs associated with some of these methods, their practical use is limited.

In this manuscript, we undertake a comprehensive assessment of different strategies to address the hierarchical correlation structure in multi-sample scRNA-seq data. We employ synthetic data generated from a simulator that retains the original correlation structure of multi-patient data while making minimal assumptions, providing a robust platform for benchmarking method performance. Our analyses indicate that neglecting within-patient correlation jeopardizes type I error control. We show that, in line with some previous reports and in contrast with others, Poisson Generalized Estimation Equations provide a useful and flexible framework for addressing these issues. We also show that pseudobulk approaches outperform single-cell level methods across the board. In this work, we resolve the conflicting results regarding the utility of GEEs and their performance relative to pseudobulk approaches. As such, we provide valuable guidelines for researchers navigating the complex landscape of gene expression modeling, and offer insights on choosing the most appropriate methods based on the specific structure and design of their datasets.
Towards Maps of Disease Progression: Biomedical Large Language Model Latent Spaces For Representing Disease Phenotypes And Pseudotime
Authors: Zamora-Resendiz Rafael , Khurram Ifrah , Crivelli Silvia
Published: June 2024

In this study, we propose a scientific framework to detect capability among biomedical large language models (LLMs) for organizing expressions of comorbid disease and temporal progression. We hypothesize that biomedical LLMs pretrained on next-token prediction produce latent spaces that implicitly capture "disease states" and disease progression, i.e., the transitions over disease states over time. We describe how foundation models may capture and transfer knowledge from explicit pretraining tasks to specific clinical applications. A scoring function based on Kullback-Leibler divergence was developed to measure "surprise" in seeing specialization when subsetting admissions along 13 biomedical LLM latent spaces. By detecting implicit ordering of longitudinal data, we aim to understand how these models self-organize clinical information and support tasks such as phenotypic classification and mortality prediction. We test our hypothesis along a case study for obstructive sleep apnea (OSA) in the publicly available MIMIC-IV dataset, finding ordering of phenotypic clusters and temporality within latent spaces. Our quantitative findings suggest that increased compute, conformance with compute-optimal training, and widening contexts promote better implicit ordering of clinical admissions by disease states, explaining 60.3% of the variance in our proposed implicit task. Preliminary qualitative findings suggest LLMs’ latent spaces trace patient trajectories through different phenotypic clusters, terminating at end-of-life phenotypes. This approach highlights the potential of biomedical LLMs in modeling disease progression, identifying new patterns in disease pathways and interventions, and evaluating clinical hypotheses related to drivers of severe illness. We underscore the need for larger, high-resolution longitudinal datasets to further validate and enhance understanding of the utility of LLMs in modeling patient trajectories along clinical text and advancing precision medicine.

Key Points

Question

Do LLMs sensibly organize cilnical data with respect to applications in precision medicine?

Findings

Biomedically-trained LLMs show increasing potential in promoting the organization of patient data to reflect disease progression. In a subcohort of OSA patients, maps derived from LLMs’ latent representations reveal traceable disease trajectories.

Meaning

Maps of disease progression offer an explanation to the utility of LLMs in precision medicine. Following current pretraining conventions in foundation modeling, scientific inquiry into these maps may help anticipate progress in applications of LLMs for healthcare.
Inhibitor of cardiolipin biosynthesis-related enzyme MoGep4 confers broad-spectrum anti-fungal activity
Authors: Sun Peng , Zhao Juan , Sha Gan , Zhou Yaru , Zhao Mengfei , Li Renjian , Kong Xiaojing , Sun Qiping , Li Yun , Li Ke , Bi Ruiqing , Yang Lei , Qin Ziting , Huang Wenzheng , Wang Yin , Gao Jie , Chen Guang , Zhang Haifeng , Adnan Muhammad , Yang Long , Zheng Lu , Chen Xiao-Lin , Wang Guanghui , Ishikawa Toshiki , Li Qiang , Xu Jin-Rong , Li Guotian
Published: June 2024

