bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endogenous LRRK2 and PINK1 function in a convergent neuroprotective ciliogenesis pathway in the brain
Authors: Bagnoli Enrico , Lin Yu-En , Burel Sophie , Jaimon Ebsy , Antico Odetta , Themistokleous Christos , Nikoloff Jonas M. , Morella Ilaria , Watzlawik Jens O. , Fiesel Fabienne C. , Springer Wolfdieter , Tonelli Francesca , Brooks Simon P. , Dunnett Stephen B. , Brambilla Riccardo , Alessi Dario R. , Pfeffer Suzanne R. , Muqit Miratul M. K. 
Published: June 2024

ABSTRACTMutations in LRRK2 and PINK1 are associated with familial Parkinson’s disease (PD). LRRK2 phosphorylates Rab GTPases within the Switch II domain whilst PINK1 directly phosphorylates Parkin and ubiquitin and indirectly induces phosphorylation of a subset of Rab GTPases. Herein we have crossed LRRK2 [R1441C] mutant knock-in mice with PINK1 knock-out (KO) mice and report that loss of PINK1 does not impact endogenous LRRK2-mediated Rab phosphorylation nor do we see significant effect of mutant LRRK2 on PINK1-mediated Rab and ubiquitin phosphorylation. In addition, we observe that a pool of the Rab-specific, PPM1H phosphatase, is transcriptionally up-regulated and recruited to damaged mitochondria, independent of PINK1 or LRRK2 activity. Parallel signalling of LRRK2 and PINK1 pathways is supported by assessment of motor behavioural studies that show no evidence of genetic interaction in crossed mouse lines. Previously we showed loss of cilia in LRRK2 R1441C mice and herein we show that PINK1 KO mice exhibit a ciliogenesis defect in striatal cholinergic interneurons and astrocytes that interferes with Hedgehog induction of glial derived-neurotrophic factor (GDNF) transcription. This is not exacerbated in double mutant LRRK2 and PINK1 mice. Overall, our analysis indicates that LRRK2 activation and/or loss of PINK1 function along parallel pathways to impair ciliogenesis, suggesting a convergent mechanism towards PD. Our data suggests that reversal of defects downstream of ciliogenesis offers a common therapeutic strategy for LRRK2 or PINK1 PD patients whereas LRRK2 inhibitors that are currently in clinical trials are unlikely to benefit PINK1 PD patients.
Decoding Protein Aggregation through Computational Approach: Identification and Scoring of Aggregation-Prone Regions in Protein Sequences
Authors: Kaushik Rahul , Launey Thomas 
Published: June 2024

AbstractProtein aggregation is a critical phenomenon associated with numerous neurodegenerative and systemic diseases. Understanding the propensity of proteins to aggregate is essential for unraveling the molecular basis of these disorders and for design and engineering of novel proteins or modulating the activity/stability of enzymatic proteins. Here, we present APR-Score, a novel machine-learning based computational method designed to identify aggregation-prone regions within protein sequences. ARP-Score leverages a combination of sequence-based features to predict regions of proteins that are prone to aggregate. The APR-Score harnessed the information ingrained in the compiled sequence and structural features to provide state-of-the-art accuracy. The APR-Score is assessed by conducting rigorous cross-validation experiments on the training dataset and further validated on an independent test dataset. The APR-Score prediction models demonstrated robustness and reliability in discriminating aggregation-prone regions from non-aggregating ones on an independent dataset, achieving Mathew’s correlation coefficient (MCC) 0.81, precision 0.89, and F1-Score 0.91. The APR-Score offers a valuable tool for researchers investigating protein aggregation-related diseases, as it can expedite the identification of aggregation-prone regions, aiding in the development of targeted therapies and diagnostic tools. The computational protein design and engineering regimes can be facilitated through APR-Score based identification and screening of aggregation prone protein sequences.
SETD8 inhibition targets cancer cells with increased rates of ribosome biogenesis
Authors: Murga Matilde , Lopez-Pernas Gema , Soliva Robert , Fueyo-Marcos Elena , Amor Corina , Faustino Ignacio , Serna Marina , Serrano Alicia G. , Díaz Lucía , Martínez Sonia , Blanco-Aparicio Carmen , Antón Marta Elena , Seashore-Ludlow Brinton , Pastor Joaquín , Jafari Rozbeh , Lafarga Miguel , Llorca Oscar , Orozco Modesto , Fernández-Capetillo Oscar 
Published: June 2024

