bluuebunny/crossref_metadata_2025 huggingface dataset:
In-situ evaluation of hole quality and cutting tool condition in robotic drilling of composite materials using machine learning
Authors: Lee Stephen K. H. , Mongan Patrick G. , Farhadi Ahmad , Hinchy Eoin P. , O’Dowd Noel P. , McCarthy Conor T.
Published: January 2025

The massive adoption of industrial robots in the manufacturing sector has significantly increased automation of installation and inspection procedures, particularly benefiting the aerospace industry, where large volumes of holes are drilled in each aircraft. However, mechanical drilling remains challenging when dealing with composite materials due to their inherently heterogeneous structure. This work presents a novel approach for in-situ hole quality inspection utilising integrated sensor data of an industrial robotic drill, combined with a machine learning model. Additionally, a novel classification approach for evaluating hole quality is proposed. This study employed a KUKA industrial robot, fitted with a multifunctional end-effector, to drill holes in a composite material used in aerospace applications. An ensemble neural network (ENN) model, which combines an artificial neural network with a genetic algorithm, was used to assess the quality of these drilled holes. The model was specifically developed and tested on the machined holes to relate process input parameters and drilling torques to hole quality. The model predictions were validated with six unseen datasets, of which five were predicted accurately. A full factorial study of the process parameters was conducted using analysis of variance (ANOVA) to investigate the relationship between tool condition and drilling torque. The results of the ANOVA show that tool condition is the largest contributor to drilling torque. The method proposed in this work, which allows real-time monitoring of hole quality, has the potential to improve manufacturing productivity of drilled components while ensuring high-quality end products.
Tumor microenvironment noise-induced polarization: the main challenge in macrophages’ immunotherapy for cancer
Authors: Sierra Jesus , de León Ugo Avila-Ponce , Padilla-Longoria Pablo
Published: January 2025

Disturbance of epigenetic processes can lead to altered gene function and malignant cellular transformation. In particular, changes in the epigenetic landscape are a central topic in cancer biology. The initiation and progression of cancer are now recognized to involve both epigenetic and genetic alterations. In this paper, we study the epigenetic mechanism (related to the tumor microenvironment) responsible for increasing tumor-associated macrophages that promote the occurrence and metastasis of tumor cells, support tumor angiogenesis, inhibit T-cell-mediated anti-tumor immune response, and lead to tumor progression. We show that the tumor benefits from the macrophages’ high degree of plasticity and larger epigenetic basins corresponding to phenotypes that favor cancer development through a process that we call noise-induced polarization. Moreover, we propose a mechanism to promote the appropriate epigenetic stability for immunotherapies involving macrophages, which includes p53 and APR-246 (eprenetapopt). Our results show that a combination therapy may be necessary to ensure the proper epigenetic stability of macrophages, which otherwise will contribute to cancer progression. On the other hand, we conclude that macrophages may remain in the anti-tumoral state in types of cancer that exhibit less TP53 mutation, like colorectal cancer; in these cases, macrophages’ immunotherapy may be more suitable. We finally mention the relevance of the epigenetic potential (Waddington’s landscape) as the backbone for our study, which encapsulates the biological information of the system.
What is 4E cognitive science?
Authors: Alexander Cameron
Published: January 2025

The 4E approach in (philosophy of) cognitive science—based on ideas that the mind is embodied, embedded, extended, and enacted—is so diverse that it defies straightforward explanation. This paper considers the most ecumenical explanation of the extant concept of the 4E approach. Purported explanations of 4E based on contested definitions of cognition, contrasts with non-4E approaches, or essential and unifying features (including embodiment) either fail to capture the correct extension for the concept of 4E or lead to incoherence. The incoherence is generated by a failure to abide by several desiderata for non-revisionist conceptual explanations: informativeness, non-contentiousness, and identification of any unifying features if they exist. By contrast, a family resemblance conception of 4E constrained by ties of historical influence satisfies these desiderata. The 4E approach should be understood as a set of family resemblances of overlapping ideas, hypotheses, theories and conceptual frameworks about the mind, as well as methods for its study. The family resemblances span several dimensions, including but not limited to a rejection of dualism, non-representational explanations of the mind, phenomenological methods, the importance of embodiment, a dynamical systems perspective, and an evolutionary perspective on the mind. This family resemblance conception is complemented by a historical dimension: the concept of 4E cognitive science emerged in the period following the cognitive revolution of the 1950s. The advantages of this explanation are that it abides by the established use of ‘4E’, explains 4E’s apparent diversity, and warns against reductive explanations.
How can relational, decolonial and feminist approaches inform the EU bioeconomy?
Authors: Ramcilovic-Suominen Sabaheta , Giuntoli Jacopo , Oliver Tom , Mehta Lyla
Published: January 2025

