bluuebunny/crossref_metadata_2025 huggingface dataset:
H3.3 deposition counteracts the replication-dependent enrichment of H3.1 at chromocenters in embryonic stem cells
Authors: Arfè S. , Karagyozova T. , Forest A. , Hmidan H. , Meshorer E. , Quivy J.-P. , Almouzni G.
Published: July 2024

Chromocenters in mouse cells are membrane-less nuclear compartments that represent typical heterochromatin stably maintained during the cell cycle. Here, we explore how histone H3 variants, replicative H3.1/H3.2 or replacement H3.3, mark these domains during the cell cycle. In mouse embryonic stem cells (ESCs), neuronal precursor cells (NPCs) as well as immortalized 3T3 cells, we find a strong and distinct H3.1 enrichment at chromocenters, with some variation in ESCs. Mechanistically, this H3.1 selective enrichment depends on the DNA Synthesis Coupled (DSC) deposition pathway operating in S phase. Yet, this selective enrichment is challenged when we target H3.3 deposition through the DNA Synthesis Independent (DSI) deposition pathway mediated by HIRA. Altering the H3.1/H3.3 equilibrium at chromocenters in ESCs affects its heterochromatin properties leading to mitotic defects. We thus reveal opposing mechanisms for H3.1 and H3.3 deposition with different enforcement according to cell cycle and potency which determine their ratio at chromocenters and are critical for genome stability and cell survival.
Food texture preference reveals multisensory contributions of gustatory organs in behaviour and physiology
Authors: Komarov Nikita , Fritsch Cornelia , Maier G. Larisa , Bues Johannes , Biočanin Marjan , Avalos Clarisse Brunet , Dodero Andrea , Kwon Jae Young , Deplancke Bart , Sprecher Simon G.
Published: July 2024

Food presents a multisensory experience, with visual, taste, and olfactory cues being important in allowing an animal to determine the safety and nutritional value of a given substance1. Texture, however, remains a surprisingly unexplored aspect, despite providing key information about the state of the food through properties such as hardness, liquidity, and granularity. Food perception is achieved by specialised sensory neurons, which themselves are defined by the receptor genes they express. While it was assumed that sensory neurons respond to one or few closely-related stimuli, more recent findings challenge this notion and support evidence that certain sensory neurons are more broadly tuned. In theDrosophilataste system, gustatory neurons respond to cues of opposing hedonic valence or to olfactory cues. Here, we identified that larvae ingest and navigate towards specific food substrate hardnesses, and probed the role of gustatory organs in this behaviour. By developing a genetic tool targeting specifically gustatory organs, we show that these organs are major contributors for evaluation of food texture and ingestion decision-making. We find that ablation of gustatory organs not only results in loss of chemosensation, but also navigation and ingestion preference to varied substrate textures. Furthermore, we show that certain neurons in the primary taste organ exhibit varied and concurrent physiological responses to mechanical and multimodal stimulation. We show that individual neurons house independent mechanisms for multiple sensory modalities, challenging assumptions about capabilities of sensory neurons. We propose that further investigations, across the animal kingdom, may reveal higher sensory complexity than currently anticipated.
Gene regulatory network structure informs the distribution of perturbation effects
Authors: Aguirre Matthew , Spence Jeffrey P. , Sella Guy , Pritchard Jonathan K.
Published: July 2024

Gene regulatory networks (GRNs) govern many core developmental and biological processes underlying human complex traits. Even with broad-scale efforts to characterize the effects of molecular perturbations and interpret gene coexpression, it remains challenging to infer the architecture of gene regulation in a precise and efficient manner. Key properties of GRNs, like hierarchical structure, modular organization, and sparsity, provide both challenges and opportunities for this objective. Here, we seek to better understand properties of GRNs using a new approach to simulate their structure and model their function. We produce realistic network structures with a novel generating algorithm based on insights from small-world network theory, and we model gene expression regulation using stochastic differential equations formulated to accommodate modeling molecular perturbations. With these tools, we systematically describe the effects of gene knockouts within and across GRNs, finding a subset of networks that recapitulate features of a recent genome-scale perturbation study. With deeper analysis of these exemplar networks, we consider future avenues to map the architecture of gene expression regulation using data from cells in perturbed and unperturbed states, finding that while perturbation data are critical to discover specific regulatory interactions, data from unperturbed cells may be sufficient to reveal regulatory programs.
Stochastic Modeling of Biophysical Responses to Perturbation
Authors: Chari Tara , Gorin Gennady , Pachter Lior
Published: July 2024

