bluuebunny/crossref_metadata_2025 huggingface dataset:
Valence and salience encoding by parallel circuits from the paraventricular thalamus to the nucleus accumbens
Authors: Rivera-Irizarry Jean K. , Hámor Peter U. , Rowson Sydney A. , Asfouri Joseph , Liu Dezhi , Zallar Lia J. , Garcia Aaron F. , Skelly Mary Jane , Pleil Kristen E.
Published: July 2023

The anterior and posterior subregions of the paraventricular thalamus (aPVT and pPVT, respectively) play unique roles in learned behaviors, from fear conditioning to alcohol/drug intake, potentially through differentially organized projections to limbic brain regions including the nucleus accumbens medial shell (mNAcSh). Here, we found that the aPVT projects broadly to the mNAcSh and that the aPVT-mNAcSh circuit encodes positive valence, such thatin vivomanipulations of the circuit modulated both innately programmed and learned behavioral responses to positively and negatively valenced stimuli, particularly in females. Further, the endogenous activity of aPVT presynaptic terminals in the mNAcSh was greater in response to positively than negatively valenced stimuli, and the probability of synaptic glutamate release from aPVT neurons in the mNAcSh was higher in females than males. In contrast, we found that the pPVT-mNAcSh circuit encodes stimulus salience regardless of valence. While pPVT-mNAcSh circuit inhibition suppressed behavioral responses in both sexes, circuit activation increased behavioral responses to stimuli only in males. Our results point to circuit-specific stimulus feature encoding by parallel PVT-mNAcSh circuits that have sex-dependent biases in organization and function.
Subcellular pathways through VG3 amacrine cells provide regionally tuned object-motion-selective signals in mouse retina
Authors: Friedrichsen Karl , Hsiang Jen-Chun , McCoy Liam , Valkova Katia , Kerschensteiner Daniel , Morgan Josh L.
Published: July 2023

We combined subcellular calcium imaging and connectomic reconstruction to understand the flow of information through a plexus of excitatory VGluT3-expressing mouse retinal amacrine cells (VG3s). We found that VG3s received inputs from all nearby bipolar cell types but exhibited a strong preference for the fast type 3a bipolar cells. We used our connectivity map and physiological recordings to predict the influence of these bipolar cells on different types of RGCs innervated by VG3s and found that the depth of retinal ganglion cell (RGC) dendritic arbor stratification determined the RGC’s view of bipolar cells through the VG3 plexus. We also found that both VG3s and their RGC targets were often innervated by the same bipolar cells. RGCs that extend processes into the middle layers of the inner plexiform layer, therefore, encounter a plexus of small object motion selective glutamatergic excitation that is complementary to the local bipolar cell input.
Genomic Diversity Illuminates the Environmental Adaptation ofDrosophila suzukii
Authors: Feng Siyuan , DeGrey Samuel P. , Guédot Christelle , Schoville Sean D. , Pool John E.
Published: July 2023

Biological invasions carry substantial practical and scientific importance, and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pestDrosophila suzukiiusing whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of theD. suzukiigenome, its diversity and its evolution, and we identify an appropriate genotype-environment association pipeline for our data set. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as a prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.
Host specificity shapes fish viromes across lakes on an isolated remote island
Authors: Grimwood Rebecca M. , Fortune-Kelly Grace , Holmes Edward C. , Ingram Travis , Geoghegan Jemma L.
Published: July 2023

Fish viromes often provide insights into the origin and evolution of viruses affecting tetrapods, including those associated with significant human diseases. However, despite fish being the most diverse vertebrate group, their viruses are still understudied. We investigated the viromes of fish on Chatham Island (Rēkohu), a geographically isolated island housing 9% of New Zealand’s threatened endemic fish species. Using metatranscriptomics, we analyzed samples from seven host species across 16 waterbodies. We identified 19 fish viruses, including 16 novel species, expanding families such as theCoronaviridae, Hantaviridae, Poxviridae, and the recently proposedTosoviridaefamily. Surprisingly, virome composition was not influenced by ecological factors measured, and smelt (Retropinna retropinna) viromes were consistent across lakes despite differences in host life history, seawater influence, and community richness. Overall, fish viromes across Rēkohu were highly diverse and revealed a long history of codivergence between host and virus despite their unique and geographically isolated ecosystem.
Reproducing Left Ventricular Twist by Mimicking Myocardial Fiber Orientation Using 3D Bioprinting-assisted Tissue Assembly
Authors: Hwang Dong Gyu , Choi Hwanyong , Yong Uijung , Kim Donghwan , Kang Wonok , Park Sung-Min , Jang Jinah
Published: July 2023

Background

Left ventricular twist, an opposite rotation of the apex and base, is caused by myocardial fiber orientation, a unique structural feature of the myocardium, and contributes to the effective ejection fraction of the native heart. Reproducing this structural-functional relationship in anin vitroheart model remains challenging due to the lack of synchrony between layers when mimicking the fiber orientations of each layer.

