bluuebunny/crossref_metadata_2025_split huggingface dataset:
Varieties of engagement: exploring the micro-practices of managers in employing disadvantaged jobseekers
Authors: Aksnes Siri Yde , Breit Eric 
Published: February 2025

Abstract
Despite the increased emphasis on ‘employer engagement’ to take advantage of demand-side active labour market policies, little attention has been paid to managers. In this paper, we examine the micro-practices of engaged managers in including jobseekers from disadvantaged groups. Through a qualitative study of managers, jobseekers and other stakeholders in twenty-one companies with a history of employing disadvantaged jobseekers, we identify three broad types of engagement by managers: vacancy-oriented, ability-oriented, and growth-oriented. The types of engagement involve crucial differences in motivation, caring and accommodation on the part of the employing managers. Our findings highlight the multi-facetedness of employer engagement when examined from the perspective of managers and propose ‘inclusive leadership’ as a useful lens to understand engaged employers.
State violence against migrant women: Ontological security, threat, and legitimacy
Authors: Innes Alexandria 
Published: February 2025

Abstract
This research examines the ways the hostile environment in the UK utilises domestic violence as a deterrent measure, weaponising this endemic form of interpersonal violence against migrant women. I argue that the state’s own processes of accountability and responsibility for domestic violence fatalities, and the active exclusion of migrant women from state-provided services that are key in intervening in cases of domestic violence, are sufficient for domestic violence against migrant women to be constituted as state violence. I frame this in the context of what an ontological security approach can offer to our understanding of the multiplicity of encounters and experiences that migrant women have with a state apparatus that is designed to offer both security and accountability to address the particularly gendered insecurity of domestic violence. The active exclusion of migrant women from these monitoring mechanisms embeds both an affective and a very real empirical insecurity in the lives of migrant women. This ontological insecurity is both inside and outside of state, making ontological security for some while unmaking it for others.
Circadian disruption by simulated shift work aggravates periodontitis via orchestrating BMAL1 and GSDMD-mediated pyroptosis
Authors: Wang Yazheng , Li Rui , Ye Qingyuan , Fei Dongdong , Zhang Xige , Huang Junling , Liu Tingjie , Wang Jinjin , Wang Qintao 
Published: February 2025

Abstract
Approximately 20% to 30% of the global workforce is engaged in shift work. As a significant cause of circadian disruption, shift work is closely associated with an increased risk for periodontitis. Nevertheless, how shift work-related circadian disruption functions in periodontitis remains unknown. Herein, we employed a simulated shift work model constructed by controlling the environmental light-dark cycles and revealed that shift work-related circadian disruption exacerbated the progression of experimental periodontitis. RNA sequencing and in vitro experiments indicated that downregulation of the core circadian protein brain and muscle ARNT-like protein 1 (BMAL1) and activation of the Gasdermin D (GSDMD)-mediated pyroptosis were involved in the pathogenesis of that. Mechanically, BMAL1 regulated GSDMD-mediated pyroptosis by suppressing NOD-like receptor protein 3 (NLRP3) inflammasome signaling through modulating nuclear receptor subfamily 1 group D member 1 (NR1D1), and inhibiting Gsdmd transcription via directly binding to the E-box elements in its promoter. GSDMD-mediated pyroptosis accelerated periodontitis progression, whereas downregulated BMAL1 under circadian disruption further aggravated periodontal destruction by increasing GSDMD activity. And restoring the level of BMAL1 by circadian recovery and SR8278 injection alleviated simulated shift work-exacerbated periodontitis via lessening GSDMD-mediated pyroptosis. These findings provide new evidence and potential interventional targets for circadian disruption-accelerated periodontitis.
Bifidobacterium animalis subsp. lactis A6 ameliorates bone and muscle loss via modulating gut microbiota composition and enhancing butyrate production
Authors: Chen Ming , Li Yi , Zhai Zhengyuan , Wang Hui , Lin Yuan , Chang Feifan , Ge Siliang , Sun Xinyu , Wei Wei , Wang Duanyang , Zhang Mingming , Chen Ruijing , Yu Haikuan , Feng Taojin , Huang Xiang , Cheng Dongliang , Liu Jiang , Di Wenxuan , Hao Yanling , Yin Pengbin , Tang Peifu 
Published: February 2025