Recent advances in high-throughput, multi-condition experiments allow for genome-wide investigation of how perturbations affect transcription and translation in the cell across multiple biological entities or modalities, from chromatin and mRNA information to protein production and spatial morphology. This presents an unprecedented opportunity to unravel how the processes of DNA and RNA regulation direct cell fate determination and disease response. Most methods designed for analyzing large-scale perturbation data focus on the observational outcomes, e.g., expression; however, many potential transcriptional mechanisms, such as transcriptional bursting or splicing dynamics, can underlie these complex and noisy observations. In this analysis, we demonstrate how a stochastic biophysical modeling approach to interpreting high-throughout perturbation data enables deeper investigation of the ‘how’ behind such molecular measurements. Our approach takes advantage of modalities already present in data produced with current technologies, such as nascent and mature mRNA measurements, to illuminate transcriptional dynamics induced by perturbation, predict kinetic behaviors in new perturbation settings, and uncover novel populations of cells with distinct kinetic responses to perturbation.
Generative deep learning models for cognitive performance trajectories in real-world scenarios
Authors: Expósito Denis , Maltseva Elina , Sastre-Barrios Carolina , de Piérola Iñigo Fernández , Cortes Jesus M.
Published: July 2024

The increasing prevalence of cognitive disorders, such as Alzheimer’s disease, imposes significant challenges on healthcare systems and society. The ability to predict the future cognitive performance (CP) is crucial for professionals in neuropsychology, and real-world data emerges as an important source of complete and reliable information. However, its inherent complexities requires the use of advanced models to make predictions. To do so, we have implemented and compared three deep learning predictive strategies from CP trajectories: multilayer perceptron (MLP), convolutional neural networks (CNN) and long short-term memory (LSTM). The three models showed robustness on their predictions in different patient datasets. The CNN was the most suitable architecture due to its local pattern recognition capabilities and its robustness to overfitting. Therefore, professionals can have a complementary support for targeting treatment approaches to patients needs and anticipate undesired outcomes (e.g. cognitive impairment). Nonetheless, further studies are needed to validate whether neuropsychological interventions based on score predictions lead to improved intervention efficacy compared to traditional approaches for controlled patient groups.
Estimating gene conversion tract length and rate from PacBio HiFi data
Authors: Charmouh Anders Poulsen , Sørud Peter Porsborg , Hansen Lasse Thorup , Besenbacher Søren , Winge Sofia Boeg , Almstrup Kristian , Hobolth Asger , Bataillon Thomas , Schierup Mikkel Heide
Published: July 2024

Gene conversions are broadly defined as the transfer of genetic material from a ‘donor’ to an ‘acceptor’ sequence and can happen both in meiosis and mitosis. They are a subset of non-crossover events and, like crossover events, gene conversion can generate new combinations of alleles and counteract mutation load by reverting germline mutations through GC-biased gene conversion. Estimating gene conversion rate and the distribution of gene conversion tract lengths remains challenging. We present a new method for estimating tract length, rate and detection probability of non-crossover events directly in HiFi PacBio long read data. The method can be used to make inference from sequencing of gametes from a single individual. The method is unbiased even under low single nucleotide variant (SNV) densities and does not necessitate any demographic or evolutionary assumptions. We test the accuracy and robustness of our method using simulated datasets where we vary length of tracts, number of tracts, the genomic SNV density and levels of correlation between SNV density and NCO event position. Our simulations show that under low SNV densities, like those found in humans, only a minute fraction (∼2%) of NCO events are expected to become visible as gene conversions by moving at least one SNV. We finally illustrate our method by applying it to PacBio sequencing data from human sperm.
Algal growth and morphogenesis-promoting factors released by cold-adapted bacteria contribute to the resilience and morphogenesis of the seaweedUlva(Chlorophyta) in Antarctica (Potter Cove)
Authors: Ghaderiardakani Fatemeh , Ulrich Johann F. , Barth Emanuel , Quartino Maria Liliana , Wichard Thomas
Published: July 2024

Macroalgae are found in a variety of marine vegetation ecosystems around the world, contributing significantly to global net primary production. In particular, the sea lettuce species, i.e., members of the genusUlva(Chlorophyta), are located in many ecological niches and are characterized by excellent adaptability to environmental changes but depend on essential associated bacteria, which release algal growth and morphogenesis-promoting-factors (AGMPFs). Our work investigated the hypothesis that bacteria need to be stress-adapted to provide sufficient amounts of AGMPFs for the growth and morphogenesis ofUlvathroughout its life cycle, even under severe environmental conditions.

Our study thus aimed to understand which bacteria contribute to overcoming a variety of stressors in polar regions. Green macroalgae were collected from Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, to study the associated microbiome and, subsequently, to identify AGMPFs releasing bacteria. Therefore, microbiome analysis was combined with morphogenetic bioassays and chemical analysis, identifying bacteria essential for algal growth under Antarctic conditions. Hereby, axenic cultures of a MediterraneanUlva compressa(cultivarUlva mutabilis), previously developed as a model system for bacteria-induced algal growth and morphogenesis, were inoculated with freshly isolated and cultivable Antarctic bacteria to determine their morphogenetic activity.