In this commentary we argue that, to transform the bioeconomy sectors towards ecologically less harmful and socially fairer outcomes, the bioeconomy policy project must be questioned, re-politicised and fundamentally reframed and reinvented. We firstly identify some of the main root causes for continuity of extractivism and injustices in the bioeconomy policy and, more broadly, in the green transition (“Root causes of today’s socioecological crises and why they matter for the EU bioeconomy project” section). Secondly, we outline the largely neglected ideas and concerns emerging from relational, feminist and decolonial approaches and perspectives (“Moving beyond growth while enabling marginalised voices, knowledges, and practices that nurture web of life and wellbeing for all” section). Finally, we compile a list of 11 actions and 47 suggestions for decisionmakers, practitioners and academics to contemplate on how to  cocreate bioeconomies founded on ethics of care, relationality and socioecological justice. Ultimately, the aim is to reject socioecological domination, extractivism and exploitation and foster collective wellbeing for all beings, human and other-than-human.
Doping Engineering of Sodium Vanadium Fluorophosphates Cathodes for Sodium-Ion Batteries
Authors: Kim Rakyung , Hwang Minjun , Park Ho Seok
Published: January 2025

Sodium-ion batteries offer a promising alternative to lithium-ion batteries due to the abundance and low cost of sodium resources. Na3V2(PO4)2F3−y
O
y
(NVPFO
y
) stands out as a cathode material with high average operating potential (~ 3.9 V vs Na+/Na), fast Na⁺ transport, and strong structural stability (minimal volumetric strain of ~ 2%). This review addresses the structural characteristics and charge storage mechanisms of NVPFO
y
, focusing on charge compensation and Na⁺/vacancy ordering. It also discusses recent advances in lattice regulation and doping strategies to enhance electrochemical properties. Finally, we highlight challenges and future directions for practical applications, emphasizing the correlation between crystal structure and performance.
Structured mathematical modelling in an authentic scientific-engineering context
Authors: Kohen Zehavit
Published: January 2025

This study suggests the framing of structured mathematical modelling (MM) in an authentic scientific-engineering context. Taking a task design view, structure is maintained through inherent scaffolding for the dual purpose of preserving the authenticity of the extra-mathematical context and making the adaptations required to allow incorporation of the task into the duration of a regular lesson and within the full capacity of the curriculum. Participants were 23 secondary school novice mathematics teachers and two experts who possess extensive experience in MM task design. Research tools included a reflective diary filled in by the novice teachers throughout the design process, and a task design evaluation form that was filled in by the two expert designers. Both tools aimed at identifying MM task characteristics and the alignment of the designed structured MM tasks with the MM cycle phases. Findings show the presence of all the unique characteristics that underly a quality designed MM task, with relatively low presence of openness and high presence of accessibility and authenticity from the novice teachers’ point of view. The alignment with the MM cycle was further manifest in the designed tasks, with the validation phase as being less evident compared to the other MM phases. Theoretical and practical contributions are discussed in the paper, indicating the sequentially-oriented process by which the structured MM tasks scaffold students through the MM cycle.
Classroom data science: data and dataing for making sense of multivariate plant growth
Authors: Fry Kym
Published: January 2025

What is considered data and how it is communicated publicly is rapidly changing. Participation in society involves multiple opportunities to engage with complex statistical concepts in media, in personal health, and regarding climate change. Children also are engaging with evolving data types in social media interactions and in educational contexts where they are the data. Yet little time is spent in classrooms supporting children to explore and make their own data decisions about various data types. This study investigates the role that fourth graders’ use of graphing conventions played in supporting their conceptual development of: non-traditional data and dataing during one lesson. The author hopes to contribute a new perspective in conceptualising dataing as enculturating statistical practices around data that involves multiple features, to communicate key information, involving tools for engaging with statistics to communicate a story. In this case study, a video clip presented an entrance point in exploring multivariate data (multiple variables). Video observation and student graphs revealed insights into children’s data and dataing experiences and processes involved with multivariate data, supported by a classroom culture that valued statistical processes as a creative and meaningful, story-telling endeavour. When students were tasked with representing plant growth using a graph, displays included a wide range of variables such as patterns of leaf growth and qualitative stages of plant growth. Engaging with multivariate data in exploratory ways supported students in this study to play with graphing conventions, establishing local mathematical practices involving non-traditional data.
A scoping review of clinical decision support systems for child and adolescent mental health
Authors: Bertie Lizél-Antoinette , McDermott Emma A. , Quiroz Juan C. , Hudson Jennifer L.
Published: January 2025

