bluuebunny/crossref_metadata_2025_split huggingface dataset:
Conformational dynamics and multi-modal interaction of Paxillin with the Focal Adhesion Targeting Domain
Authors: Bhattacharya Supriyo , He Yanan , Chen Yihong , Mohanty Atish , Grishaev Alexander , Kulkarni Prakash , Salgia Ravi , Orban John 
Published: January 2025

ABSTRACTPaxillin (PXN) and focal adhesion kinase (FAK) are two major components of the focal adhesion complex, a multiprotein structure linking the intracellular cytoskeleton to the cell exterior. PXN interacts directly with the C-terminal targeting domain of FAK (FAT) via its intrinsically disordered N-terminal domain. This interaction is necessary and sufficient for localizing FAK to focal adhesions. Furthermore, PXN serves as a platform for recruiting other proteins that together control the dynamic changes needed for cell migration and survival. Here, we show that the PXN disordered region undergoes large-scale conformational restriction upon binding to FAT, forming a 48-kDa multi-modal complex consisting of four major interconverting states. Although the complex is flexible, each state has unique sets of contacts involving disordered regions that are both highly represented in ensembles and conserved. Moreover, conserved intramolecular contacts from glutamine-rich regions in PXN contribute to high entropy and thus stability of the FAT bound complex. As PXN is a hub protein, the results provide a structural basis for understanding how perturbations that lead to cellular network rewiring, such as ligand binding and phosphorylation, may lead to shifts in the multi-state equilibrium and phenotypic switching.
The role of MYB46 in modulating polysaccharide acetylation by mediating the transcriptional regulation of cell wall-related genes in Arabidopsis
Authors: Rastogi Lavi , Deshpande Sanjay , Pawar Prashant Anupama-Mohan 
Published: January 2025

AbstractUnderstanding the mechanism behind the transcriptional regulation of polysaccharideO-acetylation remains a key challenge that might be regulated through transcription factors. Our earlier work revealed the upregulation ofAtGELP7 in MYB46 overexpression lines, prompting us to investigate how MYB46 transcriptionally controlsAtGELP7 including other cell wall acetylation pathway genes in Arabidopsis. In MYB46 overexpression lines, we observed alteration in acetylation levels on xylan, xyloglucan and pectin in different tissue types, which suggests complex and tight regulation of acetylation homeostasis in the cell wall. Further, our transcriptomic data revealed the simultaneous upregulation of bothAtGELP7 (acetyl xylan esterase) and xylan-specific TBLs (xylanO-acetyltransferases) indicating sophisticated regulation of cell wall acetylation homeostasis. Using transactivation studies in Nicotiana andpAtGELP7::GUSstable lines, we found that MYB46 enhancesAtGELP7 expression probably through downstream regulators which could be either MYB103 or other MYBs. In addition, extensive cell wall analysis of MYB46 overexpression lines showed differential sugar distribution, preferably to major cell wall components such as cellulose, xyloglucan, and xylan across different tissue types of different developmental stages. Moreover, the integration of RNA-sequencing and ChIP-sequencing data uncovered previously unknown, novel probable direct gene targets of MYB46 that may be involved in polysaccharide acetylation and cell wall remodeling.
GPNMB is a biomarker for lysosomal dysfunction and is secreted via LRRK2-modulated lysosomal exocytosis
Authors: Bogacki Erin C. , Longmore George , Lewis Patrick A. , Herbst Susanne 
Published: January 2025

AbstractGenome-wide association studies have identifiedGlycoprotein Nmb(GPNMB) as a risk factor for Parkinson’s Disease. The risk allele increasesGPNMBtranscription and GPNMB protein levels in the CSF highlighting GPMNB as a potential biomarker for Parkinson’s Disease. However, a lack of knowledge of GPNMB’s function and mechanism of secretion have hindered an interpretation of secreted GPNMB levels. In this study, we assessed the mechanism of GPNMB secretion by macrophages, the primary cell type expressing GPNMB in the brain. We show that GPNMB is secreted in response to lysosomal stress via lysosomal exocytosis and highlight the Parkinson’s Disease risk factor LRRK2 as a strong modulator of GPNMB secretion.
Assessing the role of BNST GABA neurons in backward conditioned suppression
Authors: Ly Annie , Hotchkiss Hayden , Prévost Emily D. , Pelletier Julianne , Deming Melissa , Murib Luma , Root David H. 
Published: January 2025

