bluuebunny/crossref_metadata_2025 huggingface dataset:
Tetramethylrhodamine self-quenching is a probe of conformational change on the scale of 15 – 25 Å
Authors: Girvan Paul , Ying Liming , Dodson Charlotte A
Published: August 2024

Tetramethylrhodamine (TMR) is a fluorescent dye whose self-quenching has been used as a probe of multiple biological phenomena. We determine the distance-dependence of self-quenching and place bounds on the timescale of TMR dissociation. Our results validate fluorescence self-quenching as an alternative to FRET and enable future assays to be designed with confidence.
A Novel Combinatorial Approach Integrating Experimental and Computational Analysis of Antioxidant Activity: Evaluating Catechin and L-Ascorbic Acid in Serum
Authors: Rasool Ayeshum , Chidi Chinanu , Rigaut Sophie , Carty Symone , Soubra-Ghaoui Chirine , Chandra Richa
Published: August 2024

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality globally, with oxidative stress playing a pivotal role in its progression. Free radicals produced via oxidative stress contribute to lipid peroxidation, leading to subsequent inflammatory responses, which then result in atherosclerosis. Antioxidants inhibit these harmful effects through their reducing ability, thereby preventing oxidative damage. In this study, we introduce a with computational models simulating hydrophilic and hydrophobic serum environments. We optimized the Ferric Reducing Ability of Plasma (FRAP) assay at a microscale level to evaluate the antioxidant activity of L-ascorbic acid (vitamin C) and catechin, a phytochemical found in green tea, in normal and hypertriglyceridemic serum. Hypertriglyceridemic serum, characterized by increased hydrophobic lipid content, provides a model to examine the impact of serum triglycerides on antioxidant activity. Additionally, we employed computational models using the Gaussian software to simulate the hydrogen atom transfer (HAT) mechanism, calculating free energy changes and bond dissociation energy (BDE) to assess the antioxidant potency of the studied compounds in both hydrophilic and hydrophobic environments. The computational results align with the experimental finding offering a unique combinatorial approach to assess antioxidant activity in both normal and hypertriglyceridemic serum, with potential implications for clinical interventions.
Vaccination against helminth IL-33-modulators permits immune-mediated parasite ejection
Authors: Smyth Danielle J , Hodge Suzanne , Ong Nicole , Richards Josh , Colomb Florent , Shek Vivien , Frangova Tania , McSorley Henry J
Published: August 2024

The murine intestinal nematodeHeligmosomoides polygyrus bakeripowerfully modulates the host immune response. This is achieved in part through the HpARI family (HpARI1/2/3), which act on IL-33, and the HpBARI family (HpBARI and HpBARI_Hom2), which act on ST2. Here, we find that this immunomodulation is evident only in the first week of infection, with abrogation of ST2 detection and systemic suppression of IL-33-dependent responses. Vaccination with individual HpARI or HpBARI family members raised antibody responses which could block these proteins’ immunomodulatory activities. During infection, vaccination could release the host from immunosuppression: HpARI2 vaccination resulted in much increased ILC2 and Th2 immunity, with heightened serum IL-4 and IL-5 responses, but did not abrogate ST2 suppression. In contrast, a HpBARI+HpBARI_Hom2 vaccination cocktail resulted in abrogation of ST2 suppression, and again increased Th2 immunity and serum cytokine responses. Either of the HpARI2 or the HpBARI cocktail vaccinations provided significant protection against subsequentH. polygyrus bakeriinfection. We therefore show a proof of principle that vaccination with immunomodulatory proteins can protect the host against infection, and can be used as a tool for blocking the effects of specific parasite-derived proteins.
Evidence for Interaction of 5,10-Methylenetetrahydrofolate Reductase (MTHFR) with Methylenetetrahydrofolate Dehydrogenase (MTHFD1) and General Control Nonderepressible 1 (GCN1)
Authors: Buchler Linda R. , Blomgren Linnea Klara Maryann , Burer Celine , Zanotelli Vito Riccardo Tomaso , Froese D Sean
Published: August 2024