This scoping review maps the literature on clinical decision support systems (CDSSs) that aid clinicians in treatment decision-making for youth mental health. The objectives were to identify CDSSs used in youth mental health services, as well as grade and evaluate these systems with regard to performance, usability, and clinical utility. Electronic databases were systematically searched for publications related to the development, implementation, or evaluation of clinical decision support systems. Identified CDSSs were grouped according to user setting (primary or mental health care) and three functional areas including screening and assessment, risk prediction, and treatment recommendation. We assessed and graded the systems based on phases of evaluation, as well as the level and direction of evidence. This review identified 10 CDSSs at various stages of development and implementation used across primary and mental health care settings. Of these, one CDSS is in development phase, four have been implemented, and five have evidence of post-implementation investigations. Outside of primary care settings, few CDSSs exist to support clinicians making clinical treatment decisions for youth mental health. Availability of CDSSs is limited and country-specific. In terms of functionality, successful implementation is evident in the functional area of screening and assessment, with more work required in the functional areas of risk prediction and treatment recommendation to assist clinicians in providing youth mental health care. There is potential for machine learning in developing these functional areas.
Early Detection of Alzheimer's Disease from MR Images Using Fine-Tuning Neighborhood Component Analysis and Convolutional Neural Networks
Authors: Özaltın Öznur
Published: January 2025

This study develops an automatic algorithm for detecting Alzheimer's disease (AD) using magnetic resonance imaging (MRI) through deep learning and feature selection techniques. It utilizes a dataset of 6400 MRI images from Kaggle, categorized into four classes. Initially, the study employs pretrained CNN architectures—DenseNet-201, MobileNet-v2, ResNet-18, ResNet-50, ResNet-101, and ShuffleNet—for classification using five fold cross-validation, with DenseNet-201 achieving the highest accuracy of 82.11%. Due to the dataset's size and imbalance, as well as the long training times, the study aims to create a more efficient algorithm. The CNNs are used as deep feature extractors from AD images, and the extracted features are reduced using a new fine-tuning neighborhood component analysis (FTNCA) algorithm, which minimizes loss and determines the optimal tolerance value. The essential features are then classified using various machine learning algorithms, including artificial neural network (ANN), K-nearest neighbor (KNN), Naïve Bayes, and support vector machine (SVM). Experimental results reveal that reducing the feature set from 2048 to 344 allows the ResNet-50-FTNCA-KNN model to achieve 100% accuracy, significantly enhancing AD detection. This approach will aid in the early diagnosis and treatment of AD patients.
The effect of caregiver mastery on the associations of depression, anxiety, caregiver burden, fear of disease progression with quality of life among children with solid tumors
Authors: Cheng Fangfang , Gao Rui , Zhu Huanhuan , Zhang Yu , Xiong Hui , Meng Yingtao
Published: January 2025

Objectives

Caring for children with solid tumors (STs) can impact caregiver’s physical and mental health. Caregiver mastery, which influences psychological well-being, is vital in improving outcomes for both caregivers and children. The study aimed to investigate the relationship between caregiver mastery, anxiety, depression, fear of disease progression (FoP), caregiver burden, and the quality of life (QOL) of children with ST.

Methods

This cross-sectional study was conducted from June 2022 to April 2023 at a Grade A tertiary hospital in Shandong. Family caregivers of children with ST completed several validated measures, including the Pediatric Quality of Life Inventory (PedsQL) 3.0 Cancer Module, the Fear of Progression Questionnaire-parent version (FoP-Q-SF/PR), the Zarit Burden Interview Scale (ZBI), the hospital anxiety and depression scale (HADS), and the Caregiver Mastery Scale. Multiple linear regression analyses assessed the relationships between FoP, caregiver burden, anxiety, depression, caregiver mastery, and children’s QOL. Results were expressed as β and 95% confidence intervals (CIs).

Results

A total of 454 caregivers participated. Caregiver mastery was positively correlated with children’s QOL (β = 0.80, 95% CI: 0.20 to 1.39). Depression (β = −0.64, 95% CI: −0.83 to −0.45), anxiety (β = −0.67, 95% CI: −0.85 to −0.49), caregiver burden (β = −1.20, 95% CI: −1.60 to −0.80), and FoP (β = −0.04, 95% CI: −0.05 to −0.03) were negatively related to children’s QOL. Caregiver mastery moderated the associations between depression, caregiver burden, FoP, and children’s QOL, while also improving the effect of mild anxiety on QOL.

Significance of results

The study underscores the importance of fostering caregiver mastery to mitigate the negative impact of caregiver distress on children’s QOL and improve outcomes for both caregivers and children with solid tumors.