ABSTRACTConditioned suppression is a useful paradigm for measuring learned avoidance. In most conditioned suppression studies, forward conditioning is used where a cue predicts an aversive stimulus. However, backward conditioning, in which an aversive stimulus predicts a cue, provides unique insights into learned avoidance due to its influence on both conditioned excitation and inhibition. We trained mice to consume sucrose in context A, associated an aversive stimulus in context B to few or many forward or backwards paired cues (CS+), and then tested for conditioned suppression in context A in response to the CS+. We found that few or many forward CS+ and few backward CS+ produced conditioned suppression, but many backwards cues did not. Administration of diazepam, a positive allosteric modulator of the GABA-A receptor, prevented conditioned suppression to the backward CS+ but not to the forward CS+. Furthermore, freezing behavior was observed in response to the forward CS+ but not the backward CS+, and diazepam had no effect on freezing or locomotion. We next examined BNST GABA neurons for potential sensitivity to backwards cues and conditioned suppression. VGaT BNST signaling increased in response to sucrose licks during the backward CS+ but not to licks outside the CS+ and not to the backward CS+ onset or offset. Using designer receptors, we found that BNST VGaT neuron activation, but not its inhibition, prevented backward conditioned suppression expression. We conclude that backward conditioned suppression is dependent on both positive allosteric modulation of GABA on GABA-A receptors by diazepam and BNST GABA neurons.
Perturbing whole-brain models of brain hierarchy: an application for depression following pharmacological treatment
Authors: Socoró Garrigosa Marcel , Sanz Perl Yonatan , Kringelbach Morten L. , Carhart-Harris Robin , Vohryzek Jakub , Deco Gustavo 
Published: January 2025

AbstractNeural representation can extend beyond localised activity to encompass global patterns, where information is distributed across brain networks in a hierarchical manner. Recent research suggests that the hierarchy of causal influences shaping these patterns can serve as a signature of distinct brain states, with implications for neuropsychiatric disorders. Here, we first delve into how whole-brain models, guided by the Thermodynamics of Mind framework, can estimate the brain hierarchy of specific brain states, and how perturbations of such models can study the in-silico transitions to other states represented by static functional connectivity. We then show an application for major depressive disorder, where different brain hierarchical reconfigurations have been found following psilocybin and escitalopram treatments. We build whole-brain models of depressed patients before and after psilocybin and escitalopram interventions, and we carry a dynamic sensitivity analysis to explore the susceptibility of brain states and their drivability to healthier states. We show that susceptibility is on average reduced by escitalopram and increased by psilocybin, and that both treatments succeed in promoting healthier transitions. These results align with the post-treatment window of plasticity opened by serotonergic psychedelics, as well as with the similar clinical efficacy of both drugs observed in clinical trials.Graphical AbstractWe apply whole-brain models of brain hierarchy based on the Thermodynamics of Mind framework to investigate state transitions in depression. Dynamic sensitivity analysis explores how psilocybin and escitalopram affect susceptibility and drivability to healthier states. Results show that psilocybin increases susceptibility, while escitalopram reduces it, with both enabling optimal transitions. This pipeline demonstrates the promise of in-silico approaches to inform neurostimulation protocols, potentially enhancing or complementing antidepressant therapies.
High Impedance Microstrip Resonators and Transceiver Arrays for Ultrahigh Field 10.5T MR Imaging
Authors: Zhang Xiaoliang , Payne Komlan , Zhao Yunkun 
Published: January 2025