Plant pathogens cause devastating diseases, leading to serious losses to agriculture. Mechanistic understanding of pathogenesis of plant pathogens lays the foundation for the development of fungicides for disease control. Mitophagy, a specific form of autophagy, is important for fungal virulence. The role of cardiolipin, mitochondrial signature phospholipid, in mitophagy and pathogenesis is largely unknown in plant pathogenic fungi. The functions of enzymes involved in cardiolipin biosynthesis and relevant inhibitors were assessed using a set of assays, including genetic deletion, plant infection, lipidomics, chemical-protein interaction, chemical inhibition, and field trials. Our results showed that the cardiolipin biosynthesis-related geneMoGEP4of the rice blast fungusMagnaporthe oryzaeregulates growth, conidiation, cardiolipin biosynthesis, and virulence. Mechanistically, MoGep4 regulated mitophagy and Mps1-MAPK phosphorylation, which are required for virulence. Chemical alexidine dihydrochloride (AXD) inhibited the enzyme activity of MoGep4, cardiolipin biosynthesis and mitophagy. Importantly, AXD efficiently inhibited the growth of 10 plant pathogens and controlled rice blast and Fusarium head blight in the field. Our study demonstrated that MoGep4 regulates mitophagy, Mps1 phosphorylation and pathogenesis inM. oryzae. In addition, we found that the MoGep4 inhibitor, AXD, displays broad-spectrum antifungal activity and is a promising candidate for fungicide development.
CHD8 adulthood microglial knockout induces behavioral, morphological, and transcriptional changes in a sex-dependent manner
Authors: Weissberg Orly , Getselter Dmitrity , Elliott Evan
Published: June 2024

Abstract

Mutations in CHD8 (chromodomain-helicase-DNA binding protein 8) are highly associated with autism spectrum disorders. It has been well established that CHD8 has a prominent role in the development of neurons. However, there is little knowledge of its specific roles in microglia, and its possible roles in cellular functions after development, i.e. adulthood. In addition, while microglial dysfunction has been characterized in autism, the roles of autism-associated genes in microglial function have not been well characterized. Using conditional transgenic mouse models, we determined that adulthood deletion of CHD8 in microglia induces robust changes in behavior, including anxiety, social deficits, and depression-like behavior, in association with changes in microglial activation and robust microglial gene expression changes, including expression of cytokines. Of great interest, many of these changes were seen specifically in male deletion mice, and not female deletion mice. In contrast, adulthood neuron knockout had more subtle effects on behavior, mainly on depression-like behavior, and induced subtle changes in gene transcription related to the Wnt/Beta-Catenin pathway. These changes were also only present in male neuron knockout mice. In summary, CHD8 is particularly important for microglial function in adulthood and has cellular effects that are specific to males.
Ccdc66 regulates primary cilium stability, disassembly and signaling important for epithelial organization
Authors: Deretic Jovana , Cengiz-Emek Seyma , Seyrek Ece , Firat-Karalar Elif Nur
Published: June 2024

The primary cilium is a conserved, microtubule-based organelle that transduces signaling pathways essential for development and homeostasis. It is a dynamic structure that assembles and disassembles in response to intrinsic and extrinsic stimuli while maintaining remarkable stability and tightly controlled length. Although cilium assembly is well-understood, less is known about the molecular players and pathways governing their stability, length and disassembly. Here, we elucidated the function of Ccdc66, a microtubule-associated protein linked to ciliopathies, in cilium maintenance and disassembly in mouse epithelial cells. We found that Ccdc66 depletion disrupts cilium disassembly, length and stability, but does not affect assembly in these cells. Live imaging of these processes revealed that cilia in Ccdc66-depleted cells frequently fluctuate in length and exhibit increased ectocytosis from the cilium tip. Phenotypic rescue experiments andin vitromicrotubule stabilization assays showed that Ccdc66 mediates these functions via regulating the stability of microtubules. Temporal proximity mapping of CCDC66 identified potential new regulators and molecular pathways involved in cilium disassembly. Additionally, depletion of CCDC66 compromised Hedgehog and Wnt pathway activation and disrupted epithelial cell organization and polarity in two-dimensional and three-dimensional cultures. Collectively, our results define Ccdc66 as a new microtubule-stabilizing factor that regulates cilium stability and disassembly, providing insights into the mechanisms of cilium homeostasis and the pathologies associated with Ccdc66.
Mechanical Drivers of Glycosaminoglycan Content Changes in Intact and Damaged Human Cartilage
Authors: Elahi Seyed Ali , Castro-Viñuelas Rocio , Tanska Petri , Maes Lauranne , Famaey Nele , Korhonen Rami K. , Jonkers Ilse
Published: June 2024