SUMMARYSETD8 is a methyltransferase that is overexpressed in several cancers, which monomethylates H4K20 as well as other non-histone targets such as PCNA or p53. We here report novel SETD8 inhibitors, which were discovered while trying to identify chemicals that prevent 53BP1 foci formation, an event mediated by H4K20 methylation. Consistent with previous reports, SETD8 inhibitors induce p53 expression, although they are equally toxic for p53-deficient cells. Thermal stability proteomics revealed that the compounds had a particular impact on nucleoli, which was confirmed by fluorescent and electron microscopy. Similarly,Setd8deletion generated nucleolar stress and impaired ribosome biogenesis, confirming that this was an on-target effect of SETD8 inhibitors. Furthermore, a genome-wide CRISPR screen identified an enrichment of nucleolar factors among those modulating the toxicity of SETD8 inhibitors. Accordingly, the toxicity of SETD8 inhibitors correlated with MYC or mTOR activity, key regulators of ribosome biogenesis. Together, our study provides a new class of SETD8 inhibitors and a novel biomarker to identify tumors most likely to respond to this therapy.
Modulation of beta oscillatory dynamics in motor and frontal areas during physical fatigue
Authors: Matta Pierre-Marie , Baurès Robin , Duclay Julien , Alamia Andrea 
Published: June 2024

AbstractBeta-band oscillations have been suggested to promote the maintenance of the current motor (or cognitive) set, thus signaling the ‘status quo’ of the system. While this hypothesis has been reliably demonstrated in many studies, it fails to explain changes in beta-band activity due to the accumulation of physical fatigue. In the current study, we aimed to reconcile the functional role of beta oscillations during physical fatigue within the status quo theory. Using an innovative EEG design, we identified two distinct beta-band power dynamics in the motor areas as fatigue rises: (i) an enhancement at rest, supposedly promoting the resting state, and (ii) a decrease during contraction, thought to reflect the increase in motor cortex activation necessary to cope with the muscular fatigue. We then conducted effective connectivity analyses, which revealed that the modulations during contractions were driven by frontal areas. Finally, we implement a biologically plausible model to replicate and characterize our results mechanistically. Together, our findings anchor the physical fatigue paradigm within the status quo theory, thus shedding light on the functional role of beta oscillations in physical fatigue. We further discuss a unified interpretation that might explain the conflicting evidence previously encountered in the physical fatigue literature.
Endothelial cell Piezo1 promotes vascular smooth muscle cell differentiation on large arteries
Authors: Abello Javier , Yin Ying , Zhao Yonghui , Maurer Josh , Lee Jihui , Bodell Cherokee , Clevenger Abigail J. , Burton Zarek , Goeckel Megan E. , Lin Michelle , Grainger Stephanie , Halabi Carmen M. , Raghavan Shreya A. , Sah Rajan , Stratman Amber N. 
Published: June 2024