Abstract
Systematic bone and muscle loss is a complex metabolic disease, which is frequently linked to gut dysfunction, yet its etiology and treatment remain elusive. While probiotics show promise in managing diseases through microbiome modulation, their therapeutic impact on gut dysfunction-induced bone and muscle loss remains to be elucidated. Employing dextran sulfate sodium (DSS)-induced gut dysfunction model and wide-spectrum antibiotics (ABX)-treated mice model, our study revealed that gut dysfunction instigates muscle and bone loss, accompanied by microbial imbalances. Importantly, Bifidobacterium animalis subsp. lactis A6 (B. lactis A6) administration significantly ameliorated muscle and bone loss by modulating gut microbiota composition and enhancing butyrate-producing bacteria. This intervention effectively restored depleted butyrate levels in serum, muscle, and bone tissues caused by gut dysfunction. Furthermore, butyrate supplementation mitigated musculoskeletal loss by repairing the damaged intestinal barrier and enriching beneficial butyrate-producing bacteria. Importantly, butyrate inhibited the NF-κB pathway activation, and reduced the secretion of corresponding inflammatory factors in T cells. Our study highlights the critical role of dysbiosis in gut dysfunction-induced musculoskeletal loss and underscores the therapeutic potential of B. lactis A6. These discoveries offer new microbiome directions for translational and clinical research, providing promising strategies for preventing and managing musculoskeletal diseases.
Targeting Chk1 and Wee1 kinases enhances radiosensitivity of 2D and 3D head and neck cancer models to X-rays and low/high-LET protons
Authors: Melia Emma , Fisch Anne-Sophie , Tinhofer Ingeborg , Parsons Jason L. 
Published: February 2025

Abstract
Ionising radiation causes the introduction of DNA damage, more specifically double strand breaks (DSBs) and complex DNA damage (CDD), that induces cancer cell death leading to the therapeutic effect. To combat this, cells activate arrest at the G2/M checkpoint to allow for effective DNA damage repair, coordinated by the Chk1 and Wee1 protein kinases. Therefore, Chk1 and Wee1 are considered promising therapeutic targets to enhance the effectiveness of radiotherapy in cancer cell killing. Here, we have analysed the response of head and neck squamous cell carcinoma (HNSCC) cell lines, spheroids and patient-derived organoids to X-rays and proton beam therapy (PBT) in the presence of either a Chk1 (MK-8776) or a Wee1 (MK-1775) inhibitor. We demonstrate that inhibitors of Chk1 or Wee1 can significantly enhance the radiosensitivity of both 2D and 3D models of HNSCC to X-rays and PBT (performed at both low and high ionisation densities), and that this effect is caused through abrogation of the G2/M checkpoint causing the persistence of DSBs. Our results therefore suggest that targeting Chk1 and Wee1 kinases in combination with X-rays and PBT could represent a promising therapeutic avenue to enhance the clinical efficacy of HNSCC treatment.
Historical loss weakens competitive behavior by remodeling ventral hippocampal dynamics
Authors: Lai Chuan , Chen Kai , Huang He-Zhou , Huang Xian , Zhang Juan , Wang Yu-Bo , Chen Zhiye , Hu Feng , Guo Ziyuan , Man Heng-Ye , Du Hui-Yun , Lu You-Ming , Shu Kai , Liu Dan , Zhu Ling-Qiang 
Published: February 2025