Methods

We employed a hierarchical approach for creating multilayered and multiaxial fibers in a chamber-like structure, as follows: 3D bioprinting-assisted tissue assembly, fabrication of uniaxially aligned engineered heart tissue as a building block, and assembly of them to create a myocardial fiber orientation in a chamber-like structure.

Result

The EHT module confirmed uniaxial alignment and cardiac functions such as contractility and electrophysiological properties. By fabricating the assembly platform by 3D bioprinting, it is possible to guide building blocks in various directions as intended, confirming the versatility of this method. The assembly platform allows structural and functional synchrony of assembled tissues while controlling and maintaining predefined cellular alignment. Furthermore, various shapes and sizes of EHT modules and assembly platform were fabricated for mimicking myocardial fiber orientation in a chamber-like structure. The resulting structure exhibited three layers and three orientations representing myocardial fiber orientation. Moreover, the left ventricular twist was confirmed by measuring basal and apical rotations.

Conclusions

Recapitulation of the microscale structure of the left ventricle enabled the identification of information not discernible from the existing macroscale structure. This understanding of the structure-function relationship of the heart can provide insights into the mechanisms underlying cardiac structure, function, and related diseases. Furthermore, the versatility of the 3D bioprinting-assisted tissue assembly allows for the creation of organs and tissue collections with complex structural and functional features by fabricating and assembling modules that meet the specific requirements of target tissues and organs.
A novelin silicoscaffold-hopping method for drug repositioning in rare and intractable diseases
Authors: Tanabe Mao , Sakate Ryuichi , Nakabayashi Jun , Tsumura Kyosuke , Ohira Shino , Iwato Kaoru , Kimura Tomonori
Published: July 2023

In the field of rare and intractable diseases, new drug development is difficult and drug repositioning (DR) is a key method to improve this situation. In this study, we present a new method for finding DR candidates utilizing virtual screening, which integrates amino acid interaction mapping into scaffold-hopping (AI-AAM). At first, we used a spleen associated tyrosine kinase (SYK) inhibitor as a reference to evaluate the technique, and succeeded in scaffold-hopping maintaining the pharmacological activity. Then we applied this method to five drugs and obtained 144 compounds with diverse structures. Among these, 31 compounds were known to target the same proteins as their reference compounds and 113 compounds were known to target different proteins. We found that AI-AAM dominantly selected functionally similar compounds; thus, these selected compounds may represent improved alternatives to their reference compounds. Moreover, the latter compounds were presumed to bind to the targets of their references as well. This new “compound-target” information provided DR candidates that could be utilized for future drug development.
Exposure to constant artificial light alters honey bee sleep rhythms and disrupts sleep
Authors: Kim Ashley Y. , Velazquez Aura , Saavedra Belen , Smarr Benjamin , Nieh James C.
Published: July 2023

Artificial light at night (ALAN) is known to create changes in animal behavior in some invertebrates and vertebrates and can result in decreased fitness. ALAN effects have not been studied in European honey bees (Apis mellifera), an important pollinator. Colonies can be exposed to ALAN in swarm clusters, when bees cluster outside the nest on hot days and evenings, and, in limited cases, when they build nests in the open. Forager bees maintained in incubated cages were subjected to constant light or dark and observed with infrared cameras. The bees maintained a regular sleep pattern for three days but showed a shift on the fourth day in the presence of continuous light. Bees under constant light demonstrated a 24.05-hour rhythm, compared to a 23.12-hour rhythm in the dark. After 95 hours, the light-exposed bees slept significantly less and experienced significantly more disturbances from their peers. They also preferred to sleep in the lower portion of the cages, which had lower light intensity. These findings suggest that ALAN can disrupt honey bees’ sleep patterns, which may have implications for their behavior and overall colony health.
Multi-omic integration of microbiome data for identifying disease-associated modules
Authors: Muller Efrat , Shiryan Itamar , Borenstein Elhanan
Published: July 2023

The human gut microbiome is a complex ecosystem with profound implications for health and disease. This recognition has led to a surge in multi-omic microbiome studies, employing various molecular assays to elucidate the microbiome’s role in diseases across multiple functional layers. However, despite the clear value of these multi-omic datasets, rigorous integrative analysis of such data poses significant challenges, hindering a comprehensive understanding of microbiome-disease interactions.