The exploratory microbiome investigation identified numerous cold-adapted AGMPF-producing bacteria. Unlike the reference bacterial strains isolated from the Mediterranean Sea, the cold-adapted isolatesMaribactersp. BPC-D8 andSulfitobactersp. BPC-C4, released sufficient amounts of AGMPFs, such as thallusin, necessary for algal morphogenesis even at 2°C. Our results illustrate the role of chemical mediators provided by bacteria in cross-kingdom interactions under cold conditions within aquatic systems. The newly isolated bacteria will enable further functional studies to understand the resilience of the holobiontUlvaand might applied in algal aquaculture even under adverse conditions. The study highlights the importance of ecophysiological assays in microbiome analysis.
Maternal diet alters offspring’s early life host-microbiota communication through goblet cells, resulting in long-lasting diseases susceptibility
Authors: Delaroque Clara , Bonazzi Erica , Huillet Marine , Ellero-Simatos Sandrine , Hao Fuhua , Patterson Andrew , Chassaing Benoit
Published: July 2024

A crucial early-life developmental phase regulates microbiome settling while establishing critical and long-lasting immune and metabolic processes. During this period, the influence of select components of maternal diet on offspring microbiota and health remains largely unknown. To investigate the potential transgenerational impact of maternal exposure to microbiota-disrupting factors, dams were subjected prior breeding to dietary emulsifiers, known to directly perturb the microbiota. Such maternal exposure induced early-life microbiota alterations in offspring which associated with long-lasting susceptibility to diet-induced obesity and intestinal inflammation. These detrimental effects were entirely prevented by early-life microbiota normalization through cross-fostering procedures. Mechanistically, maternal emulsifier exposure induces strong offspring’s impairment in goblet cells-mediated host-microbiota communication which is central in driving the observed long-lasting deleterious effects. To conclude, this study underscores the central role played by maternal intake of microbiota-disrupting agents on the next generation’s microbiota, with long lasting consequences for intestinal and metabolic health.
Bayesian inference in arm posture perception
Authors: Peviani Valeria C. , Joosten Manon G.A. , Miller Luke E. , Medendorp W. Pieter
Published: July 2024

To configure our limbs in space the brain must compute their position based on sensory information provided by mechanoreceptors in the skin, muscles, and joints. Because this information is corrupted by noise, the brain is thought to process it probabilistically, and integrate it with prior belief about arm posture, following Bayes’ rule. Here, we combined computational modeling with behavioral experimentation to test this hypothesis. The model conceives the perception of arm posture as the combination of a probabilistic kinematic chain composed by the shoulder, elbow, and wrist angles, compromised with additive Gaussian noise, with a Gaussian prior about these joint angles. We tested whether the model explains errors in a VR-based posture-matching task better than a model that assumes a uniform prior. Human participants (N=20) were required to align their unseen right arm to a target posture, presented as a visual configuration of the arm in the horizontal plane. Results show idiosyncratic biases in how participants matched their unseen arm to the target posture. We used maximum likelihood estimation to fit the Bayesian model to these observations and retrieve key parameters including the prior means and its variance-covariance structure. The Bayesian model including a Gaussian prior explained the response biases and variance much better than a model with a uniform prior. The prior varied across participants, consistent with the idiosyncrasies in arm posture perception, and in alignment with previous behavioral research. Our work clarifies the biases in arm posture perception within a new perspective on the nature of proprioceptive computations.

New & Noteworthy

We modeled the perception of arm posture as a Bayesian computation. A VR posture-matching task was used to empirically test this Bayesian model. The Bayesian model including a non-uniform postural prior well explained individual participants’ biases in arm posture perception.
Human-specific lncRNA TMEM9B-AS1 is downregulated in skeletal muscle of individuals with type 2 diabetes and regulates ribosomal biogenesis
Authors: Sen Ilke , Smith Jonathon A B , Caria Elena , Savikj Mladen , Lian Kristian , Ellefsen Stian , Zierath Juleen R , Krook Anna
Published: July 2024

Long non-coding RNAs (lncRNAs) are important regulators of skeletal muscle physiology, with altered expression noted in several human diseases including type 2 diabetes. Here we report TMEM9B-AS1, a previously uncharacterized lncRNA, is downregulated in skeletal muscle of men with type 2 diabetes. Silencing of TMEM9B-AS1 in primary human myotubes attenuated protein synthesis, concomitant with reduced phosphorylation of ribosomal protein S6, a downstream target of ERK and mTOR pathways. Moreover, we provide evidence that TMEM9B-AS1 plays a pivotal role in the regulation of ribosomal biogenesis by facilitating mRNA stabilization of the transcription factor MYC through a direct physical interaction with the RNA-binding protein IGF2BP1. Disrupted ribosomal biogenesis resulting from TMEM9B-AS1 silencing is linked reduced skeletal muscle mass in type 2 diabetes, elucidating molecular mechanisms contributing to skeletal muscle loss in metabolic disease.
Cell crowding activates pro-invasive mechanotransduction pathway in high-grade DCIS via TRPV4 inhibition and cell volume reduction
Authors: Bu Xiangning , Ashby Nathanael , Vitali Teresa , Lee Sulgi , Gottumukkala Ananya , Yun Kangsun , Tabbara Sana , Latham Patricia , Teal Christine , Chung Inhee
Published: July 2024