5,10-methylenetetrahydrofolate reductase (MTHFR) is a folate cycle enzyme required for the intracellular synthesis of methionine. MTHFR was previously shown to be partially phosphorylated at 16 residues, which was abrogated by conversion of threonine 34 to alanine (T34A) or truncation of the first 37 amino acids (i.e. expression of amino acids 38-656), and promoted by methionine supplementation. Here, we over-expressed wild-type MTHFR (MTFHRWT), as well as the variants MTHFRT34A and MTHFR38-656 in 293T cells to provide further insights into these mechanisms. We demonstrate that following incubation in high methionine conditions (100-1000 uM) MTHFRWT is almost completely phosphorylated, but in methionine restricted conditions (0-10 uM) phosphorylation is reduced, while MTHFRT34A always remains unphosphorylated. Following affinity purification coupled mass spectrometry of an empty vector, MTHFRWT, MTHFRT34A and MTHFR38-656 in three separate experiments, we identified 134 proteins consistently pulled-down by all three MTHFR protein variants, of which 5 were indicated to be likely true interactors (SAINT prediction threshold of 0.95 and 2 fold-change). Amongst these were the folate cycle enzyme methylenetetrahydrofolate dehydrogenase (MTHFD1) and the amino acid starvation sensor General Control Nonderepressible 1 (GCN1). Immunoprecipitation-immunoblotting of MTHFRWT replicated interaction with both proteins. An AlphaFold 3 generated model of the MTHFR-MTHFD1 interaction places the MTHFD1 dehydrogenase/cyclohydrolase domain in direct contact with the MTHFR catalytic domain, suggesting their interaction may facilitate direct delivery of methylenetetrahydrofolate. Overall, we confirm methionine availability increases MTHFR phosphorylation, and identified potential interaction of MTHFR with MTHFD1 and GCN1.
Dysfunctional mechanotransduction regulates the progression of PIK3CA-driven vascular malformations
Authors: Aw Wen Yih , Sawhney Aanya , Rathod Mitesh , Whitworth Chloe P. , Doherty Elizabeth L. , Madden Ethan , Lu Jingming , Westphal Kaden , Stack Ryan , Polacheck William J.
Published: August 2024

Somatic activating mutations inPIK3CAare common drivers of vascular and lymphatic malformations. Despite common biophysical signatures of tissues susceptible to lesion formation, including compliant extracellular matrix and low rates of perfusion, lesions vary in clinical presentation from localized cystic dilatation to diffuse and infiltrative vascular dysplasia. The mechanisms driving the differences in disease severity and variability in clinical presentation and the role of the biophysical microenvironment in potentiating progression are poorly understood. Here, we investigate the role of hemodynamic forces and the biophysical microenvironment in the pathophysiology of vascular malformations, and we identify hemodynamic shear stress and defective endothelial cell mechanotransduction as key regulators of lesion progression. We found that constitutive PI3K activation impaired flow-mediated endothelial cell alignment and barrier function. We show that defective shear stress sensing inPIK3CAE542Kendothelial cells is associated with reduced myosin light chain phosphorylation, junctional instability, and defective recruitment of vinculin to cell-cell junctions. Using 3D microfluidic models of the vasculature, we demonstrate thatPIK3CAE542Kmicrovessels apply reduced traction forces and are unaffected by flow interruption. We further found that draining transmural flow resulted in increased sprouting and invasion responses inPIK3CAE542Kmicrovessels. Mechanistically, constitutive PI3K activation decreased cellular and nuclear elasticity resulting in defective cellular tensional homeostasis in endothelial cells which may underlie vascular dilation, tissue hyperplasia, and hypersprouting inPIK3CA-driven venous and lymphatic malformations. Together, these results suggest that defective nuclear mechanics, impaired cellular mechanotransduction, and maladaptive hemodynamic responses contribute to the development and progression ofPIK3CA-driven vascular malformations.
A screening setup to streamline in vitro Engineered Living Material cultures with the host
Authors: Desai Krupansh , Sankaran Shrikrishnan , del Campo Aranzazu , Trujillo Sara
Published: August 2024

Engineered living materials (ELMs), which usually comprise bacteria, fungi, or animal cells entrapped in polymeric matrices, offer limitless possibilities in fields like drug delivery or biosensing. To determine the conditions that sustain ELM performance while ensuring ELM-host compatibility is essential before testing them in vivo. This is critical to reduce animal experimentation and can be achieved through in vitro investigations. Towards this goal, we designed a 96-well plate-based screening method to streamline ELM growth across culture conditions and determine their compatibility potential in vitro. We showed proliferation of three bacterial species encapsulated in hydrogels over time and screened six different cell culture media. We fabricated ELMs in bilayer and monolayer formats and tracked bacterial leakage. After screening, an appropriate medium was selected that sustained growth of an ELM, and it was used to study cytocompatibility in vitro. ELM cytotoxicity on murine fibroblasts and human monocytes was studied by adding ELM supernatants and measuring cell membrane integrity and live/dead staining, respectively, proving ELM cytocompatibility. Our work illustrates a simple setup to streamline the screening of compatible environmental conditions of ELMs with the host.
Transmembrane channel-like 4 and 5 proteins at microvillar tips are potential ion channels and lipid scramblases
Authors: Ebrahim Seham , Ballesteros Angela , Sharon Zheng W. , Mukherjee Shounak , Hu Gaizun , Weng Wei-Hsiang , Montgomery Jonathan S. , Agyemang Yaw , Cui Runjia , Sun Willy , Krystofiak Evan , Foster Mark P. , Sotomayor Marcos , Kachar Bechara
Published: August 2024