Abstract
Competitive interactions are pervasive within biological populations, where individuals engage in fierce disputes over vital resources for survival. Before the establishment of a social hierarchy within the population, this competition becomes even more intense. Historical experiences of competition significantly influence the competitive performance; individuals with a history of persistent loss are less likely to initiate attacks or win escalated contests. However, it remains unclear how historical loss directly affects the evolution of mental processes during competition and alters responses to ongoing competitive events. Here, we utilized a naturalistic food competition paradigm to track the competitive patterns of mutually unfamiliar competitors and found that a history of loss leads to reduced competitive performance. By tracking the activity of ventral hippocampal neuron ensembles, we identified clusters of neurons that responded differently to behavioral events during the competition, with their reactivity modulated by previous losses. Using a Recurrent Switch Linear Dynamical System (rSLDS), we revealed rotational dynamics in the ventral hippocampus (vHPC) during food competition, where different discrete internal states corresponded to different behavioral strategies. Moreover, historical loss modulates competitive behavior by remodeling the characteristic attributes of this rotational dynamic system. Finally, we found that an evolutionarily conserved glutamate receptor-associated protein, glutamate receptor-associated protein 1 (Grina), plays an important role in this process. By continuously monitoring the association between the attributes of the dynamic system and competitiveness, we found that restoring Grina expression effectively reversed the impact of historical loss on competitive performance. Together, our study reveals the rotational dynamics in the ventral hippocampus during competition and elucidates the underlying mechanisms through which historical loss shapes these processes.
A single-cell atlas to map sex-specific gene-expression changes in blood upon neurodegeneration
Authors: Grandke Friederike , Fehlmann Tobias , Kern Fabian , Gate David M. , Wolff Tobias William , Leventhal Olivia , Channappa Divya , Hirsch Pascal , Wilson Edward N. , Meese Eckart , Liu Chuanyu , Shi Quan , Flotho Matthias , Li Yongping , Chen Cynthia , Yu Yeya , Xu Jiangshan , Junkin Michael , Wang Zhifeng , Wu Tao , Liu Longqi , Hou Yong , Andreasson Katrin I. , Gansen Jenny S. , Mass Elvira , Poston Kathleen , Wyss-Coray Tony , Keller Andreas 
Published: February 2025

Abstract
The clinical course and treatment of neurodegenerative disease are complicated by immune-system interference and chronic inflammatory processes, which remain incompletely understood. Mapping immune signatures in larger human cohorts through single-cell gene expression profiling supports our understanding of observed peripheral changes in neurodegeneration. Here, we employ single-cell gene expression profiling of over 909k peripheral blood mononuclear cells (PBMCs) from 121 healthy individuals, 48 patients with mild cognitive impairment (MCI), 46 with Parkinson’s disease (PD), 27 with Alzheimer’s disease (AD), and 15 with both PD and MCI. The dataset is interactively accessible through a freely available website (https://www.ccb.uni-saarland.de/adrcsc). In this work, we identify disease-associated changes in blood cell type composition and the gene expression in a sex-specific manner, offering insights into peripheral and solid tissue signatures in AD and PD.
On opportunities and challenges of large multimodal foundation models in education
Authors: Küchemann Stefan , Avila Karina E. , Dinc Yavuz , Hortmann Chiara , Revenga Natalia , Ruf Verena , Stausberg Niklas , Steinert Steffen , Fischer Frank , Fischer Martin , Kasneci Enkelejda , Kasneci Gjergji , Kuhr Thomas , Kutyniok Gitta , Malone Sarah , Sailer Michael , Schmidt Albrecht , Stadler Matthias , Weller Jochen , Kuhn Jochen 
Published: February 2025

Abstract
Recently, the option to use large language models as a middleware connecting various AI tools and other large language models led to the development of so-called large multimodal foundation models, which have the power to process spoken text, music, images and videos. In this overview, we explain a new set of opportunities and challenges that arise from the integration of large multimodal foundation models in education.
An eye-movement database of bilingual language control for Chinese-English bilinguals
Authors: Wang Tao , Wang Yue , Hu Haibo , Wang Xing , Chen Shengdong , Yang Yiming 
Published: February 2025