Cell crowding is a common microenvironmental factor influencing various disease processes, but its role in promoting cell invasiveness remains unclear. This study investigates the biomechanical changes induced by cell crowding, focusing on pro-invasive cell volume reduction in ductal carcinoma in situ (DCIS). Crowding specifically enhanced invasiveness in high-grade DCIS cells through significant volume reduction compared to hyperplasia-mimicking or normal cells. Mass spectrometry revealed that crowding selectively relocated ion channels, including TRPV4, to the plasma membrane in high-grade DCIS cells. TRPV4 inhibition triggered by crowding decreased intracellular calcium levels, reduced cell volume, and increased invasion and motility. During this process, TRPV4 membrane relocation primed the channel for later activation, compensating for calcium loss. Analyses of patient-derived breast cancer tissues confirmed that plasma membrane- associated TRPV4 is specific to high-grade DCIS and indicates the presence of a pro-invasive cell volume reduction mechanotransduction pathway. Hyperosmotic conditions and pharmacologic TRPV4 inhibition mimicked crowding-induced effects, while TRPV4 activation reversed them. Silencing TRPV4 diminished mechanotransduction in high-grade DCIS cells, reducing calcium depletion, volume reduction, and motility. This study uncovers a novel pro-invasive mechanotransduction pathway driven by cell crowding and identifies TRPV4 as a potential biomarker for predicting invasion risk in DCIS patients.
Structural Characterization of DNA Binding Domain of Essential Mammalian Protein TTF 1
Authors: Singh Gajender , Bhopale Abhinetra Jagdish , Khatri Saloni , Prakash Prashant , Kumar Rajnish , Singh Sukh Mahendra , Singh Samarendra Kumar
Published: July 2024

Transcription termination factor 1 (TTF1), being multifunctional in nature, is involved in a wide range of critical processes that make it essential for survival of the mammalian cells. TTF1 protein comprises three functional domains: the N-terminal (regulatory/inhibitory) domain, trans-activation domain, and C-terminal domain. The Myb domain is responsible for DNA-binding function of this protein and spans 550 to 732 amino acids (183 residues long). Despite the essential role of TTF1 in multiple cellular processes, there is no physical structure available to date. Purification of the functional full-length protein has been unsuccessful so far. Hence, we moved forward towards characterizing the Myb domain of this essential protein. We first constructed a three-dimensional model of the Myb domain using Robetta server and determined its stability through MD simulation in an explicit solvent. To validate the model, upon codon optimization we cloned this domain into a bacterial expression vector. The protein was then purified to homogeneity and its DNA-binding activity was checked by electro-mobility shift assay. We then proceeded to CD spectroscopy and Raman spectroscopy for secondary structure characterization. The results validated the computational model, concluding that this domain is predominantly helical in nature. The confidence built by this study now pushes us to move ahead in order to solve the atomic structure of this critical domain by crystallography or NMR spectroscopy, which in turn will decipher the exact mechanism by which this essential protein engages DNA to cater to various functions.
Dynamics and Regulatory Roles of RNA m6A Methylation in Unbalanced Genomes
Authors: Zhang Shuai , Wang Ruixue , Luo Kun , Gu Shipeng , Liu Xinyu , Wang Junhan , Zhang Ludan , Sun Lin
Published: July 2024

N6-methyladenosine (m6A) in eukaryotic RNA is an epigenetic modification that is critical for RNA metabolism, gene expression regulation, and the development of organisms. Aberrant expression of m6A components appears in a variety of human diseases. RNA m6A modification in Drosophila has proven to be involved in sex determination regulated by Sxl and may affect X chromosome expression through the MSL complex. The dosage-related effects under the condition of genomic imbalance (i.e., aneuploidy) are related to various epigenetic regulatory mechanisms. Here, we investigated the roles of RNA m6A modification in unbalanced genomes using aneuploid Drosophila. The results showed that the expression of m6A components changed significantly under genomic imbalance, and affected the abundance and genome-wide distribution of m6A, which may be related to the developmental abnormalities of aneuploids. The relationships between methylation status and classical dosage effect, dosage compensation, and inverse dosage effect were also studied. In addition, we demonstrated that RNA m6A methylation may affect dosage-dependent gene regulation through dosage-sensitive modifiers, alternative splicing, the MSL complex, and other processes. More interestingly, there seems to be a closely relationship between MSL complex and RNA m6A modification. It is found that ectopically overexpressed MSL complex, especially the levels of H4K16Ac through MOF could influence the expression levels of m6A modification and genomic imbalance may be involved in this interaction. We found that m6A could affect the levels of H4K16Ac through MOF, a component of the MSL complex, and that genomic imbalance may be involved in this interaction. Altogether, our work reveals the dynamic and regulatory role of RNA m6A modification in unbalanced genomes, and may shed new light on the mechanisms of aneuploidy-related developmental abnormalities and diseases.
Nanotiming: telomere-to-telomere DNA replication timing profiling by nanopore sequencing
Authors: Theulot Bertrand , Tourancheau Alan , Simonin Chavignier Emma , Jean Etienne , Arbona Jean-Michel , Audit Benjamin , Hyrien Olivier , Lacroix Laurent , Le Tallec Benoît
Published: July 2024