Perhaps most notably, multiple approaches, including univariate and multivariate analyses, as well as machine learning, have been applied to such data to identify disease-associated markers, namely, specific features (e.g., species, pathways, metabolites) that are significantly altered in disease state. These methods, however, often yield extensive lists of features associated with the disease without effectively capturing the multi-layered structure of multi-omic data or offering clear, interpretable hypotheses about underlying microbiome-disease mechanisms.

Here, we address this challenge by introducingMintTea –an intermediate integration-based method for analyzing multi-omic microbiome data. MintTea combines a canonical correlation analysis (CCA) extension, consensus analysis, and an evaluation protocol to robustly identify disease-associated multi-omic modules. Each such module consists of a set of features from the various omics that both shift in concord, and collectively associate with the disease.

Applying MintTea to diverse case-control cohorts with multi-omic data, we show that this framework is able to capture modules with high predictive power for disease, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome (MS) study, we found a MS-associated module comprising of a highly correlated cluster of serum glutamate- and TCA cycle-related metabolites, as well as bacterial species previously implicated in insulin resistance. In another cohort, we identified a module associated with late-stage colorectal cancer, featuringPeptostreptococcusandGemellaspecies and several fecal amino acids, in agreement with these species’ reported role in the metabolism of these amino acids and their coordinated increase in abundance during disease development. Finally, comparing modules identified in different datasets, we detected multiple significant overlaps, suggesting common interactions between microbiome features.

Combined, this work serves as a proof of concept for the potential benefits of advanced integration methods in generating integrated multi-omic hypotheses underlying microbiome-disease interactions and a promising avenue for researchers seeking systems-level insights into coherent mechanisms governing microbiome-related diseases.
An ancient split of germline and somatic stem cell lineages in Hydra
Authors: Nishimiya-Fujisawa Chiemi , Petersen Hendrik , Koubková-Yu Tracy Chih-Ting , Noda Chiyo , Shigenobu Shuji , Bageritz Josephine , Fujisawa Toshitaka , Simakov Oleg , Kobayashi Satoru , Holstein Thomas W.
Published: July 2023

In many animals, germ cell segregation occurs during early embryogenesis to protect the genome, but its origin in basal metazoans is controversial. Here, we show in the freshwater polypHydraby clonal analysis and transgenic animals that interstitial stem cells comprise two separate stem cell populations, i.e., germline and multipotent somatic stem cells. We isolated genetically labelled stem cells for a global transcriptome study and discovered a broad set of germline-specific/enriched genes includingPrdm9, Pax5, Dmrt1. In an alternative splicing analysis, we identified many genes with germline-specific isoforms; among them, male-specific isoforms ofDmrt1andSnf5. The somatic interstitial stem cell lineage was characterized by numerous neuronal control genes likeNeurog. But all stem cells inHydraalso share a core of stemness genes that has its roots in unicellular eukaryotes. This suggests an evolutionary scenario in which, at the emergence of animal multicellularity, there was an early split into a stable germline and different somatic stem cell lineages.
Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis
Authors: Akshay Akshay , Katoch Mitali , Shekarchizadeh Navid , Abedi Masoud , Sharma Ankush , Burkhard Fiona C. , Adam Rosalyn M. , Monastyrskaya Katia , Gheinani Ali Hashemi
Published: July 2023

Background

Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance.

Results

To address these challenges, we have developed a novel tool calledMachine Learning Made Easy(MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme’s feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations.

Conclusion

MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available athttps://github.com/FunctionalUrology/MLme.

Key Points

MLme is a novel tool that simplifies machine learning (ML) for researchers by integrating Data Exploration, AutoML, CustomML, and Visualization functionalities.

MLme improves efficiency and productivity by streamlining the ML workflow and eliminating the need for extensive coding efforts.

Rigorous testing on diverse datasets demonstrates MLme’s promising performance in classification problems.

MLme provides intuitive interfaces for data exploration, automated ML, customizable ML pipelines, and result visualization.