Articular cartilage undergoes significant degeneration during osteoarthritis, currently lacking effective treatments. This study explores mechanical influences on cartilage health using a novel finite element-based mechanoregulatory model, predicting combined degenerative and regenerative responses to mechanical loading. Calibrated and validated through one-week longitudinal ex vivo experiments on intact and damaged cartilage samples, the model underscores the roles of maximum shear strain, fluid velocity, and dissipated energy in driving changes in cartilage glycosaminoglycan (GAG) content. It delineates the distinct regenerative contributions of fluid velocity and dissipated energy, alongside the degenerative contribution of maximum shear strain, to GAG adaptation in both intact and damaged cartilage under physiological mechanical loading. Remarkably, the model predicts increased GAG production even in damaged cartilage, consistent with our in vitro experimental findings. Beyond advancing our understanding of mechanical loading’s role in cartilage homeostasis, our model aligns with contemporary ambitions by exploring the potential of in silico trials to optimize mechanical loading in degenerative joint disease, fostering personalized rehabilitation.
Functional Control of Network Dynamical Systems: An Information Theoretic Approach
Authors: Singh Moirangthem Sailash , Pasumarthy Ramkrishna , Vaidya Umesh , Leonhardt Steffen
Published: June 2024

In neurological networks, the emergence of various causal interactions and information flows among nodes is governed by the structural connectivity in conjunction with the node dynamics. The information flow describes the direction and the magnitude of an excitatory neuron’s influence to the neighbouring neurons. However, the intricate relationship between network dynamics and information flows is not well understood. Here, we address this challenge by first identifying a generic mechanism that defines the evolution of various information routing patterns in response to modifications in the underlying network dynamics. Moreover, with emerging techniques in brain stimulation, designing optimal stimulation directed towards a target region with an acceptable magnitude remains an ongoing and significant challenge. In this work, we also introduce techniques for computing optimal inputs that follow a desired stimulation routing path towards the target brain region. This optimization problem can be efficiently resolved using non-linear programming tools and permits the simultaneous assignment of multiple desired patterns at different instances. We establish the algebraic and graph-theoretic conditions necessary to ensure the feasibility and stability of information routing patterns (IRPs). We illustrate the routing mechanisms and control methods for attaining desired patterns in biological oscillatory dynamics.

Author Summary

A complex network is described by collection of subsystems or nodes, often exchanging information among themselves via fixed interconnection pattern or structure of the network. This combination of nodes, interconnection structure and the information exchange enables the overall network system to function. These information exchange patterns change over time and switch patterns whenever a node or set of nodes are subject to external perturbations or stimulations. In many cases one would want to drive the system to desired information patterns, resulting in desired network system behaviour, by appropriately designing the perturbating signals. We present mathematical framework to design perturbation signals that drive the system to the desired behaviour. We demonstrate the applicability of our framework in the context of brain stimulation and in modifying causal interactions in gene regulatory networks.
Approach and rotation of reconnecting topological defect lines in liquid crystal
Authors: Zushi Yohei , Schimming Cody D. , Takeuchi Kazumasa A.
Published: June 2024

Topological defects are a universal concept across many disciplines, such as crystallography, liquid-crystalline physics, low-temperature physics, cosmology, and even biology. In nematic liquid crystals, topological defects called disclinations have been widely studied. For their three-dimensional (3D) dynamics, however, only recently have theoretical approaches dealing with fully 3D configurations been reported. Further, recent experiments have observed 3D disclination line reconnections, a phenomenon characteristic of defect line dynamics, but detailed discussions were limited to the case of approximately parallel defects. In this paper, we focus on the case of two disclination lines that approach at finite angles and lie in separate planes, a more fundamentally 3D reconnection configuration. Observing and analyzing such reconnection events, we find the square-root law of the distance between disclinations and the decrease of the interdisclination angle over time. We compare the experimental results with theory and find qualitative agreement on the scaling of distance and angle with time, but quantitative disagreement on distance and angle relative mobilities. To probe this disagreement, we derive the equations of motion for systems with reduced twist constant and also carry out simulations for this case. These, together with the experimental results, suggest that deformations of disclinations may be responsible for the disagreement.