Current temporal studies of DNA replication are either low-resolution or require complex cell synchronisation and/or sorting procedures. Here we introduce Nanotiming, a nanopore sequencing-based method producing high-resolution, telomere-to-telomere replication timing (RT) profiles of eukaryotic genomes by interrogating changes in intracellular dTTP concentration during S phase through competition with its analogue bromodeoxyuridine triphosphate (BrdUTP) for incorporation into replicating DNA. Nanotiming solely demands the labelling of asynchronously growing cells with an innocuous dose of BrdU during one doubling time followed by BrdU quantification along nanopore reads. We demonstrate in yeastS. cerevisiaethat Nanotiming precisely reproduces RT profiles generated by reference methods in wild-type and mutant cells inactivated for known RT determinants, for one-tenth of the cost. Nanotiming is simple, accurate, inexpensive, amenable to large-scale analyses, and is capable of unveiling RT at individual telomeres, revealing that Rif1 iconic telomere regulator directly delays the replication only of telomeres with specific subtelomeric elements.
N-acetyl-transferases required for iron uptake and aminoglycoside resistance promote virulence lipid production inM. marinum
Authors: Jones Bradley S. , Pareek Vikram , Hu Daniel D. , Weaver Simon D. , Syska Camille , Galfano Grace , Champion Matthew M. , Champion Patricia A.
Published: July 2024

Phagosomal lysis is a key aspect of mycobacterial infection of host macrophages. Acetylation is a protein modification mediated enzymatically by N-acetyltransferases (NATs) that impacts bacterial pathogenesis and physiology. To identify NATs required for lytic activity, we leveragedMycobacterium marinum,a nontubercular pathogen and an established model forM. tuberculosis. M. marinumhemolysis is a proxy for phagolytic activity. We generatedM. marinumstrains with deletions in conserved NAT genes and screened for hemolytic activity. Several conserved lysine acetyltransferases (KATs) contributed to hemolysis. Hemolysis is mediated by the ESX-1 secretion system and by phthiocerol dimycocerosate (PDIM), a virulence lipid. For several strains, the hemolytic activity was restored by the addition of second copy of the ESX-1 locus. Using thin-layer chromatography (TLC), we found a single NAT required for PDIM and phenolic glycolipid (PGL) production. MbtK is a conserved KAT required for mycobactin siderophore synthesis and virulence. Mycobactin J exogenously complemented PDIM/PGL production in the ΔmbtKstrain. The ΔmbtK M. marinumstrain was attenuated in macrophage andGalleria mellonellainfection models. Constitutive expression of eithereisorpapA5,which encode a KAT required for aminoglycoside resistance and a PDIM/PGL biosynthetic enzyme, rescued PDIM/PGL production and virulence of the ΔmbtKstrain. Eis N-terminally acetylated PapA5in vitro, supporting a mechanism for restored lipid production. Overall, our study establishes connections between the MbtK and Eis NATs, and between iron uptake and PDIM and PGL synthesis inM. marinum. Our findings underscore the multifunctional nature of mycobacterial NATs and their connection to key virulence pathways.

Significance Statement

Acetylation is a modification of protein N-termini, lysine residues, antibiotics and lipids. Many of the enzymes that promote acetylation belong to the GNAT family of proteins.M. marinumis a well-established as a model to understand howM. tuberculosiscauses tuberculosis. In this study we sought to identify conserved GNAT proteins required for early stages of mycobacterial infection. UsingM. marinum,we determined that several GNAT proteins are required for the lytic activity ofM. marinum.We uncovered previously unknown connections between acetyl-transferases required for iron uptake and antimicrobial resistance, and the production of the unique mycobacterial lipids, PDIM and PGLOur data support that acetyl-transferases from the GNAT family are interconnected, and have activities beyond those previously reported.
Structural details of helix-mediated TDP-43 C-terminal domain multimerization
Authors: Rizuan Azamat , Shenoy Jayakrishna , Mohanty Priyesh , dos Passos Patricia M. S. , Mercado Ortiz José F. , Bai Leanna , Viswanathan Renjith , Wang Szu-Huan , Johnson Victoria , Mamede Lohany D. , Ayala Yuna M. , Ghirlando Rodolfo , Mittal Jeetain , Fawzi Nicolas L.
Published: July 2024