Future developments aim to expand MLme’s capabilities to include support for unsupervised learning, regression, hyperparameter tuning, and integration of user-defined algorithms.
Dynamic ventral disc contraction is necessary forGiardiaattachment and host pathology
Authors: Nosala C , Hagen KD , Guest SL , Hilton NA , Müller A , Laue M , Klotz C. , Aebischer A , Dawson SC
Published: July 2023

Giardia lambliais a common parasitic protist that infects the small intestine and causes giardiasis, resulting in diarrhea, vomiting, weight loss, and malabsorption. Giardiasis leads to cellular damage, including loss of microvilli, disruption of tight junctions, impaired barrier function, enzyme inhibition, malabsorption, and apoptosis. In the host, motileGiardiatrophozoites attach to the duodenal microvilli using a unique microtubule organelle called the ventral disc. Despite early observations of disc-shaped depressions in microvilli after parasite detachment, little is known about disc-mediated attachment mechanisms and there little direct evidence showing that parasite attachment causes cellular damage. However, advancements inin vitroorganoid models of infection and genetic tools have opened new possibilities for studying molecular mechanisms of attachment and the impact of attachment on the host. Through high-resolution live imaging and a novel disc mutant, we provide direct evidence for disc contraction during attachment, resolving the long-standing controversy of its existence. Specifically, we identify three types of disc movements that characterize contraction, which in combination result in a decrease in disc diameter and volume. Additionally, we investigate the consequences of attachment and disc contractility using an attachment mutant that has abnormal disc architecture. In a human organoid model, we demonstrate that this mutant has a limited ability to break down the epithelial barrier as compared to wild type. Based on this direct evidence, we propose a model of attachment that incorporates disc contraction to generates the forces required for the observed “grasping” of trophozoites on the host epithelium. Overall, this work highlights the importance of disc contractility in establishing and maintaining parasite attachment, leading to intestinal barrier breakdown.
A pre-trained large generative model for translating single-cell transcriptome to proteome
Authors: Liu Linjing , Li Wei , Wong Ka-Chun , Yang Fan , Yao Jianhua
Published: July 2023

Proteins are crucial for life, and measuring their abundance at the single-cell level can facilitate a high-resolution understanding of biological mechanisms in cellular processes and disease progression. However, current single-cell proteomic technologies face challenges such as limited coverage, throughput, and sensitivity, as well as batch effects, high costs, and stringent experimental operations. Drawing inspiration from the translation procedure of both natural language processing (NLP) and the genetic central dogma, we propose a pre-trained, large generative model named scTranslator (single-cell translator). scTranslator is align-free and capable of generating multi-omics data by inferring the missing single-cell proteome based on the transcriptome. Systematic benchmarking confirms the accuracy, stability, and flexibility of scTranslator across various quantification techniques, cell types, and conditions. Furthermore, scTranslator has demonstrated its superiority in assisting various downstream analyses and applications, including gene/protein interaction inference, gene pseudo-knockout, cell clustering, batch correction, and cell origin recognition on pan-cancer data.
Unconscious manipulation of conceptual representations with decoded neurofeedback impacts search behaviour
Authors: Margolles Pedro , Elosegi Patxi , Mei Ning , Soto David
Published: July 2023

The necessity of conscious awareness in human learning has been a long-standing topic in psychology and neuroscience. Previous research on non-conscious associative learning is limited by the low signal-to-noise ratio of the subliminal stimulus, and the evidence remains controversial, including failures to replicate. Using functional MRI decoded neurofeedback (fMRI-DecNef) we guided participants from both sexes to generate neural patterns akin to those observed when visually perceiving real-world entities (e.g., dogs). Importantly, participants remained unaware of the actual content represented by these patterns. We utilized an associative DecNef approach to imbue perceptual meaning (e.g., dogs) into Japanese hiragana characters that held no inherent meaning for our participants, bypassing a conscious link between the characters and the dogs concept. Despite their lack of awareness regarding the neurofeedback objective, participants successfully learned to activate the target perceptual representations in the bilateral fusiform. The behavioural significance of our training was evaluated in a visual search task. DecNef and control participants searched for dogs or scissors targets that were pre-cued by the hiragana used during DecNef training or by a control hiragana. The DecNef hiragana did not prime search for its associated target but, strikingly, participants were impaired at searching for the targeted perceptual category. Hence, conscious awareness may function to support higher-order associative learning. Meanwhile, lower-level forms of re-learning, modification, or plasticity in existing neural representations can occur unconsciously, with behavioural consequences outside the original training context. The work also provides an account of DecNef effects in terms of neural representational drift.