AbstractVascular stabilization is a mechanosensitive process, in part driven by blood flow. Here, we demonstrate the involvement of the mechanosensitive ion channel, Piezo1, in promoting arterial accumulation of vascular smooth muscle cells (vSMCs) during zebrafish development. Using a series of small molecule antagonists or agonists to temporally regulate Piezo1 activity, we identified a role for the Piezo1 channel in regulatingklf2alevels and altered targeting of vSMCs between arteries and veins. Increasing Piezo1 activity suppressedklf2aand increased vSMC association with the cardinal vein, while inhibition of Piezo1 activity increasedklf2alevels and decreased vSMC association with arteries. We supported the small molecule data within vivogenetic suppression ofpiezo1and2in zebrafish, resulting in loss oftransgelin+vSMCs on the dorsal aorta. Further, endothelial cell (EC)-specificPiezo1knockout in mice was sufficient to decrease vSMC accumulation along the descending dorsal aorta during development, thus phenocopying our zebrafish data, and supporting functional conservation of Piezo1 in mammals. To determine mechanism, we usedin vitromodeling assays to demonstrate that differential sensing of pulsatile versus laminar flow forces across endothelial cells changes the expression of mural cell differentiation genes. Together, our findings suggest a crucial role for EC Piezo1 in sensing force within large arteries to mediate mural cell differentiation and stabilization of the arterial vasculature.
Brain Age Prediction: Deep Models Need a Hand to Generalize
Authors: Rajabli Reza , Soltaninejad Mahdie , Fonov Vladimir S. , Bzdok Danilo , Collins D. Louis 
Published: June 2024

AbstractPredicting brain age from T1-weighted MRI is a promising marker for understanding brain aging and its associated conditions. While deep learning models have shown success in reducing the Mean Absolute Error (MAE) of predicted brain age, concerns about robust and accurate generalization in new data limit their clinical applicability. The large number of trainable parameters, combined with limited medical imaging training data, contribute to this challenge, often resulting in a generalization gap where there is a significant discrepancy between model performance on training data versus unseen data.In this study, we assess a deep model, SFCN-reg, based on the VGG-16 architecture, and address the generalization gap through comprehensive preprocessing, extensive data augmentation, and model regularization. Using training data from the UK Biobank, we demonstrate substantial improvements in model performance. Specifically, our approach reduces the generalization MAE by 44% (from 5.25 to 2.96 years) in the Alzheimer’s Disease Neuroimaging Initiative dataset and by 22% (from 4.35 to 3.40 years) in the Australian Imaging, Biomarker and Lifestyle dataset. Furthermore, we achieve a 29% reduction in scan-rescan error (from 0.86 to 0.61 years) while enhancing the model’s robustness to registration errors. Feature importance maps highlight anatomical regions used to predict age.These results highlight the critical role of high-quality preprocessing and robust training techniques in improving accuracy and narrowing the generalization gap, both necessary steps towards the clinical use of brain age prediction models. Our study makes valuable contributions to neuroimaging research by offering a potential pathway to improve the clinical applicability of deep learning models.
Feasibility of Stereo EEG Based Brain Computer Interfacing in An Adult and Pediatric Cohort
Authors: Jensen Michael A , Schalk Gerwin , Ince Nuri , Hermes Dora , Brunner Peter , Miller Kai J 
Published: June 2024

ABSTRACTIntroductionStereoelectroencephalography (sEEG) is a mesoscale intracranial monitoring method which records from the brain volumetrically with depth electrodes. Implementation of sEEG in BCI has not been well-described across a diverse patient cohort.MethodsAcross eighteen subjects, channels with high frequency broadband (HFB, 65-115Hz) power increases during hand, tongue, or foot movements during a motor screening task were provided real-time feedback based on these HFB power changes to control a cursor on a screen.ResultsSeventeen subjects established successful control of the overt motor BCI, but only nine were able to control imagery BCI with≥80% accuracy. In successful imagery BCI, HFB power in the two target conditions separated into distinct subpopulations, which appear to engage unique subnetworks of the motor cortex compared to cued movement or imagery alone.ConclusionsEEG-based motor BCI utilizing overt movement and kinesthetic imagery is robust across patient ages and cortical regions with substantial differences in learning proficiency between real or imagined movement.
Emulating
ab initio
computations of infinite nucleonic matter
Authors: Jiang W. G. , Forssén C. , Djärv T. , Hagen G. 
Published: June 2024

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for >106 different parametrizations of a chiral interaction model with explicit Δ-isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He4, we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties.