The primarily disordered C-terminal domain (CTD) of TAR DNA binding protein-43 (TDP-43), a key nuclear protein in RNA metabolism, forms neuronal inclusions in several neurodegenerative diseases. A conserved region (CR, spanning residues 319-341) in CTD forms transient helix-helix contacts important for its higher-order oligomerization and function that are disrupted by ALS-associated mutations. However, the structural details of CR assembly and the explanation for several ALS-associated variants’ impact on phase separation and function remain unclear due to challenges in analyzing the dynamic association of TDP-43 CTD using traditional structural biology approaches. By employing an integrative approach, combining biophysical experiments, biochemical assays, AlphaFold2-Multimer (AF2-Multimer), and atomistic simulations, we generated structural models of helical oligomerization of TDP-43 CR. Using NMR, we first established that the native state of TDP-43 CR under physiological conditions is α-helical. Next, alanine scanning mutagenesis revealed that while hydrophobic residues in the CR are important for CR assembly, phase separation and TDP-43 nuclear retention function, polar residues down regulate these processes. Finally, pairing AF2-Multimer modeling with AAMD simulations indicated that dynamic, oligomeric assemblies of TDP-43 that are stabilized by a methionine-rich core with specific contributions from a tryptophan/leucine pair. In conclusion, our results advance the structural understanding of the mechanisms driving TDP-43 function and provide a window into the initial stages of its conversion into pathogenic aggregates.
CBP/p300 lysine acetyltransferases inhibit HIV-1 expression in latently infected T-cells
Authors: Horvath Riley M. , Sadowski Ivan
Published: July 2024

HIV-1 latency is regulated by chromatin modifying enzymes, and histone deacetylase inhibitors (HDACi) were previously found to reactivate provirus expression. We report that inhibitors of CBP/p300 acetyltransferases also cause reversal of latency in T-cells. CBP/p300 inhibitors synergize with mechanistically diverse latency reversing agents to cause HIV-1 reactivation. In contrast, inhibition of CBP/p300 impaired the latency reversal by the HDACi SAHA, indicating that CBP/p300 contribute to acetylation on the HIV-1 LTR associated with HDACi-mediated latency reversal. CBP/p300 inhibition caused loss of H3K27ac and H3K4me3 from the LTR, but did not affect association of the inhibitor protein BRD4. Furthermore, inhibition of the additional lysine acetyl transferases PCAF/GCN5 or KAT6A/KAT6B also caused reversal of latency, suggesting that protein acetylation has an inhibitory effect on HIV-1 expression. Collectively, these observations indicate that transcription from the HIV-1 LTR is controlled both positively and negatively by protein acetylation, likely including both histone and non-histone regulatory targets.
Practical and theoretical judgment in data-driven financial due diligence
Authors: Kastrup Tim , Grant Michael , Nilsson Fredrik
Published: July 2024

Purpose

New digital technologies are reshaping the business landscape and accounting work. This paper aims to investigate how incorporating more data and new data analytics (DA) tools impacts the role and use of judgment in financial due diligence (FDD).

Design/methodology/approach

The paper reports findings from a field study at a Big Four accounting firm in Sweden (“DealCo”). The primary data includes semi-structured interviews, observations and other meetings. Theoretically, it draws on Dewey’s The Logic of Judgments of Practise and Logic: The Theory of Inquiry and distinguishes between theoretical (what is probably true) and practical judgment (what to do).

Findings

In DealCo’s FDD practice, using more data and new DA tools meant that the realm of possibility had expanded significantly. To manage the newfound abundance and to use DA effectively, DealCo’s advisors invoked practical and theoretical judgments in different stages and areas of the data-driven FDD. The paper identifies four critical uses of judgment: Setting priorities and exercising restraint (practical judgment) and forming hypotheses and doing sense checks (theoretical judgment). In these capacities, practical judgment and theoretical judgment were essential in transforming raw data into actionable insights and, in effect, an indeterminate situation into a determinate one.

Originality/value

The study foregrounds the practical dimension of knowledge production for decision-making and contributes to a better understanding of the role, use and importance of accounting professionals’ judgment in a data-driven world.
Integrated project delivery enablers to enhance conventional project delivery toward improving design documentation quality
Authors: Agbaxode Peter Dodzi Kwasi , Saghatforoush Ehsan , Dlamini Sitsabo , Korsah John Kwesi
Published: July 2024

Purpose

The purpose of this study was to identify specific enablers intrinsic to integrated project delivery (IPD) that can be adapted into the conventional project delivery (CPD) approach to enhance the quality of design documentation produced under the CPD within the Ghanaian construction industry.

Design/methodology/approach

The study employed questionnaires and semi-structured interviews for data collection. The sample size was 235 responses for questionnaires while 15 participants were interviewed. The survey instrument was piloted with industry professionals to ensure validity. IBM SPSS was used to analyze quantitative data by determining frequencies, percentages, correlation and regression, while content analysis was used on qualitative data with the aid of QSR Nvivo software.

Findings

Key findings include the need to adapt the early involvement of key participants for collaborative design input, tie individual success to overall project success with incentives and establish shared accountability for design errors and encourage open communication.