Conclusion

Caregiver mastery moderates the effects of anxiety, depression, FoP, and caregiver burdenon children’s QOL. Supporting caregiver mastery can alleviate caregiver burden and enhance both caregiver and child well-being.
Exploring the Influence of Morphologic Heterogeneity and Discharge on Transient Storage in Stream Systems: 1. Insights From the Field
Authors: Gambill Ian , Marshall Anna , Benson David A. , McFadden Sawyer , Navarre‐Sitchler Alexis , Wohl Ellen , Singha Kamini
Published: January 2025

Here, we explore how differences in morphologic heterogeneity due to logjams and secondary channels drive transient storage across discharge in two stream reaches within the Front Range of Colorado, USA. During three tracer tests conducted from baseflow to near‐peak snowmelt, we collected instream fluid conductivity measurements and conducted electrical resistivity surveys to characterize tracer movement in the surface and subsurface of the stream system. The reach with two logjams and an intermittent secondary channel exhibited greater heterogeneity in surface transient storage, driving heterogeneity in hyporheic exchange flows, compared to the reach with a single logjam and a perennial secondary channel. As discharge increased, (a) backwater pools created by logjams increased in size in both systems, (b) channel complexity increased as logjams forced flow into secondary channels, and (c) subsurface flowpath distribution increased. Various transient storage indices provide some insight on solute retention but compressing data from this system into simple values was unintuitive given the noise in breakthrough‐curve tails and secondary peaks in concentration. While subsurface exchange increases with discharge in both reaches, retention may not. Flushing of subsurface tracers is highest at medium discharge as interpreted from the electrical resistivity inversions in both reaches, perhaps because of a tradeoff between the increasing extent of subsurface flowpaths with discharge and larger pressure gradients for driving flow. This work is one of the first to explore controls on exchange and retention in stream systems with multiple logjams and evolving channel planform using geophysical data to constrain the subsurface movement of solutes.
Day‐To‐Day Variability of Ionospheric Electron Temperature Revealed by High‐Resolution SYISR Observations During April–May 2022
Authors: Wang Zhongqiu , Yue Xinan , Zhou Xu , Cai Yihui , Wang Junyi , Ding Feng , He Jianhui , Wang Yonghui , Zhang Ning , Luo Junhao , Li Mingyuan , Xu Su
Published: January 2025

This study investigated the day‐to‐day variability of ionospheric electron temperature (Te) over Sanya using the newly built Sanya Incoherent Scatter Radar (SYISR; 18.3°N, 109.6°E, dip latitude: 12.8°N). The 24 days of observations with transmitted beams encoded by the alternating code and directed toward the zenith provided Te profiles during April–May 2022. The spatial‐temporal resolution was as precise as 4.5 km and ∼120 s. The day‐to‐day variability of Te over Sanya thus revealed, which was strong in the sunrise Te peak region (above ∼260 km, duration increases from ∼0.5 to ∼3.5 hr with altitude) and the top of the 200–300 km Te bulge (∼260 to ∼300 km, lasting from ∼09:00 LT to ∼18:30 LT). The day‐to‐day variability of Te in the two regions could reach ∼26% and ∼16% of the average Te, respectively. Although the day‐to‐day variability of Te is negatively correlated with the variation of ionospheric electron densities (Ne) in general, a positive correlation still occurred during the daytime, especially at 400–480 km from ∼17:00 LT to ∼18:00 LT. Further Thermosphere Ionosphere Electrodynamics General Circulation Model simulations reproduced the positive correlation, which may result from the internal heat exchange between electrons, ions, and neutrals. The simulations suggested that the variation of solar radiation/geomagnetic activity contributes most to the daytime/sunrise day‐to‐day variability of Te over Sanya.
Development and Application of a New Convective Entrainment Rate Parameterization for Improving Precipitation Simulation Over the Tibetan Plateau and Its Surrounding Areas
Authors: Li Junjun , Lu Chunsong , Chen Jinghua , Li Jian , Yang Jing , Xu Xiaoqi , Zhu Lei , He Xin , Wu Shiying
Published: January 2025