Published by the American Physical Society
2024
Probing bosonic overdensities with optomechanical sensing
Authors: Slattery Katherine , Wijewardhana Rohana , Eby Joshua , Street Lauren 
Published: June 2024

Previous work has shown that optomechanical force sensing can be used for efficient detection of ultralight (sub-eV) dark matter candidates. We propose to extend the reach of this method to the search for ultralight dark matter in gravitationally bound configurations in the Milky Way. We consider three scenarios, each strongly motivated by previous studies: boson stars traveling in the galaxy with virial velocity; a bosonic halo centered around the Sun (a “solar halo”); and a bosonic halo centered around the Earth. For each case, we consider bound states composed of either scalar particles with a Yukawa coupling, or vector particles coupled to baryon minus lepton number charge. Accounting for all experimental constraints on coupling strength, we estimate the sensitivity reach of an optomechanical sensor search. We conclude that, although boson star encounters with Earth would be too infrequent to be detected in the relevant parameter space, current optomechanical force sensing technologies provide promising search capabilities for solar or Earth-bound halos.

Published by the American Physical Society
2024
A composite indicator-based energy-efficiency benchmarking for residential buildings
Authors: Gupta Gyanesh , Mathur Sanjay , Mathur Jyotirmay 
Published: June 2024

PurposeBuildings require significant energy, and meeting energy demands is becoming exceedingly challenging. Energy demand reduction goals are now prioritised as the demand is rising. Energy-saving improvements and opportunities can be provided if enough information is provided through building energy benchmarking. The study focuses on developing a framework for benchmarking the energy efficiency of residential buildings.Design/methodology/approachThis study applied multiple linear regression analysis to analyse the energy use of residential buildings and establish energy benchmarks. Over 2000 data from Jaipur city were surveyed, and regression analysis was done on 1527 datasets after fundamental statistical analysis. The research considered the significant energy used by household appliances and placed a greater emphasis on end-use appliances.FindingsThe comparison of the developed framework with the standard rating plan was carried out to evaluate the accuracy of the benchmarks. The validation of the model determines the gap between the predicted and actual value of the building energy. The recommendations were made for organisations and policymakers to employ multiple or combinations of methods to assess the reliability of the developed benchmark framework.Practical implicationsPolicymakers may promote awareness campaigns encouraging homeowners to consume less energy and make buildings more energy efficient. This technique may be applied worldwide with the proper and suitable adjustments and information provided.Originality/valueTo our knowledge, India needs residential building energy benchmarking framework studies. In addition, a new framework based on Composite Indicators was implemented to overcome the scepticism of the EPI/BPI or floor-based approach held by several academics and to offer energy benchmarking for residential buildings.
“Nudging towards excellence: Harnessing behavioral insights for organizational learning”
Authors: Arya Jyoti , Hindolia Anand 
Published: June 2024

Purpose
In dynamic business environments, organizations must constantly adapt and learn. Nudging, a concept from behavioral economics, offers a novel approach to influence organizational behavior and learning. This article explores the integration of nudging within organizational learning, drawing from Thaler and Sunstein’s work and organizational learning theories. Also, To investigate nudging’s role in organizational learning and propose a practical nudging framework, while addressing ethical considerations.

Design/methodology/approach
The article combines theoretical insights from behavioral economics (Thaler and Sunstein; Kahneman) with organizational learning theories (Argyris and Schön). It discusses real-world nudging applications, like Google's health initiatives, and examines the ethical aspects of workplace nudging.

Findings
Nudging effectively influences organizational decisions and strategies by targeting rapid cognitive processes. It finds application in training, performance management, and decision-making, with a critical focus on ethical implications, especially regarding autonomy and non-manipulation.

Research limitations/implications
This study highlights the potential of behavioral economics in reshaping organizational learning, emphasizing the importance of ethical application in developing adaptive, learning-focused organizational cultures.