Practical implications

Adapting IPD enablers into the CPD approach would ensure higher-quality design documentation and more efficient project delivery. This has the potential to improve project outcomes, reduce errors, and foster better collaboration among stakeholders.

Originality/value

This study is the first of its kind to identify specific enablers inherent in IPD that can be adapted into the CPD approach to improve the quality of design documentation within the Ghanaian construction industry.
AI showdown: info accuracy on protein quality content in foods from ChatGPT 3.5, ChatGPT 4, bard AI and bing chat
Authors: Bayram Hati̇ce Merve , Ozturkcan Arda
Published: July 2024

Purpose

This study aims to assess the effectiveness of different AI models in accurately aggregating information about the protein quality (PQ) content of food items using four artificial intelligence (AI) models -– ChatGPT 3.5, ChatGPT 4, Bard AI and Bing Chat.

Design/methodology/approach

A total of 22 food items, curated from the Food and Agriculture Organisation (FAO) of the United Nations (UN) report, were input into each model. These items were characterised by their PQ content according to the Digestible Indispensable Amino Acid Score (DIAAS).

Findings

Bing Chat was the most accurate AI assistant with a mean accuracy rate of 63.6% for all analyses, followed by ChatGPT 4 with 60.6%. ChatGPT 4 (Cohen’s kappa: 0.718, p < 0.001) and ChatGPT 3.5 (Cohen’s kappa: 0.636, p: 0.002) showed substantial agreement between baseline and 2nd analysis, whereas they showed a moderate agreement between baseline and 3rd analysis (Cohen’s kappa: 0.538, p: 0.011 for ChatGPT 4 and Cohen’s kappa: 0.455, p: 0.030 for ChatGPT 3.5).

Originality/value

This study provides an initial insight into how emerging AI models assess and classify nutrient content pertinent to nutritional knowledge. Further research into the real-world implementation of AI for nutritional advice is essential as the technology develops.
Relationships between high-tech SME suppliers and foreign buyers: effects of relational trust, relationship-specific investments and contract specificity on product innovation
Authors: Strupinski Jacek , Witek-Hajduk Marzanna
Published: July 2024

Purpose

Referring to transaction costs theory, resource based view and social exchange theory, this paper examines the interplay between selected dimensions of suppliers’ relationships with foreign buyers, specifically relational trust, contract specificity and relationship-specific investments, as well as analyzes the effects those dimensions have on the suppliers’ product innovation.

Design/methodology/approach

This study uses survey data from 179 small- and medium-sized Polish manufacturing suppliers of high-tech products. Information was collected on dyadic relationships with their key foreign buyers and used as an input to a structural model consisting of multiple linear regressions.

Findings

It was discovered that trust and investments have a mutual positive impact on each other and individually contribute to the supplier’s product innovation. However, once both trust and investments were included in the model, only the latter showed significant effect. Contracts, on the other hand, showed different impact on innovation depending on how it was measured.

Practical implications

Managers should treat trust only as a mechanism to create supportive environment for investments, which exclusively have the power to improve supplier’s product innovation. Contracts’ role, in turn, should be limited to facilitating business relationships.

Originality/value

Only single quantitative studies analyzed trust, investments and contracts as determinants of supplier’s product innovation. Also, focus was not placed on high-tech SMEs in relationships with foreign buyers. As a result, our study provides unique insights on such relationships and unveils new details on an indirect link between trust and product innovation.
Cognitive, affective and behavioural repercussions of perceived quality in tourism vocational education: insights from self-determination theory
Authors: Silva Rejane Santana da , Souki Gustavo Quiroga , Oliveira Alessandro Silva de , Vieira Luís Sérgio Gonçalves , Serra Manuel
Published: July 2024

Purpose

This study aimed to investigate the influence of the perceived quality by students regarding their experiences in vocational schools in tourism, hospitality and food service on cognitive and affective responses (satisfaction, self-efficacy expectations and self-regulation strategies of motivation for learning - SRSML) and commitment (behavioural response).

Design/methodology/approach

A cross-sectional survey was conducted with 454 students from twelve Turismo de Portugal IP-affiliated schools. The theoretical framework was rooted in Self-Determination Theory (SDT) and PLS-SEM, using ADANCO 2.3 software to test the proposed model.

Findings

Perceived quality by students concerning their school experiences are socio-contextual factors that directly influence their satisfaction and self-efficacy expectations (cognitive and affective responses). Satisfaction and self-efficacy expectations positively affected SRSML. Finally, satisfaction and the SRSML positively impacted the students` commitment to schools (behavioural response).