The Tibetan Plateau (TP) significantly impacts the global climate. TP's unique geographical conditions make it one of the areas with the largest precipitation biases in numerical models. The overestimation and distribution biases of precipitation in models are closely related to the parameterization of convection processes over the TP. In light of this, a new deep convective entrainment rate parameterization suitable for the region is developed based on convection observational data and is applied to the Grell‐Freitas Ensemble Scheme of the Weather Research and Forecasting Model. The new scheme significantly reduces the overestimation of simulated precipitation over the TP, decreasing the overestimation from 29.4% in the default scheme to 11.8%. The physical mechanism behind the improved simulation results is as follows: first, the entrainment rate of convection in the new scheme is closer to the observed results. Second, in terms of cloud macrophysics, the new scheme increases the convective entrainment rate, reduces the cloud top height and depth of convective clouds, and decreases the number of grids with updrafts in the vertical layers and grids with convective precipitation on the surface. Third, in terms of cloud microphysics, the increased entrainment rate reduces the cloud water content and weakens the intensity of convective precipitation. All of these mechanisms ultimately reduce the accumulated convective precipitation amount, providing an optimized modeling tool for weather and climate research over TP, which also aids in better assessing the water cycle and water resource reserves of the “Asian Water Tower.”
Predicting Transient Anomalous Transport in Two‐Dimensional Discrete Fracture Networks With Dead‐End Fractures
Authors: Sun HongGuang , Lei Dawei , Zhang Yong , Qian Jiazhong , Yu Xiangnan
Published: January 2025

Pollutant transport in discrete fracture networks (DFNs) exhibits complex dynamics that challenge reliable model predictions, even with detailed fracture data. To address this issue, this study derives an upscaled integral‐differential equation to predict transient anomalous diffusion in two‐dimensional (2D) DFNs. The model includes both transmissive and dead‐end fractures (DEFs), where stagnant water zones in DEFs cause non‐uniform flow and transient sub‐diffusive transport, as shown by both literature and DFN flow and transport simulations using COMSOL. The upscaled model's main parameters are quantitatively linked to fracture properties, especially the probability density function of DEF lengths. Numerical experiments show the model's accuracy in predicting the full‐term evolution of conservative tracers in 2D DFNs with power‐law distributed fracture lengths and two orientation sets. Field applications indicate that while model parameters for transient sub‐diffusion can be predicted from observed DFN distributions, predicting parameters controlling solute displacement in transmissive fractures requires additional field work, such as tracer tests. Parameter sensitivity analysis further correlates late‐time solute transport dynamics with fracture properties, such as fracture density and average length. Potential extensions of the upscaled model are also discussed. This study, therefore, proves that transient anomalous transport in 2D DFNs with DEFs can be at least partially predicted, offering an initial step toward improving model predictions for pollutant transport in real‐world fractured aquifer systems.
Dual targeting PD-L1 and 4-1BB to overcome dendritic cell-mediated lenalidomide resistance in follicular lymphoma
Authors: Zheng Zhong , Wang Jian-Biao , Sun Rui , Wang Nan , Weng Xiang-Qin , Xu Tian-Yuan , Fu Di , Feng Yan , Xu Peng-Peng , Cheng Shu , Wang Li , Zhao Yan , Qu Bin , Huang Chuan-Xin , Zhao Wei-Li
Published: January 2025

Immunomodulatory agent lenalidomide is effective in treating follicular lymphoma (FL). We conducted the first trial of immunotherapy rituximab plus lenalidomide in newly diagnosed FL in China (NCT03715309). One-hundred and fifteen patients were enrolled and treated with rituximab 375 mg/m2 intravenously on day 0 and lenalidomide 25 mg orally on day 1–10 for 6 cycles of induction treatment, as well as lenalidomide for 6 cycles and rituximab for 8 cycles of maintenance treatment. We found that inferior progression-free survival of the patients was significantly associated with elevated serum β2m and lymph node >6 cm, linking to decreased lymphoma cell autophagy and dendritic cell infiltration within the tumor microenvironment. PU.1 transcriptionally downregulated PD-L1 (Programmed death ligand 1) expression and upregulated 4-1BBL (4-1BB ligand) expression, increased lymphoma cell autophagy and dendritic cell maturation via PD-1/PD-L1 and 4-1BB/4-1BBL interaction. In vitro in co-culture system and in vivo in murine xenograft model, knockdown of PU.1 induced lenalidomide resistance, but sensitized FL cells to bi-specific PD-L1/4-1BB antibody or combined treatment of PD-L1 inhibitor and 4-1BB agonist. Collectively, PU.1 is essential in immunomodulatory effect of FL through PD-1/PD-L1- and 4-1BB/4-1BBL-mediated microenvironmental modulation. Dual targeting PD-L1 and 4-1BB could be an alternative immunotherapeutic strategy in the chemo-free era of FL treatment.
Isoxazole-based molecules restore NK cell immune surveillance in hepatocarcinogenesis by targeting TM4SF5 and SLAMF7 linkage
Authors: Kim Ji Eon , Kim Hyun Su , Kim Wonsik , Lee Eun Hae , Kim Soyeon , Kim Taewoo , Shin Eun-Ae , Pyo Kyung-hee , Lee Haesong , Jin Seo Hee , Lee Jae-Ho , Byeon Soo-Min , Kim Dong Joo , Jeong Jinwook , Lee Jeongwon , Ohn Minjae , Lee Hyojung , Yu Su Jong , Shin Dongyun , Kim Semi , Yoo Jun Yeob , Lee Seung-Chul , Suh Young-Ger , Lee Jung Weon
Published: January 2025