Microvilli—membrane bound actin protrusions on the surface of epithelial cells—are sites of critical processes including absorption, secretion, and adhesion. Increasing evidence suggests microvilli are mechanosensitive, but underlying molecules and mechanisms remain unknown. Here, we localize transmembrane channel-like proteins 4 and 5 (TMC4 and 5) and calcium and integrin binding protein 3 (CIB3) to microvillar tips in intestinal epithelial cells, near glycocalyx insertion sites. We find that TMC5 colocalizes with CIB3 in cultured cells and that a TMC5 fragment forms a complex with CIB3in vitro. Homology and AlphaFold2 models reveal a putative ion permeation pathway in TMC4 and 5, and molecular dynamics simulations predict both proteins can conduct ions and perform lipid scrambling. These findings raise the possibility that TMC4 and 5 interact with CIB3 at microvillar tips to form a mechanosensitive complex, akin to TMC1 and 2, and CIB2 and 3, within the mechanotransduction channel complex at the tips of inner ear stereocilia.
CD4+T cells recruit, then engage macrophages in cognate interactions to clearMycobacterium tuberculosisfrom the lungs
Authors: Becker Samuel H , Ronayne Christine E , Bold Tyler D , Jenkins Marc K
Published: August 2024

IFN-γ-producing CD4+T cells are required for protection against lethalMycobacterium tuberculosis(Mtb) infections. However, the ability of CD4+T cells to suppressMtbgrowth cannot be fully explained by IFN-γ or other known T cell products. In this study, we show that CD4+T cell-derived IFN-γ promoted the recruitment of monocyte-derived macrophages (MDMs) to the lungs ofMtb-infected mice. Although the recruited MDMs became quickly and preferentially infected withMtb, CD4+T cells rapidly disinfected the MDMs. Clearance ofMtbfrom MDMs was not explained by IFN-γ, but rather by MHCII-mediated cognate interactions with CD4+T cells. These interactions promoted MDM expression of glycolysis genes essential forMtbcontrol. Thus, by recruiting MDMs, CD4+T cells initiate a cycle of bacterial phagocytosis,Mtbantigen presentation and disinfection in an attempt to clear the bacteria from the lungs.
Nociceptor Neurons Control Pollution-Mediated Neutrophilic Asthma
Authors: Wang Jo-Chiao , Crosson Theo , Nikpoor Amin Reza , Gupta Surbhi , Rafei Moutih , Talbot Sebastien
Published: August 2024

The immune and sensory nervous systems, having evolved together, use a shared language of receptors and transmitters to maintain homeostasis by responding to external and internal disruptions. Although beneficial in many cases, neurons can exacerbate inflammation during allergic reactions, such as asthma. Our research modeled asthma aggravated by pollution, exposing mice to ambient PM2.5particles and ovalbumin. This exposure significantly increased bronchoalveolar lavage fluid neutrophils and γδ T cells compared to exposure to ovalbumin alone. We normalized airway inflammation and lung neutrophil levels by silencing nociceptor neurons at inflammation’s peak using intranasal QX-314 or ablating TRPV1-expressing neurons. Additionally, we observed heightened sensitivity in chemical-sensing TRPA1 channels in neurons from pollution-exacerbated asthmatic mice. Elevated levels of artemin were detected in the bronchoalveolar lavage fluid from pollution-exposed mice, with artemin levels normalizing in mice with ablated nociceptor neurons. Upon exposure PM2.5particles, alveolar macrophages expressing pollution-sensing aryl hydrocarbon receptors, were identified as the source of artemin. This molecule enhanced TRPA1 responsiveness and increased neutrophil influx, providing a novel mechanism by which lung-innervating neurons respond to air pollution and suggesting a potential therapeutic target for controlling neutrophilic airway inflammation in asthma, a clinically intractable condition.
Remodelling of the glycome of B-cell precursor acute lymphoblastic leukemia cells developing drug-tolerance
Authors: Oliveira Tiago , Zhang Mingfeng , Chen Chun-Wei , Packer Nicolle H. , von Itzstein Mark , Heisterkamp Nora , Kolarich Daniel
Published: August 2024

Reduced responsiveness of precursor B-acute lymphoblastic leukemia (BCP-ALL) to chemotherapy can be first detected in the form of minimal residual disease leukemia cells that persist after 28 days of initial treatment. The ability of these cells to resist chemotherapy is partly due to the microenvironment of the bone marrow, which promotes leukemia cell growth and provides protection, particularly under these conditions of stress. It is unknown if and how the glycocalyx of such cells is remodelled during the development of tolerance to drug treatment, even though glycosylation is the most abundant cell surface post-translational modification present on the plasma membrane. To investigate this, we performedomicsanalysis of BCP-ALL cells that survived a 30-day vincristine chemotherapy treatment while in co-culture with bone marrow stromal cells. Proteomics showed decreased levels of some metabolic enzymes. Overall glycocalyx changes included a shift from Core-2 to less complex Core-1 O-glycans, and reduced overall sialylation, with a shift from α2-6 to α2-3 linked Neu5Ac. Interestingly, there was a clear increase in bisecting complex N-glycans with a concomitant increased mRNA expression ofMGAT3, the only enzyme known to form bisecting N-glycans. These small but reproducible quantitative differences suggest that individual glycoproteins become differentially glycosylated. Glycoproteomics confirmed glycosite-specific modulation of cell surface and lysosomal proteins in drug-tolerant BCP-ALL cells, including HLA-DRA, CD38, LAMP1 and PPT1. We conclude that drug-tolerant persister leukemia cells that grow under continuous chemotherapy stress have characteristic glycotraits that correlate with and perhaps contribute to their ability to survive and could be tested as neoantigens in drug-resistant leukemia.
Solving the "Blind men and the elephant problem": Additive deep learning of complex high dimensional models from partial faceted datasets
Authors: Wu Yufei , Wu Pei-Hsun , Chambliss Allison , Wirtz Denis , Sun Sean
Published: August 2024