Significance Statement

This study examined the role of conscious awareness in human learning by using fMRI-DecNef. These techniques enabled participants to self-regulate their brain activity to align with the perceptual representations generated by a real-world entity (i.e., dogs), without awareness of the content they represented. We demonstrated that established brain conceptual representations can be unconsciously modified, influencing visual search behaviour for the targeted perceptual content through the neural representational drift mechanism. Nonetheless, our research suggests that conscious awareness plays a role in more advanced forms of associative learning. Further, this study offers methodological insights for improving DecNef protocols and suggests potential for personalized interventions, including guidance to correct maladaptive conceptual representations.
Improved protein complex prediction with AlphaFold-multimer by denoising the MSA profile
Authors: Bryant Patrick , Noé Frank
Published: July 2023

Structure prediction of protein complexes has improved significantly with AlphaFold2 and AlphaFold-multimer (AFM), but only 60% of dimers are accurately predicted. A way to improve the predictions is to inject noise to generate more diverse predictions. However, thousands of predictions are needed to obtain a few that are accurate in difficult cases. Here, we learn a bias to the MSA representation that improves the predictions by performing gradient descent through the AFM network. We effectively denoise the MSA profile, similar to how a blurry image would be sharpened. We demonstrate the performance on seven difficult targets from CASP15 and increase the average MMscore to 0.76 compared to 0.63 with AFM. We evaluate the procedure on 334 protein complexes where AFM fails and demonstrate an increased success rate (MMscore>0.75) of 8% on these hard targets. Our protocol, AFProfile, provides a way to direct predictions towards a defined target function guided by the MSA. We expect gradient descent over the MSA to be useful for different tasks, such as generating alternative conformations. AFProfile is freely available at:https://github.com/patrickbryant1/AFProfile
A Basal Ganglia Model for understanding Working Memory Functions in Healthy and Parkinson’s Conditions
Authors: C Vigneswaran , Nair Sandeep Sathyanandan , Chakravarthy V. Srinivasa
Published: July 2023

Working memory is considered as the scratchpad to write, read, and process information to perform cognitive tasks. Basal Ganglia (BG) and Prefrontal Cortex are two important parts of the brain that are involved in working memory functions and both the structures receive projections from dopaminergic nuclei. In this modelling study, we specifically focus on modelling the working memory functions of the BG, the working memory deficits in Parkinson’s disease conditions, and the impact of dopamine deficiency on different kinds of working memory functions. Though there are many experimental and modelling studies of working memory properties, there is a paucity of models of the BG that provide insights into the contributions of the BG in working memory functions. The proposed model of the BG is a unified model that can explain the working memory functions of the BG over a wide variety of tasks in normal and Parkinson’s disease conditions.
A fungal pathogen manipulates phytocytokine signaling for plant infection
Authors: Hua Chenlei , Zhang Lisha , Stintzi Annick , Schaller Andreas , Guo Hui-Shan , Nürnberger Thorsten
Published: July 2023

Phytocytokines are hormone-like plant peptides that modulate immune homeostasis and development. Phytosulfokine (PSK) mediates plant growth and attenuates activation of plant pattern-triggered immunity (PTI). We show that the small cysteine-containing effector VdSCP8 from Verticillium dahliae (Vd) is a virulence-promoting protein that suppresses PTI in Arabidopsis thaliana and Nicotiana benthamiana. Apoplastic SCP8 suppresses immune activation through leucine-rich repeat ectodomain pattern recognition receptors. SCP8 virulence and immunosuppressive activities require PHYTOSULFOKINE RECEPTOR 1 (PSKR1), which binds PSK and forms a complex with co-receptor BAK1 for PTI suppression. We find that PSK, like SCP8, suppresses PTI, SCP8 stimulates PSKR1-BAK1 complex formation, and that Vd requires PSK signaling for host infection. SCP8 interacts with an apoplastic subtilase, and co-expression of SCP8 and subtilase inhibitors reduces PTI suppression. Our findings suggest that a multi-host plant pathogen manipulates PTI by enhancing immunosuppressive PSK signaling, likely through plant subtilase activity.
Comparison of New and Old BacT/Alert Aerobic Bottles for Detection ofCandidaspp.
Authors: Choe Kye Won , Lim Yong Kwan , Lee Mi-Kyung
Published: July 2023

Purpose

A new version of aerobic blood culture media has been developed for the BacT/Alert (bioMérieux) blood culture system. We evaluated the TTD and yeast cell counts in positive blood cultures for eachCandidaspp. according to changes in media.