Originality/value

This study contributes to academia by comprehensively addressing 16 perceived quality dimensions within vocational education. It aligns with SDT, revealing that socio-contextual factors affect students’ cognitive, affective, and behavioural responses. Additionally, it demonstrates positive relationships between student satisfaction, self-efficacy expectations, SRSML, and students’ commitment to vocational education institutions. This study emphasises the multidimensional nature of perceived quality, urging educational institutions to address tangible and intangible dimensions to develop strategies to provide high-quality experiences, increasing students` satisfaction, self-efficacy expectations, motivation, and commitment.
A meaning-making perspective on digital ridesharing platforms in underdeveloped markets
Authors: Amissah Karen , Sarpong David , Boakye Derrick , Carrington David John
Published: July 2024

Purpose

The digital platform-based sharing economy has become ubiquitous all over the world. In this paper, we explore how market actors’ conflicting interpretations of digital platforms’ business models give form and shape value co-creation and capture practices in contexts marked by weak institutions and underdeveloped markets.

Design/methodology/approach

Integrating insights from the broader literature on digital platforms and the contemporary turn to “meaning-making” in social theory, we adopt a problematization method to unpack the collective contest over the interpretation of value co-creation and capture from ridesharing platforms in contexts marked by weak institutions and underdeveloped markets.

Findings

Collective contest over the interpretation of digital business models may give rise to competing meanings that may enable (or impede) digital platform providers’ ability to co-create and capture value. We present an integrative framework that delineates how firms caught up in such collective contests in contexts marked by weak institutions and underdeveloped markets may utilise such conditions as marketing resources to reset their organising logic in ways that reconcile the conflicting perspectives.

Practical implications

The paper presents propositions constituting a contribution to a meaning-making perspective on ridesharing digital platforms by offering insights into how digital business models could potentially be localised and adapted to address and align with the peculiarities of contexts. It goes further to present a theoretical model to extend our understanding of the different sources of contestation of meaning of digital platforms.

Originality/value

The meaning-making perspective on digital platforms extends our understanding of how the collective contest over interpretations of value co-creation and capture may offer a set of contradictory frames that yield possibilities for ridesharing platform providers, and their users, to assimilate the organising logic of digital business models into new categories of understanding.
“Sorry, I Don’t Understand …”: effects of task type, personality presentation and performance error on user trust of a personal digital assistant
Authors: Zhang Xinyi , Lee Sun Kyong
Published: July 2024

Purpose

Based on the theoretical predictions of media equation theory and the computers-are-social-actors (CASA) perspective, this study aims to examine the effects of performance error type (i.e. logical, semantic or syntactic), task type and personality presentation (i.e. dominant/submissive and/or friendly/unfriendly) on users’ level of trust in their personal digital assistant (PDA), Siri.

Design/methodology/approach

An experimental study of human–PDA interactions was performed with two types of tasks (social vs functional) randomly assigned to participants (N = 163). While interacting with Siri in 15 task inquiries, the participants recorded Siri’s answers for each inquiry and self-rated their trust in the PDA. The answers were coded and rated by the researchers for personality presentation and error type.

Findings

Logical errors were the most detrimental to user trust. Users’ trust of Siri was significantly higher after functional tasks compared to social tasks when the effects of general usage (e.g. proficiency, length and frequency of usage) were controlled for. The perception of a friendly personality from Siri had an opposite effect on social and functional tasks in the perceived reliability dimension of trust and increased intensity of the presented personality reduced perceived reliability in functional tasks.

Originality/value

The research findings contradict predictions from media equation theory and the CASA perspective while contributing to a theoretical refinement of machine errors and their impact on user trust.
Unlocking destination cultural reputation: the role of sustainable on-site activity involvement as moderator
Authors: Dini Mauro , Curina Ilaria , Hegner Sabrina
Published: July 2024

Purpose

The study aims to provide a detailed definition of Destination Cultural Reputation while also exploring its impact on tourist satisfaction through an investigation of the dynamics between these two elements. Additionally, the potential moderating role of on-site engagement in sustainable activities has been investigated, examining whether satisfaction prompts tourists to exhibit behaviors such as the intention to return and recommend the cultural destination.

Design/methodology/approach

To achieve these objectives, a survey and a structural equation model, based on a sample of 647 visitors to an important UNESCO World Heritage site (i.e. Urbino), have been adopted.

Findings

Findings confirm tourists’ recognition of the destination’s cultural reputation, supporting its relationship with visitor satisfaction. Additionally, tourist satisfaction is positively associated with destination loyalty. However, on-site sustainable activities negatively moderate the relationship between destination reputation and tourist satisfaction. This suggests that a favorable cultural reputation should align with quality sustainable activities in the destination to prevent tourist dissatisfaction.

Practical implications

The paper offers valuable practical insights for destination managers and policymakers aiming to enhance appeal and sustainability.

Originality/value

The study contributes to enhancing the understanding of the complex relationship between reputation, satisfaction, and loyalty in cultural destinations. In addiction it measures the reputation of tourist destination through the specific cultural dimension.
Missing genotype imputation in non‐model species using self‐organizing maps
Authors: Mora‐Márquez Fernando , Nuño Juan Carlos , Soto Álvaro , López de Heredia Unai
Published: July 2024

Current methodologies of genome‐wide single‐nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well‐studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non‐model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self‐organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM‐derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open‐source application programmed in Python3 and with a user‐friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.