Biological systems are complex networks involving tens of thousands of interacting molecular components, and measurable biological functions are emerging properties of these complex networks. Many quantitative studies in biology attempt to connect biological function with molecular components and genes, in the process developing mechanistic understanding. However, it is challenging to quantify the contribution of all components to the biological function simultaneously, especially at the single cell level. Instead, in typical experiments, only a subset of the variables (or facet) is measured. This makes it difficult to obtain a complete and unbiased understanding of the network and how different components of the network cooperatively contribute to the biological function. In this paper, we explore a machine learning approach to combine different facets of data and obtain a complete picture of the biological system based on conditional distributions from faceted data subsets. Both a polynomial regression approach and a neural network approach are developed and examined with two set of concrete examples: A mechanical spring network system deforming under external forces and a small (8-dimensions) biological network including the cellular senescence marker P53. In the later example, single cell data is collected to validate the machine learning approach. We find that the full system is successfully reconstructed from faceted data in both examples. We further discuss the additive property of the model, where the model predictive accuracy increases with increasing number of simultaneously measured variables (dimension of subsets). Our model provides a systematic and novel approach to integrate different pieces of experimental information to reconstruct complex high dimensional systems, arriving at an unbiased and wholistic model of biological function.
On the same wavelength: The relationship between neural synchrony and cognitive ability during movie watching in late childhood and early adolescence
Authors: Lyons KM , Ho W. , Stevenson RA , Owen AM , Stojanoski B
Published: August 2024

Development during late childhood and early adolescence is associated with vast improvements to thinking and reasoning abilities. Coinciding with developing cognitive abilities, the environments children navigate become more complex, with an expanding social circle giving rise to richer and more elaborate experiences. If cognitive development is associated with more complex experiences, do individual differences in cognitive abilities influence how children and adolescents experience their world? To address this question, we investigated the relationships between intersubject correlation (ISC) during movie watching and cognitive scores in children and adolescents (aged 7 -15, N = 309). Data for the current study was obtained from the Healthy Brain Biobank. As part of the Healthy Brain Biobank protocol, participants watched a 10-minute clip ofDespicable Mewhile in the fMRI scanner. They also completed the Weschler Intelligent Scale for Children (WISC). We compared the degree to which participants brain activity synchronized to other participants brain activity during the movie, as measured by ISC, and investigated if scores on the WISC predicted this synchrony. We found adolescents (ages 11-15) with higher cognitive scores showed greater ISC during movie watching in brain networks associated with social processing and executive functions compared to those with below average cognitive scores. These networks included the frontoparietal and default mode networks. This pattern was not evident in children (ages 7-11) who differed in their cognitive scores. These results suggest that adolescents with more mature cognitive abilities may have more similar experiences of naturalistic stimuli. Our results also suggest that children may be less reliant on the frontoparietal network when processing movies, compared to previous findings in adults.
Anxiety and risk-taking behavior maps onto opioid and alcohol polysubstance consumption patterns in male and female mice
Authors: Patarino Makenzie , Wang Ziheng Christina , Wong Katrina , Lee Suhjung Janet , Skillen Emma , Nag Richa , Baskin Britahny , Schindler Abigail G.
Published: August 2024

Polysubstance use is prevalent in the population but remains understudied in preclinical models. Alcohol and opioid polysubstance use is associated with negative outcomes, worse treatment prognosis, and higher overdose risk; but underlying mechanisms are still being uncovered. Examining factors that motivate use of one substance over another in different contexts in preclinical models will better our understanding of polysubstance use and improve translational value. Here we assessed baseline anxiety-like and locomotive behavior and then measured voluntary consumption of multiple doses of alcohol and fentanyl in group housed male and female mice using our novel Socially Integrated Polysubstance (SIP) system. Fifty-six male (n=32) and female (n=24) adult mice were housed in groups of 4 for one week with continuous access to food, water, two doses of ethanol (5% and 10%) and two doses of fentanyl (5 ug/ml and 20 ug/ml). Our analyses revealed sex differences across multiple domains – female mice consumed more liquid in the dark cycle, had higher activity, a higher preference for both ethanol and fentanyl over water, and their fentanyl preference increased over the seven days. We then used machine-learning techniques to reveal underlying relationships between baseline behavioral phenotypes and subsequent polysubstance consumption patterns, where anxiety- and risk-taking-like behavioral phenotypes mapped onto discrete patterns of polysubstance use, preference, and escalation. By simulating more translationally relevant substance use and improving our understanding of the motivations for different patterns of consumption, this study contributes to the developing preclinical literature on polysubstance use with the goal of facilitating better treatment outcomes and novel therapeutic strategies.
Climate, population size, and dispersal influences mutational load across the landscape inVitis arizonica
Authors: Fiscus Christopher J. , Aguirre-Liguori Jonás A. , Gaut Garren R. J. , Gaut Brandon S.
Published: August 2024