Dynamic communication between hepatocytes and the environment is critical in hepatocellular carcinoma (HCC) development. Clinical immunotherapy against HCC is currently unsatisfactory and needs more systemic considerations, including the identification of new biomarkers and immune checkpoints. Transmembrane 4 L six family member 5 (TM4SF5) is known to promote HCC, but it remains unclear how cancerous hepatocytes avoid immune surveillance and whether avoidance can be blocked. We investigated how TM4SF5-mediated hepatic tumorigenesis avoids surveillance by natural killer (NK) cells, which are prevalent in the liver, and whether the avoidance can be blocked by anti-TM4SF5 agents. We used comprehensive structure activity relationship analysis to identify TM4SF5-specific isoxazole (TSI)-based small molecules that inhibit TM4SF5-mediated effects. TM4SF5 expressed by hepatocytes reduced NK cell cytotoxicity by downregulating stimulatory ligands/receptors, including signaling lymphocytic activation molecule family member 7 (SLAMF7). TM4SF5 bound SLAMF7 depending on N-glycosylation and caused intracellular trafficking of SLAMF7 from the plasma membrane to lysosomes for degradation. TSI treatments in cell lines and animal models of HCC blocked this binding, intracellular trafficking, and downregulation, resulting in higher levels of stimulatory NK cell ligands. In mouse xenograft models, TSI treatment abrogated HCC development by increasing the abundance and dispersion of Slamf7-positive cells in liver tissues, recapitulating the phenotype of Tm4sf5-knockout mice and indicating TSI-mediated restoration of NK cell surveillance. These findings suggest that TSIs can inhibit TM4SF5-mediated liver carcinogenesis by increasing NK cell surveillance.
CRAT downregulation promotes ovarian cancer progression by facilitating mitochondrial metabolism through decreasing the acetylation of PGC-1α
Authors: Zhang Zhen , Zhao Shuhua , Lv Xiaohui , Gao Yan , Guo Qian , Ren Yanjie , He Yuanyuan , Jin Yihua , Yang Hong , Liu Shujuan , Zhang Xiaohong
Published: January 2025

Mitochondrial dysfunctions are closely associated with different types of disease, including cancer. Carnitine acetyltransferase (CRAT) is a mitochondrial-localized enzyme catalyzing the reversible transfer of acyl groups from an acyl-CoA thioester to carnitine and regulates the ratio of acyl-CoA/CoA. Our bioinformatics analysis using public database revealed a significant decrease of CRAT expression in ovarian cancer (OC). However, the functions of CRAT have rarely been investigated in human cancers, especially in OC. Here, we found a frequent down-regulation of CRAT in OC, which is mainly caused by up-regulation of miR-132-5p. Downregulation of CRAT was significantly associated with shorter survival time for patients with OC. Forced expression of CRAT suppressed OC growth and metastasis by inducing cell cycle arrest and epithelial to mesenchymal transition (EMT). By contrast, CRAT knockdown promoted OC growth and metastasis. Mechanistically, we found that CRAT downregulation promoted OC growth and metastasis by increasing mitochondrial biogenesis to facilitate mitochondrial metabolism through reducing the acetylation of peroxisome proliferator-activated receptor-γ coactivator (PGC-1α). In summary, CRAT functions as a critical tumor suppressor in OC progression by enhancing PGC-1α-mediated mitochondrial biogenesis and metabolism, suggesting CRAT as a potential therapeutic target in treatment of OC.
Age-associated microglial transcriptome leads to diminished immunogenicity and dysregulation of MCT4 and P2RY12/P2RY13 related functions
Authors: Škandík Martin , Friess Lara , Vázquez-Cabrera Guillermo , Keane Lily , Grabert Kathleen , Cruz De los Santos Mireia , Posada-Pérez Mercedes , Baleviciute Austeja , Cheray Mathilde , Joseph Bertrand
Published: January 2025