AbstractMultichannel transceiver coil arrays are needed to enable parallel imaging and B1 manipulation in ultrahigh field MR imaging and spectroscopy. However, the design of such transceiver coils and coil arrays often faces technical challenges in achieving the required high operating frequency at the ultrahigh fields and sufficient electromagnetic (EM) decoupling between resonant elements. In this work, we propose a high impedance microstrip transmission line resonator (HIMTL) technique that has unique high frequency capability and adequate EM decoupling without the use of dedicated decoupling circuits. To validate the proposed technique for the ultrahigh field 10.5T applications, a two-channel high impedance microstrip array with the element dimension of 8cm by 8cm was built and tuned to 447 MHz, Larmor frequency of proton at 10.5T, for signal excitation and reception. Bench tests and numerical simulations were performed to evaluate its feasibility and performance. The results show that the proposed high impedance microstrip technique can be a simple and robust way to design high frequency transceiver coils and coil arrays for ultrahigh field MR applications.
Development and External Validation of a Machine Learning Model to Predict Restriction from Spirometry
Authors: Moffett Alexander T. , Balasubramanian Aparna , McCormack Meredith C. , Aysola Jaya , Ungar Lyle H. , Halpern Scott D. , Weissman Gary E. 
Published: January 2025

AbstractBackgroundThough European Respiratory Society and American Thoracic Society (ERS/ATS) guidelines for pulmonary function test (PFT) interpretation recommend the use of the forced vital capacity (FVC) lower limit of normal (LLN) to exclude restriction, recent data suggest that the negative predictive value (NPV) of the FVC LLN is lower than has been accepted, particularly among non-Hispanic Black patients. We sought to develop and externally validate a machine learning (ML) model to predict restriction from spirometry and determine whether its use may improve the accuracy and equity of PFT interpretation.MethodsWe included PFTs with both static and dynamic lung volume measurements for patients between 18 and 80 years of age who were tested at pulmonary diagnostic labs within two health systems. We used PFTs from one health system to train logistic regression, random forest, and boosted tree models to predict restriction using demographic, anthropometric, and spirometric data. We used PFTs from the second health system to externally validate these models. The primary measure of model performance was the NPV. Racial equity was assessed by comparing the NPV among non-Hispanic Black and non-Hispanic White patients.FindingsA total of 42 462 PFTs were used for model development and 24 524 for external validation. The prevalence of restriction was 29.8% in the development dataset and 39.6% in the validation dataset. All three ML models outperformed the FVC LLN by a wide margin, both overall and among all demographic subgroups. The overall NPV of the random forest model (88.3%, 95% confidence interval [CI] 87.8% to 88.9%) was significantly greater than that of the FVC LLN (72.7%, 95% CI 72.1% to 73.3%). The NPV of the random forest model was greater than that of the FVC LLN among both non-Hispanic Black (74.6% [95% CI 72.5% to 76.6%] versus 49.5% [95% CI 47.8% to 51.2%]) and non-Hispanic White (90.9% [95% CI 90.3% to 91.5%] versus 79.6% [95% CI 78.9% to 80.3%]) patients.InterpretationML models to exclude restriction from spirometry improve the accuracy and equity of PFT interpretation but do not fully eliminate racial differences.
The Hypno-PC: Uncovering Sleep Dynamics through Principal Component Analysis and Hidden Markov Modeling of Electrophysiological Signals
Authors: Guendelman Miriam , Shriki Oren 
Published: January 2025

AbstractThe conventional approach to sleep analysis relies on pre-defined, visually scored stages derived from electrophysiological signals. This manual method demands substantial effort and is influenced by subjective assessments, implicitly assuming that these categories accurately reflect underlying biological processes. Recent advancements indicate that low-dimensional representations of complex brain activity can provide objective means of identifying brain states. These approaches can potentially uncover inherent patterns within sleep, offering valuable insights into its organization.In this study, we applied Principal Component Analysis (PCA) to spectral features extracted from high-density EEG, EOG, EMG, and ECG recorded overnight at both 30– and 4-second resolutions. Notably, the first principal component—the “Hypno-PC”—strongly aligns with the hypnogram at both time scales. Subsequently, we employed a Gaussian Hidden Markov Model (GHMM) to delineate discrete states in the PCA-transformed data and to quantify their temporal dynamics. Using minimal supervision (less than 0.5% of the data labeled) and a cross-subject approach, the model achieved alignment with standard sleep labels comparable to the typical inter-rater agreement. Finally, independent component analysis (ICA) was applied to the PCA space, decomposing it into an independent set of components that potentially represent distinct physiological processes.The integrated use of PCA, GHMM, and ICA provides a reproducible and scalable methodology that aligns with traditional sleep staging, while offering a more flexible and comprehensive perspective on sleep states. Our findings indicate that these data-driven, unsupervised methods effectively uncover the intrinsic dynamics of sleep, advancing automated sleep analysis and enhancing our understanding of sleep organization.Statement of SignificanceThis study introduces a data-driven framework for sleep analysis designed to objectively identify brain states using low-dimensional representations of electrophysiological signals during sleep. By integrating a suite of unsupervised learning techniques, our methodology offers an alternative to subjective manual scoring, potentially enhancing both efficiency and reproducibility. In addition to aligning with traditional sleep staging, this approach uncovers subtle sleep dynamics across multiple time scales, enabling the discovery of patterns that conventional methods might overlook. These advancements hold promise for automated sleep monitoring and the study of sleep disorders, potentially improving diagnostic accuracy and facilitating large-scale sleep research. By addressing current limitations in sleep analysis techniques, this framework lays the groundwork for more elaborate and scalable assessments.
MECOM is a master repressor of myeloid differentiation through dose control ofCEBPAin acute myeloid leukemia
Authors: Pastoors Dorien , Havermans Marije , Mulet-Lazaro Roger , Smeenk Leonie , Ottema Sophie , Erpelinck-Verschueren Claudia , van Herk Stanley , Anthonissen Maikel , Grob Tim , Wouters Bas J. , Beverloo Berna , Haferlach Torsten , Haferlach Claudia , Zuber Johannes , Bindels Eric , Delwel Ruud 
Published: January 2025