The interplay between genetics and the environment determines a population’s ability to survive. Plants, being immobile, are particularly vulnerable to environmental shifts and must adapt to their local environment or face extinction. While considerable efforts have been devoted to identifying adaptive genetic variation and to model its relationship with climate, the role of deleterious variation has been largely overlooked. To address this gap, we studied the landscape genomics ofVitis arizonica, a grape species endemic to the American Southwest and a crop wild relative of the domesticated grapevine. We estimated mutational load, a component of genetic load, in 162 individuals sampled across the present species range and built temporal species distribution models (SDMs) to project the historical, present, and future distributions ofV. arizonicato infer species’ range dynamics. Mutational load was highest for individuals at an inferred leading edge of range expansion. Using random forest regression (RF) models, we examined the relationship between mutational load and climatic variation. The RF models, which we transformed by a weighting method to account for correlated predictors, identified climatic variables, historical dispersion distances, and heterozygosity as high-ranking features. Our findings show that mutational load can be predicted and identifies features that contribute to load. These results provide a foundation for integrating mutational load into broader efforts to understand species adaptation and maladaptation in the face of climate change.

SIGNIFICANCE STATEMENT

The accumulation of deleterious genetic variation (i.e., genetic load) in a genome can reduce organismal fitness and hinder adaptation to local conditions. While the genetic mechanisms contributing to genetic load have been well-studied, its interaction with environmental variation is less understood. Here we explored the relationship between climatic variation, species range, and genetic load inVitis arizonica, a wild grape species native to the American Southwest. We identified associations between climatic variation and genetic load and built a machine learning model to predict genetic load under future climate scenarios. Our findings suggest that the species range will expand and that genetic load will slightly increase at the population level by the end of the century. This work enhances our understanding of the environmental factors influencing genetic load.
Visualizing Single V-ATPase Rotation Using Janus Nanoparticles
Authors: Otomo Akihiro , Wiemann Jared , Bhattacharyya Swagata , Yamamoto Mayuko , Yu Yan , Iino Ryota
Published: August 2024

Understanding the function of rotary molecular motors, such as the rotary ATPases, relies on our ability to visualize the single-molecule rotation. Traditional imaging methods often involve tagging those motors with nanoparticles (NPs) and inferring their rotation from translational motion of NPs. Here, we report an approach using ″two-faced″ Janus NPs to directly image the rotation of single V-ATPase fromEnterococcus hirae, an ATP-driven rotary ion pump. By employing a 500-nm silica/gold Janus NP, we exploit its asymmetric optical contrast — silica core with a gold cap on one hemisphere — to achieve precise imaging of the unidirectional counter-clockwise rotation of single V-ATPase motors immobilized on surfaces. Despite the added viscous load from the relatively large Janus NP probe, our approach provides accurate torque measurements of single V-ATPase. This study underscores the advantages of Janus NPs over conventional probes, establishing them as powerful tools for single-molecule analysis of rotary molecular motors.
A multi-omics approach to identify deleterious mutations in plants
Authors: Baruch Omer , Levy Avraham A. , Mafessoni Fabrizio
Published: August 2024

Crops lose genetic variation due to strong founder effects during domestication, accumulating and potentially exposing recessive deleterious alleles. Therefore, identifying those deleterious variants in domesticated varieties and their functional orthologs in wild relatives is key for plant breeding, food security and in rescuing the biodiversity of cultivated crops. We explored a machine learning strategy to estimate the impact of new and existing mutations in plant genomes, leveraging multi-omics data, encompassing genomic, epigenomic and transcriptomic information. Specifically, we applied a support-vector-machine framework, previously applied to animal datasets, to published omics data of two important crops of the genus Solanum - tomato and potato - and for the model plantArabidopsis thaliana. We show that our approach provides biologically plausible inferences on the role of mutations occurring in different genomic regions and predictions that correlate with natural genetic variation for the three species, supporting the validity of our estimates. Finally, we show that our estimates outperform existing methods relying exclusively on phylogenetic conservation and not leveraging the availability of omics data for crop species. This approach provides a simple score for researchers to prioritize variants for gene editing and breeding purposes.
Pancreatic endocrine cells are transduced by adeno-associated virus serotypes 2 and 9 but not 6
Authors: Ahuja Vishal , Jeyabalan Sanjeev , Tzanakakis Emmanuel S.
Published: August 2024