The aging process is marked by a time-dependent deterioration in cellular functions, particularly the immune and neural systems. Understanding the phenotype acquisition of microglia, the sentinel immune cells of the brain, is crucial for understanding the nature of age-related neurological diseases. However, the specific phenotype adopted by microglia during aging remains a subject of debate and is contingent on the chosen experimental model. To address these unresolved questions, we employed a novel and highly controlled approach utilizing long-term cultivated BV-2 microglia, exempted from additional external stimuli. Our findings revealed that aged microglial cells, in comparison to their younger counterparts, acquire a distinct gene expression profile, primarily characterized by alterations in microglial immune response. Indeed, pro-inflammatory stimulated aged and young BV-2 microglia exhibited similar transcriptomic profiles, yet the response intensity to the stimulus was markedly muted in the aged microglia. Functional neurotoxic assays confirmed diminished neuronal death in coculture with aged, activated microglia, underscoring a compromised immune response. Furthermore, a subsequent comparative analysis of aged BV-2 microglia with established transcriptomic microglial datasets from aged mice and humans identified 13 overlapping genes, laying the foundation for identifying core microglial aging signature. Particularly noteworthy were SLC16A3 and P2RY13, which consistently exhibited upregulation and downregulation, respectively, across all datasets. Additionally, four other genes—CAPG, LGALS3BP, NRIP1, and P2RY12—were found to share regulatory patterns in response to both aging and extrinsic activation. An in-depth investigation focused on SLC16A3, encoding the high-affinity lactate transporter MCT4, revealed disruptions in extracellular acidification rate and lactate concentration with age. Microglial purine sensing and motility capacities, regulated by P2RY12/P2RY13, displayed age-related alterations. Remarkably, protein analysis in human brain tissue validated the observed upregulation of MCT4 and downregulation of P2RY12 in aged microglia. In conclusion, our study unveils a distinct phenotype in aged microglia characterized by compromised immune responsiveness. Through the integration of in vitro cultured BV-2 microglia with primary microglia datasets, we identify critical molecular determinants of microglial cellular aging confirmed in human-aged brain tissue. This comprehensive approach offers potential insights for understanding and potentially reprogramming aged microglia, with implications for combating age-related neurological disorders.
Structural insights into human topoisomerase 3β DNA and RNA catalysis and nucleic acid gate dynamics
Authors: Yang Xi , Chen Xuemin , Yang Wei , Pommier Yves
Published: January 2025

Type IA topoisomerases (TopoIAs) are present in all living organisms. They resolve DNA/RNA catenanes, knots and supercoils by breaking and rejoining single-stranded DNA/RNA segments and allowing the passage of another nucleic acid segment through the break. Topoisomerase III-β (TOP3B), the only RNA topoisomerase in metazoans, promotes R-loop disassembly and translation of mRNAs. Defects in TOP3B lead to severe neurological diseases. We present a series of cryo-EM structures of human TOP3B with its cofactor TDRD3 during cleavage and rejoining of DNA or RNA, thus elucidating the roles of divalent metal ions and key enzyme residues in each step of the catalytic cycle. We also obtained the structure of an open-gate configuration that addresses the long-standing question of the strand-passage mechanism. Our studies reveal how TOP3B catalyzes both DNA and RNA relaxation, while TOP3A acts only on DNA.
Identification of a binding site for small molecule inhibitors targeting human TRPM4
Authors: Ekundayo Babatunde , Arullampalam Prakash , Gerber Christian E. , Hämmerli Anne-Flore , Guichard Sabrina , Boukenna Mey , Ross-Kaschitza Daniela , Lochner Martin , Rougier Jean-Sebastien , Stahlberg Henning , Abriel Hugues , Ni Dongchun
Published: January 2025

Transient receptor potential (TRP) melastatin 4 (TRPM4) protein is a calcium-activated monovalent cation channel associated with various genetic and cardiovascular disorders. The anthranilic acid derivative NBA is a potent and specific TRPM4 inhibitor, but its binding site in TRPM4 has been unknown, although this information is crucial for drug development targeting TRPM4. We determine three cryo-EM structures of full-length human TRPM4 embedded in native lipid nanodiscs without inhibitor, bound to NBA, and an anthranilic acid derivative, IBA. We found that the small molecules NBA and IBA were bound in a pocket formed between the S3, S4, and TRP helices and the S4-S5 linker of TRPM4. Our structural data and results from patch clamp experiments enable validation of a binding site for small molecule inhibitors, paving the way for further drug development targeting TRPM4.
Enhancing structural health monitoring of fiber-reinforced polymer composites using piezoresistive Ti3C2Tx MXene fibers
Authors: Taymaz Bircan Haspulat , Kamış Handan , Dziendzikowski Michal , Kowalczyk Kamil , Dragan Krzysztof , Eskizeybek Volkan
Published: January 2025