AbstractEnhancer translocations, due to 3q26 rearrangements, drive out-of-contextMECOMexpression in an aggressive subtype of acute myeloid leukemia (AML). Direct depletion of MECOM using an endogenous auxin-inducible degron immediately upregulates expression of myeloid differentiation factorCEBPA. MECOM depletion is also accompanied by a severe loss of stem cells and gain of differentiation. MECOM exerts its inhibitory effect by binding to the +42kbCEBPAenhancer, a gene essential for neutrophil development. This is partially dependent on the interaction betweenMECOMand its co-repressor CTBP2. We demonstrate thatCEBPAoverexpression can bypass the MECOM-mediated block of differentiation. In addition, AML patients withMECOMoverexpression through enhancer hijacking show significantly reducedCEBPA. Our study directly connects two main players of myeloid transformationMECOMandCEBPA, and it provides insight into the mechanism by which MECOM maintains the stem cell state in a unique subtype of AML by inactivatingCEBPA.
From experimental clues to theoretical modeling: Evolution associated with the membrane-takeover at an early stage of life
Authors: Ma Wentao , Yu Chunwu 
Published: January 2025

AbstractModern cell membranes are primarily composed of phospholipids, while primitive cell membranes in the beginning of life are believed to have formed from simpler lipids (such as fatty acids) synthesized in the prebiotic environment. An attractive experimental study suggested that the corresponding “membrane-takeover” (as an evolutionary process) is likely to have occurred very early (e.g. in the RNA world) due to some simple physical effects, and might have subsequently triggered some other evolutionary processes. Here, via computer modeling on a system of RNA-based protocells, we convinced the plausibility of such a scenario and elaborated on relevant mechanisms. It is shown that in protocells with a fatty-acid membrane, because of the benefit of phospholipid content (i.e., stabilizing the membrane), a ribozyme favoring the synthesis of phospholipids may emerge; subsequently, due to the reduced membrane permeability on account of the phospholipid content, two other functional RNA species could arise: a ribozyme exploiting more fundamental materials (thus more permeable) for nucleotide synthesis and a species favoring across-membrane transportation. This case exemplifies a combination of experimental and theoretical efforts regarding early evolution, which may shed light on that notoriously complicated problem: the origin of life.
“On the same wavelength”: reconciling competing logics in tax client relationships
Authors: Lynch Ruth 
Published: January 2025