Adeno-associated viruses (AAVs) have emerged as powerful tools for delivery of genes to a variety of cell types including pancreatic endocrine cells. Currently, AAV serotype 8 (AAV8) is the main AAV vector employed for infecting pancreatic cells for transgene transfer. We aimed to address whether alternative serotypes (AAV2, AAV6, and AAV9) commonly used for gene transfer can be effective in transducing pancreatic cells efficiently. We also screened the additives heparin and neuraminidase to further understand the interaction between the individual AAV types included in this work and the cells for optimal infection. Murine pancreatic β-cells and α-cells as well as fibroblasts were infected with AAV serotypes 2, 6, and 9 carrying the transgene for enhanced green fluorescent protein (eGFP). AAV2 outperformed AAV9 in transducing pancreatic cells, while AAV6 induced cytotoxicity. Both AAV2 and AAV9 displayed slightly higher tropism for α-cells than for β-cells. Compared to the pancreatic cells, the fraction of GFP-expressing cells at various multiplicities of infection was consistently lower for fibroblasts. Incubation of AAV2 with heparin prior to transduction failed to induce any GFP expression in β-cells, indicating that the primary site used for initial interaction with pancreatic cells are heparan sulfate proteoglycans. Treatment of β-cells with neuraminidase prior to AAV9 infection appeared to improve the number of GFP-positive cells, but the increase was not statistically significant. These findings expand the repertoire of available serotypes for AAV-mediated delivery of transgenes to pancreatic endocrine cells and may contribute to gene therapy strategies for pancreas pathologies.
Predicting small-molecule inhibition of protein complexes
Authors: Yaseen Adiba , Roy Soumyadip , Akhter Naeem , Ben-Hur Asa , Minhas Fayyaz
Published: August 2024

Motivation

Protein-Protein Interactions (PPIs) are crucial in biological processes and disease mechanisms, underscoring the importance of discovering PPI inhibitors in drug development. Machine learning can expedite this discovery process. Although machine learning techniques for predicting general compound inhibition are available, we are not aware of any that accurately forecast the inhibitory effect of a compound on aspecificprotein complex, utilizing inputs from both the compound and the protein complex.

Methods

We present the firsttargetedmachine learning based predictor of small molecule based inhibition of protein complexes. Our proposed graph neural network integrates the structure of a protein complex, its protein-protein binding site or interface features and a compound’s SMILES representation to predict the potential of the given compound to inhibit the interaction between proteins in the given complex in a targeted manner.

Results

Validated on the 2p2i-DB-v2 database, encompassing 714 inhibitors across 23 complexes with over 12,000 instances, our model achieves superior predictive accuracy (cross-validation AUC-ROC of 0.86), outperforming established kernel methods and pre-trained neural networks. We further tested the predictive performance of our model on two independent external datasets – one collected from recent publications and another consisting of putative inhibitors of the SARS-CoV-2-Spike and Human-ACE2 protein complex with AUC-ROCs of 0.82 and 0.78, respectively. Our targeted predictor introduces a novel approach for PPI inhibitor discovery, laying foundational work for future advancements in addressing this complex and previously unexplored prediction challenge.

Availability

Code/supplementary material available:https://github.com/adibayaseen/PPI-Inhibitors
Rapid Changes in Risk Preferences Originate from Bayesian Inference on Parietal Magnitude Representations
Authors: de Hollander Gilles , Grueschow Marcus , Hennel Franciszek , Ruff Christian C.
Published: August 2024

Risk preferences – the willingness to accept greater uncertainty to achieve larger potential rewards – determine many aspects of our lives and are often interpreted as an individual trait that reflects a general ’taste’ for risk. However, this perspective cannot explain why risk preferences can change considerably across contexts and even across repetitions of the identical decisions. Here we provide modelling and neural evidence that contextual shifts and moment-to-moment fluctuations in risk preferences can emerge mechanistically from Bayesian inference on noisy magnitude representations in parietal cortex. Our participants underwent fMRI while choosing between safe and risky options that were either held in working memory or present on the screen. Risky options that were held in working memory were less likely to be chosen (risk aversion) when they had large payoffs but more likely to be chosen (risk-seeking) when they had small payoffs. These counterintuitive effects are mechanistically explained by a computational model of the Bayesian inference underlying the perception of the payoff magnitudes: Options kept in working memory are noisier and therefore more prone to central tendency biases, leading small (or large) payoffs to be overestimated (or underestimated) more. Congruent with the behavioural modelling, fMRI population-receptive field modelling showed that on trials where intraparietal payoff representations were noisier, choices were also less consistent and less risk-neutral, in line with participants resorting more to their prior belief about potential payoffs. Our results highlight that individual risk preferences and their puzzling changes across contexts and choice repetitions are mechanistically rooted in perceptual inference on noisy parietal magnitude representations, with profound implications for economic, psychological, and neuroscience theories of risky behaviour.
The preference for surprise in reinforcement learning underlies the differences in developmental changes in risk preference between autistic and neurotypical youth
Authors: Sumiya Motofumi , Katahira Kentaro , Akechi Hironori , Senju Atsushi
Published: August 2024