Methods

Isolates from defibrinated horse blood were inoculated into three types of bottles: the old version of FA Plus (Old FA Plus), New FA Plus, and FN Plus. All bottles were incubated in the BacT/Alert Virtuo blood culture system. The TTD was monitored for each bottle, and yeast cell counts were performed immediately after testing positive, determined via the plate count method. Clinical retrospective data of the candidemia samples before and after aerobic bottle change also were analyzed.

Results

The mean TTD was 51.2 hours in the Old FA Plus bottles versus 19.5 hours in the New FA Plus bottles (P< 0.001) forCandida glabrata, and standard and clinical strains showed similar results.C. albicans(27.6 to 25.1 hours) andC. guilliermondii(28.8 to 27.3 hours) had shorter TTDs. However,C. auris(25.6 to 28.1 hours) had a longer TTD in the New FA Plus bottle. The retrospective clinical analysis showed a significant decrease in TTD (45.0 to 19.4 hours) forC. glabrata, which is consistent with our simulated study.

Conclusion

This study shows that the TTD ofC. glabratawas markedly reduced in the New FA Plus bottle due to the optimized growth performance. The reduction of TTD enables faster detection and therapeutic approach forC. glabratainfections.
Non-catalytic function of PRC2 in the control of small RNA dynamics during programmed genome elimination inParamecium
Authors: Miró-Pina Caridad , Arnaiz Olivier , de Vanssay Augustin , Frapporti Andrea , Charmant Olivia , Humbert Adeline , Lhuillier-Akakpo Maoussi , Duharcourt Sandra
Published: July 2023

To limit transposable element (TE) mobilization, most eukaryotes have evolved small RNAs to silence TE activity via homology-dependent mechanisms. Small RNAs, 20-30 nucleotides in length, bind to PIWI proteins and guide them to nascent transcripts by sequence complementarity, triggering the recruitment of histone methyltransferase enzymes on chromatin to repress the transcriptional activity of TEs and other repeats. In the ciliateParamecium tetraurelia, 25-nt scnRNAs corresponding to TEs recruit Polycomb Repressive Complex 2 (PRC2), and trigger their elimination during the formation of the somatic nucleus. Here, we sequenced sRNAs during the entire sexual cycle with unprecedented precision. Our data confirmed that scnRNAs are produced from the entire germline genome, from TEs and non-TE sequences, during meiosis. Non-TE scnRNAs are selectively degraded, which results in the specific selection of TE-scnRNAs. We provide important mechanistic insight into the scnRNA selection pathway by identifying PRC2 and its cofactors as essential for the selective degradation of non-TE-scnRNAs. Our findings reveal a new mechanism for PRC2 that involves a non-methyltransferase function for regulating small RNA dynamics during development.
A digital twin for DNA data storage based on comprehensive quantification of errors and biases
Authors: Gimpel Andreas L. , Stark Wendelin J. , Heckel Reinhard , Grass Robert N.
Published: July 2023

Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modelling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twin’s ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.
On the Spatial Positioning of Ribosomes around chromosome inE. coliCytoplasm
Authors: Wasim Abdul , Bera Palash , Mondal Jagannath
Published: July 2023

The spatial organization of ribosomes in the cytoplasm of Escherichia coli (E. coli) bacteria has been a subject of longstanding intrigue. Previous investigations suggested that ribosomes remain completely excluded from the chromosome-rich nucleoid region in a “poor solvent” like cytoplasm. Here, we present an integrated model of the bacterial cytoplasm, informed by experimental data, which updates this prevailing narrative. We demonstrate that ribosomes maintain a delicate balance of both attractive and repulsive interactions with the chromosome, contrary to the conventional notion of it acting as an inert crowder in cytoplasm. The multi-dimensional spatial distribution of free ribosomes (30S and 50S) and bound ribosomes (70S polysome) inside the cytoplasm reveals that the extent of mutual ribosome-chromosome segregation is relatively less pronounced due to the presence of non-negligible amount of ribosomes within the inner core of the cytoplasm. In particular, we identify a central void within the inner-most core of the nucleoid that lacks chromosomal DNA but can accommodate finite proportion of both free (11 %) and bound (18 %) ribosomes. Furthermore, our analysis of the chromosome mesh size and the conformation of bound ribosomes suggests that bound ribosomes remain elongated and would be able to navigate past the chromosome mesh to access the central void. Together by highlighting the dynamic nature of ribosome localization in E. coli, this investigation proposes that this segregation is crucial for maximizing the utilization of synthesized mRNA and facilitating efficient translation into proteins, which are essential for bacterial survival.
Studying the motivations in choosing study tour destinations: evidence from Asian university students
Authors: Lau Yui-Yip , Xu Jing (Bill) , Mang Tsz Ching
Published: July 2023

Purpose

This study aims to explore university students' push and pull motivational factors towards their study tour destination choices and to investigate the differences between experienced and non-experienced students concerning their push and pull motivational factors.