Originality/value
Nudging offers a promising method for enhancing organizational learning. Applied ethically, it can improve workforce engagement, performance, and adaptability. Future research should focus on nudging's long-term organizational impacts and ethical boundaries.
Tensions in data use for mission: academic data within holistic education
Authors: Jones Mary F. , Dallavis Julie 
Published: June 2024

PurposeResearch shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders’ data use toward such outcomes, particularly in the Catholic school context.Design/methodology/approachThis qualitative interview study uses interview (n = 23) data from a sample of Catholic school leaders to unpack how they conceptualize data, the motivations encouraging their data use and the challenges inhibiting data routines.FindingsCatholic school leaders largely shared a narrow definition of data as quantitative, standardized achievement data, were motivated by a moral imperative to meet students’ needs and faced several common challenges, including time constraints, uncertainty in measurement, limited capacity and resources and issues of turnover at the classroom and school levels.Practical implicationsSchool leaders can assuage tension around data by broadening the scope of measures and appealing to teachers’ sense of personal responsibility and commitment to students.Originality/valueThese findings extend the research in three ways. They bring to light an important tension between data-informed practice and a whole child approach to education, highlight the possibility of motivating data use through conscience rather than compliance and provide insight into data perceptions in private schools, an understudied context in the literature.
Social media’s sway: how social comparison on social media stimulates impulse travelling; serial mediation study on Indian millennials tourists
Authors: Kumar Satinder , Kumar Sandeep 
Published: June 2024

PurposeThe study explores the impact of social media-induced social comparison on impulse travelling, drawing upon social comparison theory. It thoroughly examines the intermediary functions of fear of missing out (FoMO) and compulsive use of social media, alongside exploring the moderating impacts of self-esteem and self-control within this dynamic process.Design/methodology/approachTo meet the objective, we conducted a survey of 382 social media users among Indian millennial tourists. The analysis has been done using SPSS (AMOS 24) and Process macro (model 1) for moderation effect. Purposive and snowball sampling techniques have been employed for data collection.FindingsThe results indicate a positive influence of social comparison on impulsive travel. Additionally, the findings suggest that FoMO and the compulsive use of social media serve as serial mediations on the link between social comparison and impulse travelling. Moreover, self-esteem has shown a negatively significant relationship between social comparison and FoMO. Furthermore, self-control has also been found to have a negatively significant effect on the relationship between FoMO and the compulsive use of social media.Practical implicationsThe study’s findings offer valuable guidance for destination administrators. It suggests that administrators should refrain from engaging in aggressive and overly tailored marketing tactics. Instead, they should focus on sharing real and authentic stories that resonate with travellers, and administrators can mitigate the effects of social comparison and discourage impulsive travelling.Originality/valueThis study delves into an unexplored realm in digital marketing literature, shedding light on how social comparison on social media influences the impulsive travelling of Indian millennial tourists. This study is an inaugural attempt to formulate a theoretical framework within the scope of the tourism sector.
The role of AI agents in fostering inclusivity for HEIs’ students with special needs against backdrops of the accreditation trend
Authors: Chedrawi Charbel , Kazoun Nahil , Kokkinaki Angelika 
Published: June 2024

Purpose
This paper aims to study the role of artificial intelligence (AI) agents in creating a climate of inclusion for people with special needs in the higher education sector (HES).

Design/methodology/approach
A qualitative methodology is used in this research that is mainly based on semistructured interviews conducted with the top ten universities in Lebanon with deans, information technology managers, professors and administrative officers.

Findings
This paper highlights findings related to the current status of the higher education institutions (HEIs) in Lebanon vis-à-vis their accreditation and quality assurance processes in accommodating and creating a climate of inclusion for people with special needs. The results show the important role of AI agents in aiding HEI in creating such a climate of inclusion for people with special needs.

Originality/value
The study sheds light on existing gaps in the literature related to creating a climate of inclusion for people with special needs in HEI. Additionally, there is yet a lack of research that focuses on the role of AI technology in general and AI agents in particular in fostering a climate of inclusion for people with special needs within the HES.