Risk preference changes nonlinearly across development. Although extensive developmental research on the neurotypical population has shown that risk preference is highest during adolescence, developmental changes in risk preference in autistic people, who tend to prefer predictable behaviors, have not been investigated. Here, we aimed to investigate these changes and underlying computational mechanisms. Using a game-like risk-sensitive reinforcement learning task, we found a significant difference in nonlinear developmental changes in risk preference between the autistic and neurotypical groups (N = 75; age range, 6–30 years). The computational modeling approach with reinforcement learning models revealed that individual preferences for surprise modulated such preferences. These findings indicate that for neurotypical people, adolescence is a developmental period involving risk preference, possibly due to lower surprise aversion. Conversely, for autistic people, who show opposite developmental trajectories of risk preference, adolescence could be a developmental period involving risk avoidance because of low surprise preference.
Regulation of plant metabolism under elevated CO2
Authors: Shokouhi Danial , Hernandez Jakob Sebastian , Walther Dirk , Kepp Gabriele , Schwenkert Serena , Leister Dario , Gremmels Jürgen , Zuther Ellen , Alpers Jessica , Nägele Thomas , Heyer Arnd G.
Published: August 2024

Plant responses to changing environments afford complex regulation at transcriptome and proteome level to maintain metabolic homeostasis. Homeostasis itself constitutes a complex and dynamic equilibrium of metabolic reactions and transport processes among cellular compartments. In the present study, we aimed at the highest possible resolution of this network by combining analysis of transcriptome, proteome and subcellular resolved metabolome of plants exposed to rising carbon dioxide concentrations over a time course of one week. To prove suitability of our approach, we included mutants affected in photorespiratory metabolism and, thus, should deviate from the wildtype in their response to elevated CO2. Our multi-omics analysis revealed that thehpr1-1mutant, defective in peroxisomal hydroxypyruvate reduction, is also affected in cytosolic pyruvate metabolism, reaching out to cysteine synthesis, while the hexokinase mutanthxk1displays a disturbed redox balance upon changing CO2levels. For the third mutant, defective in the mitochondrial protein BOU, we found compelling evidence that the function of this transporter is related to lipoic acid metabolism, thus challenging current interpretations. This demonstrates that the combined omics approach introduced here opens new insights into complex metabolic interaction of pathways shared among different cellular compartments.
Coordination structure and intermolecular interactions in copper(II) acetate complexes with 1,10-phenanthroline and 2,2′-bipyridine
Authors: Guimaraes Samuel P. , Dos Santos Leonardo H. R. , Rodrigues Bernardo L.
Published: August 2024

The crystal structures of two coordination compounds, (acetato-κO)(2,2′-bipyridine-κ2
N,N′)(1,10-phenanthroline-κ2
N,N′)copper(II) acetate hexahydrate, [Cu(C2H3O2)(C10H8N2)(C12H8N2)](C2H3O2)·6H2O or [Cu(bipy)(phen)Ac]Ac·6H2O, and (acetato-κO)bis(2,2′-bipyridine-κ2
N,N′)copper(II) acetate–acetic acid–water (1/1/3), [Cu(C2H3O2)(C10H8N2)2](C2H3O2)·C2H4O2·3H2O or [Cu(bipy)2Ac]Ac·HAc·3H2O, are reported and compared with the previously published structure of [Cu(phen)2Ac]Ac·7H2O (phen is 1,10-phenanthroline, bipy for 2,2′-bipyridine, ac is acetate and Hac is acetic acid). The geometry around the metal centre is pentacoordinated, but highly distorted in all three cases. The coordination number and the geometric distortion are both discussed in detail, and all complexes belong to the space group P\overline{1}. The analysis of the geometric parameters and the Hirshfeld surface properties d
norm and curvedness provide information about the metal–ligand interactions in these complexes and allow comparison with similar systems.
Sustainability in human resource management practices used by small and medium-sized enterprises: a systematic review
Authors: Purgał-Popiela Joanna
Published: August 2024

Purpose

This study aims to determine the current state of research on sustainability in the context of human resource management (HRM) practices adopted by small and medium-sized enterprises (SMEs), identify the most important gaps and propose an agenda for future studies.

Design/methodology/approach

Through a systematic literature review (SLR), this study comprehensively examines the relevant literature on sustainability-related aspects of HRM in SMEs. It includes descriptive and thematic analyses of 29 research articles published in high-ranked academic journals selected from 506 records retrieved from four major databases (Scopus, Web of Science, ScienceDirect and EBSCOhost).

Findings

The findings suggest a growing interest in sustainability-related HRM in SMEs after 2020. Notably, most studies focused on green and social sustainability concerns, with limited attention to the triple bottom line (TBL) perspective. A detailed examination revealed variations among the three streams of research in terms of methodology, location of studies, nature of sustainability-HRM linkage and placement of HRM practices in research models. Despite these differences, positive effects of HRM practices on sustainability integration seem evident, including impacts on employee competences, behaviors and company-level outcomes.