Abstract
The current absence of an eye-tracking database that explores bilingual language control and how intra-sentence code-switching types influence the language control process limits our deeper understanding of bilingual control mechanisms. To address this issue, we present a database containing eye-movement recordings collected during a silent reading task combined with language switching paradigm. The database contains typical measures of eye movement data of 160 Chinese and their translation equivalent English words from 40 high-proficient and 40 low-proficient participants across 1280 Chinese, English and intra-sentential code-switching sentences. This database enables researchers to test the impacts of both intra-sentential code-switching and the second language proficiency on bilingual language control and the underlying cognitive mechanisms.
Deep learning-based debris flow hazard detection and recognition system: a case study
Authors: Wu Fei , Zhang Jianlin , Liu Dunlong , Maier Andreas , Christlein Vincent 
Published: February 2025

Abstract
Debris flows are characterized by their suddenness, rapidity, large scale and destructive power, causing serious threat to the population in mountainous areas. Surveillance cameras are widely used in geological hazard monitoring and early warning projects. So far, video cameras are used as a passive tool for post inspection and not as an active role for debris flow monitoring and early warning. Inspired by recent developments of anomaly detection in the field of computer vision, in this paper, we propose a novel automatic debris flow detection and recognition system based on deep learning. It consists of a video feature extraction network using a 3D convolutional neural network (CNN), a debris flow hazard detection network using a multi-layer perceptron (MLP), and a debris flow hazard recognition network for verification employing another CNN. The proposed system takes the video sequences captured by the cameras as inputs and enables the detection and recognition of debris flow hazards. All the networks are optimized and evaluated on a newly annotated image dataset called Debrisflow23. Extensive experimental evaluations with a detection accuracy of 86.3 % AUC, a recognition accuracy of 83.7 % AUC, and an overall identification accuracy of 88.1 % AUC on the test dataset demonstrate that the proposed method possesses accurate and reliable debris flow warning capability. Thus, further precautions can be taken in advance to reduce the damage to human settlements and infrastructure caused by debris flows.
Multitarget mechanism of MYC inhibition by the bacterial lon protease in disease
Authors: Ambite Ines , Wan Murphy Lam Yim , Tran Hien Thi , Nazari Atefeh , Chaudhuri Arunima , Krintel Christian , Gomes Inês , Sabari Samudra , Ahmadi Shahram , Carneiro António N. B. M. , Ishac Rita , Haq Farhan , Svanborg Catharina 
Published: February 2025

Abstract
Identifying specific inhibitors of the MYC oncogene has been challenging, due to off target effects associated with MYC inhibition. This study investigated how the recombinant Escherichia coli Lon protease (rLon), which targets MYC in human cells, inhibits MYC over-activation in models of infection and cancer. In silico predictions identified specific peptide domains of bacterial Lon that target MYC and the affinity of these peptides for MYC was investigated by surface plasmon resonance. The N-terminal domain of rLon was shown to interact with the C-terminal, leucine zipper domain of MYC and MAX and to prevent MYC/MAX dimerization. Furthermore, rLon targeted and degraded c-MYC in vitro and in cellular models, through the peptidase domain. In a model of kidney infection, rLon treatment prevented, c-MYC, N-MYC and L-MYC over-expression, MYC-dependent gene expression, specifically renal toxicity genes and pathology, suggesting that rLon recognizes and corrects MYC dysregulation in this disease. The findings describe a multitarget mechanism of MYC inhibition by rLon, and the combined effects achieved by the Lon domains, targeting different MYC epitopes and MYC-dependent functions, with no evidence of toxicity or detrimental effects on homeostatic MYC expression.
Eyes and movement differences in unconscious state during microscopic procedures
Authors: Fujita Akiko , Oyama Shintaro , Tatebe Masahiro , Shimoda Shingo , Tokutake Katsuhiro , Yamamoto Michiro , Hirata Hitoshi 
Published: February 2025