Published by the American Physical Society
2024
Crystal structure elucidation of a geminal and vicinal bis(trifluoromethanesulfonate) ester
Authors: Pickl Thomas , Zuber Julian , Stephan Johannes , Pöthig Alexander
Published: June 2024

Geminal and vicinal bis(trifluoromethanesulfonate) esters are highly reactive alkylene synthons used as potent electrophiles in the macrocyclization of imidazoles and the transformation of bypyridines to diquat derivatives via nucleophilic substitution reactions. Herein we report the crystal structures of methylene (C3H2F6O6S2) and ethylene bis(trifluoromethanesulfonate) (C4H4F6O6S2), the first examples of a geminal and vicinal bis(trifluoromethanesulfonate) ester characterized by single-crystal X-ray diffraction (SC-XRD). With melting points slightly below ambient temperature, both reported bis(trifluoromethanesulfonate)s are air- and moisture-sensitive oils and were crystallized at 277 K to afford two-component non-merohedrally twinned crystals. The dominant interactions present in both compounds are non-classical C—H...O hydrogen bonds and intermolecular C—F...F—C interactions between trifluoromethyl groups. Molecular electrostatic potential (MEP) calculations by DFT-D3 helped to quantify the polarity between O...H and F...F contacts to rationalize the self-sorting of both bis(trifluoromethanesulfonate) esters in polar (non-fluorous) and non-polar (fluorous) domains within the crystal structure.
ChatGPT: reflections from the UK higher education institutions, accountancy bodies and BIG4s
Authors: Sales de Aguiar Thereza Raquel
Published: June 2024

Purpose

This study aims to explore ChatGPT in the context of the UK higher education (HE) and accountancy profession.

Design/methodology/approach

Narrative research that applies deductive thematic analysis to investigate secondary data produced by the UK HE governing bodies, the ancient UK universities, accountancy bodies and BIG4s.

Findings

Discussions held by the governing bodies of HE in the UK follow the advice found in the literature on how to acknowledge contributions from artificial intelligence. However, these discussions are informal. Universities provide guidance on the use of ChatGPT; however, these documents differ, compromising a consistent approach across institutions. Similarly, accountancy researchers lack uniform guidance. This is concerning because the data analysis indicates that ChatGPT’s limitations may have a detrimental impact on compliance with the UK Concordat to support research integrity. Moreover, accountancy bodies are predicting major changes in the accountancy profession due to automation, which will potentially change the job market and the content of qualification examinations. BIG4s have begun automating, with some negative impacts already evident. Thus, the field should be ready for future challenges.

Originality/value

This study explores ChatGPT in the context of the UK HE and accountancy profession. It provides a detailed analysis of the risks and opportunities associated with the use of ChatGPG, while also providing suggestions for risk mitigation to assist accountancy students, researchers and practitioners.
Does good governance moderate the relationship between blockchain technology use and tax evasion? Evidence from STOXX 600
Authors: Chouaibi Yamina , Ardhaoui Roua , Affes Wajdi
Published: June 2024

Purpose

This paper aimed to shed light on the relationship between blockchain technology intensity and tax evasion and whether this relationship is moderated by good governance.

Design/methodology/approach

Data from a sample of 50 European companies selected from the STOXX 600 index between 2010 and 2019 were used to test the model via panel data and multiple regression. Here, we used the generalized least squares method estimated on panel data. A multivariate regression model was used to analyze the moderating effect of good governance on the association between blockchain technology intensity and tax evasion. For the robustness analyses, we included the comparative study of legal systems. We performed an additional analysis by testing the dynamic dimension of the data set using the generalized method of moments to control for the endogeneity problem.

Findings

Expectedly, the results showed a negative relationship between blockchain technology intensity and tax evasion. Furthermore, the findings suggest that the moderating variable negatively affects the relationship between blockchain technology and tax evasion.