PurposeThe purpose of this paper is to explore the dynamics in the relationship between tax practitioners and their tax clients, to understand how tax practitioners reconcile competing logics in their tax work.Design/methodology/approachThis research adopts a qualitative approach in which semi-structured interviews are conducted with 68 tax practitioners across 11 countries, allowing for the examination of an in-depth personal perspective on tax practitioners’ relationships with their clients.FindingsUsing a Bourdieusian frame, I find that long-term client relationships built on trust and shared values, as moderated by risk appetite and cultural markers, can enable tax practitioners to reconcile competing logics in their advisory work.Practical implicationsThe research findings presented reflect the way in which tax practitioners navigate, build up and maintain long-term relationships with their clients. The findings are highly relevant for regulators as my research shows that clients share a similar tax risk appetite with their tax advisor, thus this can assist regulators in curbing tax non-compliance and in identifying more tax-aggressive tax practitioners and taxpayers.Originality/valuePrevious studies (Carter and Spence, 2014; Harber and Willows, 2022) have examined the tension between commercial and other professional logics among senior accountants working in Big 4 firms. I extend and deepen this work to tax practitioners, drawing on a substantial corpus of interviews to examine the role of the client relationship in explaining the heterogeneity of the field. These findings add to the understanding of client agency and to the subtleties of professional relationships within the tax domain.
Developing an assessment model of supply chain resilience in prefabricated construction based on the ripple effect and supply chain performance
Authors: Ye Meng , Li Yueran , Ye Kunhui 
Published: January 2025

PurposePrefabricated construction has been rapidly developing and intensifying the reliance on the supply chain. The pandemic of COVID-19 induced severe disruptions to the supply chain operation and thus attracted the research attention on the supply chain resilience (SCR) under various events. Assessing the resilience of the prefabricated construction supply chain (PCSC) is essential for surviving the shifting disruptive attacks and ensuring consistent, reliable operation. Based on the ripple effect and supply chain performance (SCP), this study aims to develop an assessment model for SCR of PCSC.Design/methodology/approachHaving identified the roles and material flows among stakeholders, a PCSC network is established. Utilizing the ripple effect model, it develops an assessment framework tailored for PCSCs, which then evolves into a comprehensive assessment model for evaluating the SCR by integrating the disruptive influence and the pre-and post-disruption SCP. Case study is then applied to validate the model.FindingsUsing SCP metrics and disruptive influence assessment as basic dimensions, the SCR can be assessed and expressed through a vector formula. Operating costs and asset utilization can effectively reflect changes in resilience, paying attention to their real-time changes can provide a better judgment of the current stage of disruptions.Originality/valueThe assessment model of SCR accounts for the ripple effect within prefabricated construction, offering a thorough understanding of how disruptions impact the entire supply chain network. Additionally, this model introduces a novel approach to evaluating SCR in reverse by leveraging SCP metrics instead of direct measurement, thereby minimizing potential biases.
Business incubators as a driver of sustainable entrepreneurship development: evidence from the Italian experience
Authors: Bonfanti Angelo , Mion Giorgio , Vigolo Vania , De Crescenzo Veronica 
Published: January 2025

PurposeThis study aims to assess whether and how non-born-sustainable business incubators (BIs) – that is, BIs whose business model was not originally sustainability-oriented – promote sustainable entrepreneurship development.Design/methodology/approachThe study adopts a qualitative research design based on grounded theory and an interpretive approach. The analysis is developed by collecting interviews with ten Italian BIs, selected by purposive sampling and examining data using the Gioia methodology.FindingsThe results show that BIs, using various specific tools, facilitate the creation of a sustainability-oriented ecosystem. In this context, BIs help start-ups develop a purpose, a cultural mindset and business models that enable them to face the challenges of today’s competitive environment, in which sustainability has become (and will increasingly be) an essential requirement for companies.Research limitations/implicationsThis study contributes to the literature by highlighting the active role of non-born-sustainable BIs in promoting the development of sustainable entrepreneurship.Practical implicationsThis research has practical implications related to the opportunities for embedding sustainability in BIs’ purpose and defining a framework of operations and practices that can boost innovativeness while having a positive impact on the community and on the environment. Finally, findings suggest that BIs can foster cost reduction when implementing sustainability in start-ups.Social implicationsThe study suggests that BIs, as drivers of social change, could be sustained by public assistance and help from well-established firms to promote the spread of sustainable entrepreneurship culture and the success of sustainability-oriented start-ups.Originality/valueBIs have the potential to promote sustainable entrepreneurship, but this topic is still under-researched. While existing studies have examined the role of born-sustainable BIs in specific business sectors, this research is one of the first attempts to explore the role of non-born-sustainable BIs in fostering sustainable entrepreneurship.