Abstract
Microsurgery is one of the techniques that is increasingly being adopted in many surgical fields. However, the acquisition and transfer of microsurgical skills primarily depend on experience. Additionally, opportunities to improve microsurgical skills are limited and a uniform evaluation system is lacking. Therefore, the aim of this study was to understand the physical characteristics of experienced and novice surgeons and to propose efficient training and evaluation methods from an educational perspective. In this study, nine hand surgeons and six orthopedic surgeons were included in expert group E and novice group N, respectively. An eye tracker and surface electromyography were used. They were asked to perform the suturing procedure under the same conditions. The viewpoint distribution area was larger in group N than in group E (p < 0.01). In group E, the pupil diameter increased only in a limited phase. The standard deviation of the distance between gaze and hand movements was smaller in group E, especially for gaze. Group E used the synergy of the same muscles to create movement. This study showed that there are differences in eye movements and unconscious body control during suturing techniques under the microscope between experienced users and novices.
Developing a dynamic combined power quality index for assessing the performance of a nuclear facility
Authors: Elsotohy Asmaa M. , Ali Mohammed Hamouda , Adail Ahmed S. , Eisa Ayman A. , Othman El-said A 
Published: February 2025

Abstract
Studying and evaluating the power quality (PQ) of an electrical network for nuclear installation is an important issue and a hot research topic for guaranteeing reliable and safe operation of sensitive electrical loads during this type of installation. As several PQ phenomena determine the overall PQ performance, analyzing PQ signals for evaluating the overall PQ is one of the major challenges for researchers in this field. Technically, voltage imbalance, current imbalance, voltage harmonic distortion, current harmonic distortion, and the power factor are five important PQ phenomena that judge the overall PQ performance of an electrical system. Multicriteria decision-making (MCDM) is used here as a methodology to identify a weighting for each PQ phenomenon. This paper proposes a power quality evaluation method for a nuclear research reactor (NRR) electrical network based on two MCDM. Methods the analytic hierarchy process (AHP) and criterion importance through inter-criteria correlation (CRITIC). A MATLAB/Simulink model for the NRR electrical system is presented, and then its validity and credibility are verified via measurements. In this study, different abnormal conditions are simulated in the NRR network to generate power quality disturbances, including a three-phase nonlinear load to simulate harmonics, an unbalanced load to simulate unbalance, and an inductive load to simulate the change in the power factor. The effectiveness and robustness of the proposed methodology are demonstrated through these different case studies. The results show that the obtained CPQI based on the dynamic weight approach allows for more accurate evaluations by adjusting the importance of various PQ phenomena depending on operational conditions and priorities. The main contribution of this paper is that a single compound power quality index (CPQI) was developed based on both the dynamic weights obtained from AHP-CRITIC methods and the results of the five PQ phenomena obtained under different abnormal conditions, considering the threshold level for each of these PQ phenomena. The analysis of the obtained results shows that this method accurately evaluates the overall PQ performance.
Characterization of a mock up nuclear waste package using energy resolved MeV neutron analysis
Authors: Jäger Tim T. , Hirsh Tsviki Y. , Scheuren Stefan , Long Alexander M. , Losko Adrian S. , Wolfertz Alexander , Zimmer Marc , Roth Markus , Vogel Sven C. 
Published: February 2025

Abstract
Reliable radiographic methods for characterizing nuclear waste packages non-destructively (without the need to open containers) have the potential to significantly contribute to safe handling and future disposal options, particularly for legacy waste of unknown content. Due to required shielding of waste containers and the need to characterize materials consisting of light elements, X-ray methods are not suitable. Here, energy-resolved MeV neutron radiography is demonstrated as a first-of-its-kind application for non-destructive and remote examination of mock up nuclear waste packages from a safe position using time-of-flight techniques enabled by a novel event-mode imaging detector system. Energy-resolved neutron transmission spectra were measured spatially, permitting the detection of analogue materials to actual nuclear waste such as water, melamine, and ion exchange resin within a 2.54 cm wall thickness steel pipe. The results demonstrate the capability to locate the materials through this wall thickness by radiography and tomographic reconstruction, revealing detailed 3D distributions and structural anomalies. The method effectively detects residual water in ion exchange resin, highlighting its sensitivity to moisture content, a crucial parameter for nuclear waste characterization. Monte Carlo simulations are in agreement with the experimental findings, providing a pathway to simulate waste forms more difficult to tackle experimentally. This work paves the way to apply sub-nanosecond intense MeV neutron sources, such as laser-driven neutron sources under development, to nuclear waste characterization.