Originality/value

To our knowledge, this study supports the existing literature. Firstly, it expands the scientific debate on tax evasion. Secondly, it extends the scope of the agency theory, which is used to explain the phenomena associated with tax evasion. This study is one of the first to examine the moderating effect of good governance on the association between blockchain technology intensity and tax evasion.
Credit (mis)allocation under capital requirements: evidence from discontinuity in loan maturities
Authors: Nguyen Trang Thu , Nguyen Ha Diep , Nguyen Huyen Thi Thu
Published: June 2024

Purpose

We study how capital requirements, intended as a measure to ensure security for the financial system, can create moral hazard for banks in dealing with distressed debts.

Design/methodology/approach

Over the period spanning from 1993 to 2019, we manually gathered data on 1953 firms, identifying a total of 2,146 distress events, with 804 instances resulting in bankruptcy fillings.

Findings

Our analyses at the loan level and the bank level consistently show that loans of distressed firms are much more likely to be extended when the lenders are closer to the capital requirement limit. Exploiting the discontinuity in the predetermined maturity date of loans, we provide causal evidence on the relationship between capital ratios and extension likelihood. Distressed loans that are due just before the report date (end of a quarter) are much more likely to be extended than loans due just after the report date, after controlling for loan and firm characteristics. Additional analyses show that the effects are stronger when external financing is more costly and when the banks are poorly capitalized.

Originality/value

Our paper presents the first causal evidence of capital requirements on lending distortion, contributing to our understanding of the dynamics within the banking sector and providing policy implications for promoting financial stability and regulatory efficacy.
Exploitative training versus explorative training: the effect of strategic human capital investment on organizational performance
Authors: Song Xiaoning , Li Jiangyan , Xia Xue
Published: June 2024

Purpose

Notwithstanding its significance as a form of strategic human capital investment, employee training has not yielded consistent conclusions among scholars regarding its impact on organizational performance. Some studies deem it effective, while others regard it as ineffective. We contend that distinct types of training impact various facets of firm performance.

Design/methodology/approach

In this study, we categorize employee training as either exploitative or explorative. Specifically, we examine their impact on two aspects of organizational performance: short-term performance and long-term competence, using a quasi-experimental setting and a difference-in-differences (DID) method.

Findings

We find that exploitative training is more effective in improving firms’ short-term performance (e.g. firms’ sales revenue), while explorative training is more effective in enhancing firms’ long-term competence (e.g. firms’ innovation output).

Originality/value

The findings of this study illuminate concrete benefits of training for practitioners, suggesting that firms can strategically select employee training category to maximize returns on their investment in strategic human capital based on their strategic orientations.
The productivity dilemma: examining the truth behind automation’s impact on employment, and the mediating role of augmentation
Authors: Murphy Liam
Published: June 2024

Purpose

This paper aims to provide a comprehensive review of the literature examining the relationship between automation and employment, with a focus on understanding the debates of automation displacement and enablement, and the mediating role of employee augmentation in driving organisational productivity.

Design/methodology/approach

A semi-systematic literature review was conducted across the areas of automation, work-design and employee skills over the past 3 years.

Findings

The academic literature was found to still be in its infancy, with empirical evidence in an organisational setting scarce. However, research suggests that automation does not cause job displacement or a negative impact on employment. In contrast, data suggest that automation leads to new job creation, task enlargement and skills enhancement. The findings suggest that organisations should employ augmentation alongside automation to drive productivity, in a way that promotes strong work-design, builds trust and leverages human creativity. A further recommendation is made for organisations to focus on continuous upskilling to combat the shortening shelf-life of skills and adapt to the constant change brought around by advances in automation.

Originality/value

Through a synthesis of diverse perspectives and academic evidence, this paper contributes to the nuanced understanding of the complexities surrounding automation and its impact on employment. This literature review underscores the need for organisational strategies that leverage augmentation to harness productivity savings, alongside a renewed focus on widespread employee skills enhancement. In addition to creating new recommendations for practitioners and organisational leaders, this paper also furthers the research agenda through a list of research gaps for scholarly attention.