Originality/value

This article is the first to systematically review the literature on the sustainability-HRM nexus specifically for SMEs. It contributes by identifying thematic clusters, methodological trends, contextual aspects and outcomes of sustainability-HRM integration, thereby laying the groundwork for future research.
A systematic taxonomic review of the application of BIM and digital twins technologies in the construction industry
Authors: Rashidi Amirreza , Sarvari Hadi , Chan Daniel W.M. , Olawumi Timothy O. , Edwards David J.
Published: August 2024

Purpose

This study provides a comprehensive analysis of the transition from Building Information Modelling (BIM) to digital twins (DT) in the construction industry. Specifically, the research explores the current state (themes and trends) and future directions of this emerging research domain.

Design/methodology/approach

A multi-stage approach was employed that combines scientometric and systematic review approaches. The scientometric analysis involves quantitative assessment of scientific publications retrieved from the Web of Science database – using software tools like VOSviewer and HistCite. The systematic review involved a rigorous synthesis and evaluation of the existing literature to identify research gaps, themes, clusters and future directions. Clusters obtained from the scientometric analysis of the co-occurrence network were then used as a subject base for a systematic study.

Findings

Emergent findings reveal a rapidly growing interest in BIM-DT integration, with over 90% of publications since 2020. The United Kingdom, China and Italy are the leading contributing countries. Five prominent research clusters identified are: (1) Construction 4.0 technologies; (2) smart cities and urban environments; (3) heritage BIM and laser scanning; (4) asset and facility management; and (5) energy and sustainability. The study highlights the potential of BIM-DT integration for enhancing project delivery, asset management and sustainability practices in the built environment. Moreover, the project’s life cycle operation phase has garnered the most attention from researchers in this field compared to other phases.

Originality/value

This unique study is comprehensive in its approach by combining scientometric and systematic methods to provide a quantitative and qualitative evaluation of the BIM-DT research landscape. Unlike previous reviews that focused solely on facility management, this study’s scope covers the entire construction sector. By identifying research gaps, challenges and future directions, this study establishes a solid foundation for researchers exploring this emerging field and envisions the future landscape of BIM-DT integration in the built environment.
Sustainability agendas and communication design pedagogy in HE
Authors: Ellis Thomas , Newton Vic
Published: August 2024

Purpose

Previous research has evidenced that communication design students wish to engage further with sustainable practices but struggle to understand how (Newton and Ellis, HER conference 2023). Whereas other design disciplines (fashion, product, furniture) can often focus on a “physical” output, communication design embraces multiple outcomes, distributed throughout a range of platforms, representing an area of industry and study which can prove difficult to define. This study aims to add further clarity as to how students consider sustainability aligned to their practice.

Design/methodology/approach

Previous focus group research sought to uncover how communication design students implicitly consider “sustainability”, uncovering that their knowledge is limited. Suggestions from participants emphasised that it was the role of the institution, not the student, to fully integrate sustainability into practice and to define methods they can deploy. This paper notes a subsequent workshop conducted with 33 Level 5 undergraduate students asking them to reflect on Sustainable Development Goals (SDGs) 12/13 in relation to meaningful practice and institutional responsibility.

Findings

Workshops demonstrated the need to engage with sustainable thinking throughout every stage of development. It is clear that students demand more from academic staff at programme level, and from the institution at large, to provide further solutions to sustainability concerns which are relevant to their specific practice.

Originality/value

Discussion surrounding pedagogical practice across communication design lacks interrogation, yet the discipline represents a significant aspect of both design and contemporary society. It is paramount that methods for reinforcing implicit engagement with sustainable best practice within students, their development and their future beyond university are therefore developed.
How representational fidelity affects sociability and cyberself engagement in the Metaverse
Authors: Lee Seoyoun , Chang Younghoon , Park Jaehyun , Chong Alain Yee Loong , Yin Qiuju
Published: August 2024

Purpose

This study examines how users' multidimensional representational fidelity factors affect sociability and cyberself engagement in the Metaverse platform; that is, how they interact with newly defined self-images as their personas in the environments. It investigates how representational fidelity serves platform users to perform social roles and increase their sociability by establishing a new cyberself, thus influencing continuous platform use.

Design/methodology/approach

This study surveyed 314 users of the Metaverse platform Horizon, where users can create a virtual agent avatar, meet people in the same online environment in real time, and interact with a sense of three-dimensional immersion. Data were analyzed using partial least squares regression models.

Findings

User socialization significantly influenced the intention to use the Metaverse platform. Representational fidelity was a crucial variable for sociability, and activity representational fidelity was the most influential aspect among the four other elements. Platforms should consider how to enable users to create and use activities that faithfully represent their personas.

Originality/value

The novelty of this study is that it introduces representational fidelity based on representation theory into the context of virtual persona in the Metaverse platform. This study extended representational fidelity to the socialization perspective by utilizing the integrated model of user satisfaction and the technology acceptance model. Through the results, this study emphasized that users' sociability significantly influences their intention to use the Metaverse platform. Finally, this study provides a feasible guideline on how practitioners could design and strengthen their platforms so that users can represent their cyberselves faithfully.