Design/methodology/approach

The study collected surveys from Hong Kong university students. In total, 248 usable responses were gathered. Among the 248 respondents, 148 university students from various universities did not have experience on a study tour in their university lives while 100 students did. The study also conducted interviews and collected qualitative data to supplement the survey findings.

Findings

Top push and pull motivational factors were highlighted in the study tour context. This study also indicated that non-experienced students relatively have more concerns about geographic location, political stability and financial budget as pull factors and education as the push factor than experienced students. Education, as a high-level human need and push motivational factor, becomes less important for experienced students.

Originality/value

A large number of Asian university students participated in study tour programmes each year. Nevertheless, there are few research papers relevant to exploring university students’ motivation to choose study tour destinations. This study provides useful insight for the universities to design and implement appropriate study tours according to students’ motivation.
Performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task
Authors: Xing Yuping , Zhan Yongzhao
Published: July 2023

Purpose

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

Design/methodology/approach

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

Findings

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

Originality/value

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.
Determinants of user satisfaction with financial information systems in the digital transformation era: insights from emerging markets
Authors: Al-Okaily Manaf , Al-Kofahi Mahmoud , Shiyyab Fadi Shehab , Al-Okaily Aws
Published: July 2023

Purpose

Most of the previous studies agree about the significance of user satisfaction in ensuring the endurance of information systems (ISs). Accordingly, it is crucial to investigate the effect of e-Government systems on individual end-user satisfaction as more and more countries adopt and deploy such Government Financial Management Information Systems (GFMIS) in the era of digital transformation. Because of this, the purpose of this study is to investigate the factors that contribute to the success of GFMIS in Jordan and ultimately the satisfaction of its users.

Design/methodology/approach

The IS success model developed by DeLone and McLean (2003) serves as the theoretical underpinning for the current research. Adding training quality as a new variable to the proposed model has been found to further increase the satisfaction of GFMIS users. A total of 104 GFMIS users in Jordan provided the data used to verify the model. The partial least squares-structural equation modelling was used to test the hypotheses.

Findings

The empirical findings indicated that GFMIS user satisfaction is significantly affected by information quality, service quality and perceived usefulness; meanwhile, system quality is only partially supported. The research also showed that the level of satisfaction among Jordanian GFMIS users was related to the quality of training they received.

Originality/value

This study fills a crucial literature gap by developing a research model that can help improve GFMIS usage towards attaining greater performance amongst government agencies in Jordan.
Experts’ feedback on the cybersecurity footprint elements: in pursuit of a quantifiable measure of SMBs’ cybersecurity posture
Authors: Gafni Ruti , Levy Yair
Published: July 2023

Purpose

While data breaches are reported daily, organizations are struggling with quantifying their cybersecurity posture. This paper aims to introduce the Universal Cybersecurity Footprint Index (UCFI), an organizational measure of Cybersecurity Footprint. The UCFI helps organizations understand the challenges related to their overall cybersecurity posture and be able to assess it for their supply chain cybersecurity. The Theory of Cybersecurity Footprint states that the risk and damage that can be caused by an attacked organization are not related to the size of the organization but to a range of parameters that may affect the interconnected entities in their supply chain.

Design/methodology/approach

Based on the 26 elements found in prior research, a survey was conducted, using 27 subject matter experts to reveal the most relevant elements and then specify their importance level to calculate their relative weight.

Findings

Results indicated that 20 of the 26 elements were validated, and their weights were calculated. Finally, an equation representing the UCFI for an organization is introduced.

Practical implications

Organizations can choose their partners according to a minimum value of the UCFI to reduce their cybersecurity risks.

Social implications

Supply chain cybersecurity incidents have demonstrated in the past several years to provide a massive impact on society. Thus, further assisting in mitigation of cyberattacks to the supply chain is significant.

Originality/value

This research aims to provide further assistance for organizations in quantifying their cybersecurity footprint in effort to help reduce cyber incidents, especially those for small organizations.
Do professional shareholders matter for corporate compliance with IFRS reporting requirements: the moderating effect of board independence
Authors: Zaid Mohammad A.A.
Published: July 2023

Purpose

From an agency theory realm, this study aims to respond to the more recent calls to deeply analyze the indirect influence of professional shareholders, namely, institutional, blockholder and foreign owners, on the extent of compliance with International Financial Reporting Standards (IFRS) mandatory reporting requirements.

Design/methodology/approach

Multivariate regression analysis was applied. Moreover, quantitative static and dynamic panel data have been used. More plainly, ordinary least squares was run as a baseline estimator. Afterwards, one-step system generalized method of moment and two-stage least squares were conducted to control for the potential endogeneity dilemma. The analysis is based on a sample of nonfinancial listed firms on the Palestine Stock Exchange for the time span of 10 years, from 2010 to 2019.

Findings

After controlling for the detrimental effect of the endogeneity issue, the findings clearly reveal that the effect of the three types of professional shareholders (institutional, blockholder and foreign) on the extent of compliance with IFRS is more significant under a high proportion of independent nonexecutive directors.

Originality/value

To the best of the author’s knowledge, prior literature on the nexus between shareholding structure and compliance level with IFRS has restricted solely to analyzing the direct influence without casting the light on the moderation effect of independent nonexecutive directors. Hence, analyzing this sensitive configuration merits attention. In this vein, to ameliorate the compliance level with IFRS, regulators have to devote remarkable effort to updating both enforcement mechanisms and best practices of shareholding structure simultaneously.
The dark side of FinTech in financial services: a qualitative enquiry into FinTech developers’ perspective
Authors: Sampat Brinda , Mogaji Emmanuel , Nguyen Nguyen Phong
Published: July 2023

Purpose

FinTech offers numerous prospects for significant enhancements and fundamental changes in financial services. However, along with the myriad of benefits, it also has the potential to induce risks to individuals, organisations and society. This study focuses on understanding FinTech developers’ perspective of the dark side of FinTech.

Design/methodology/approach

This study conducted semi-structured interviews with 23 Nigerian FinTech developers using an exploratory, inductive methodology The data were transcribed and then thematically analysed using NVivo.

Findings

Three themes – customer vulnerability, technical inability and regulatory irresponsibility – arose from the thematic analysis. The poor existing technological infrastructure, data management challenges, limited access to data and smartphone adoption pose challenges to a speedy integration of FinTech in the country, making customers vulnerable. The lack of privacy control leads to ethical issues. The lack of skilled developers and the brain drain of good developers present additional obstacles to the development of FinTech in Nigeria.

Research limitations/implications

FinTech operation in a developing country differs from that in developed countries with better technological infrastructure and institutional acceptance. This study recognises that basic banking operations through FinTech are still not well adopted, necessitating the need to be more open-minded about the global practicalities of FinTech.

Practical implications

FinTech managers, banks and policymakers can ethically collect consumer data that can help influence customer credit decisions, product development and recommendations using the mobile app and transaction history. There should be strict penalties on FinTech for selling customers’ data, sending unsolicited messages or gaining unnecessary access to the customer’s contact list. FinTech can offer to educate consumers about their financial management skills.

Originality/value

Whereas other studies have focused on the positive aspects of FinTech to understand client perceptions, this study offers new insights into the dark side of FinTech by analysing the viewpoints of FinTech developers. Furthermore, the study is based in Nigeria, an emerging economy adopting FinTech, adding a new dimension to the body of knowledge.
Resilient leadership in hospitality and tourism enterprises: conceptualization and scale development
Authors: Zhang Jiangchi , Xie Chaowu , Huang Songshan (Sam)
Published: July 2023

Purpose

This study aims to conceptualize the dimensions of resilient leadership and develop the resilient leadership scale (RLS) through three studies.

Design/methodology/approach

In Study 1, based on interviews with 77 leaders and 8 junior employees, a seven-factor resilient leadership model was constructed. In Study 2, exploratory factor analysis (n= 237) was conducted to refine the initial items. In Study 3, confirmatory factor analysis (n= 610) was performed to validate the dimensional structure identified in Study 2, and different types of validity of the RLS were assessed.

Findings

The validated RLS composed of seven dimensions: contingency planning, improvisation, adaptive instructing, contingency control, emergency care, adjustment recovery and mutual growth. The scale showed desirable measurement qualities in terms of reliability and validity. Resilient leadership and its dimensions significantly impact employee turnover intentions and employee resilience.

Research limitations/implications

This research contributes to the literature on the resilience of hospitality and tourism enterprises and enriches the research scope and theoretical framework of resilient leadership.

Originality/value

This research revealed the resilient leadership responses to crisis in hospitality and tourism enterprises with practical implications for tourism enterprise leaders to deal with major crisis.