The anisotropic behavior of fiber-reinforced polymer composites, coupled with their susceptibility to various failure modes, poses challenges for their structural health monitoring (SHM) during service life. To address this, non-destructive testing techniques have been employed, but they often suffer from drawbacks such as high costs and suboptimal resolutions. Moreover, routine inspections fail to disclose incidents or failures occurring between successive assessments. As a result, there is a growing emphasis on SHM methods that enable continuous monitoring without grounding the aircraft. Our research focuses on advancing aerospace SHM through the utilization of piezoresistive MXene fibers. MXene, characterized by its 2D nanofiber architecture and exceptional properties, offers unique advantages for strain sensing applications. We successfully fabricate piezoresistive MXene fibers using wet spinning and integrate them into carbon fiber-reinforced epoxy laminates for in-situ strain sensing. Unlike previous studies focused on high strain levels, we adjust the strain levels to be comparable to those encountered in practical aerospace applications. Our results demonstrate remarkable sensitivity of MXene fibers within low strain ranges, with a maximum sensitivity of 0.9 at 0.13% strain. Additionally, MXene fibers exhibited high reliability for repetitive tensile deformations and low-velocity impact loading scenarios. This research contributes to the development of self-sensing composites, offering enhanced capabilities for early detection of damage and defects in aerospace structures, thereby improving safety and reducing maintenance expenses.
An android can show the facial expressions of complex emotions
Authors: Diel Alexander , Sato Wataru , Hsu Chun-Ting , Bäuerle Alexander , Teufel Martin , Minato Takashi
Published: January 2025

Trust and rapport are essential abilities for human–robot interaction. Producing emotional expressions in the robots’ faces is an effective way for that purpose. Androids can show human-like facial expressions of basic emotions. However, whether androids can show the facial expression of complex emotions remains unknown. In this experiment, we investigated the android Nikola’s ability to produce 22 dynamic facial expressions of complex emotions. For each video, 240 international participants (120 Japanese, 120 German) rated the emotions expressed by Nikola. For 13 complex emotions (i.e., amusement, appal, awe, boredom, contentment, coyness, hatred, hesitation, moral disgust, not face, pain, sleepiness, suspicion), participants of both samples rated the target emotion above the mean of other non-target emotions. Four emotions (bitterness, confusion, pride, relief) were rated above mean by one sample. For twelve of these emotions, target emotions were among the highest ranked. The results suggest that androids can produce the facial expressions of a wide range of complex emotions, which can facilitate human–robot interactions.
Secure channel estimation model for cognitive radio network physical layer security using two-level shared key authentication
Authors: Saravanan K. , Gurumoorthy K. B. , Stalin Allwin Devaraj , Kumar Om Prakash
Published: January 2025

Physical Layer Security (PLS) in Cognitive Radio Networks (CRN) improves the confidentiality, availability, and integrity of the external communication between the devices/ users. The security models for sensing and beamforming reduce the impact of adversaries such as eavesdroppers in the signal processing layer. To such an extent, this article introduces a Secure Channel Estimation Model (SCEM) using Channel State Information (CSI) and Deep Learning (DL) to improve the PLS. In this proposed model, the CSI is exploited to evaluate the channel utilization and actual capacity availability throughout the allocation intervals. The change in channel capacity and utilization augments the need for security through 2-level key shared authentication. The deep learning algorithm verifies the authentication completeness for maximum channel capacity utilization irrespective of adversary interference. This verification follows mutual authentication between the primary and secondary users sharing the maximum capacity channel with high secrecy. The learning monitors the outage secrecy rates to verify failed allocations such that the replacement for allocation is pursued. Thus, the physical layer security between different user categories is administered through maximum CSI exploitation with high beamforming abilities. The proposed model leverages the secrecy rate by 10.77% and the probability of detection by 15.01% and reduces the interference rate by 11.07% for the varying transmit powers.
The extent of the hip bone sexual dimorphism in two Italian coeval modern skeletal samples
Authors: Sorrentino Rita , Pietrobelli Annalisa , Mameli Davide , Nicolosi Teresa , Belcastro Maria Giovanna
Published: January 2025

The rate of sexual dimorphism in the human hip bone is primarily due to the structural demands of childbirth. Genetic, environmental, and socio-cultural factors can also influence pelvic shape variations across populations. This study examines intra-population sex variation within the Italian population based on regional differences of 280 coxal bones from two documented human osteological collections (Bologna and Sassari) coming from different geographical areas, the northern continental and island regions. Nineteen metric variables were used to evaluate sexual dimorphism and population differences. Most of the variables showed sexual dimorphism, particularly the hip height and ischio-pubic measures within both populations, and accurately predicted sex for each population (Bologna: 100%; Sassari: 91.2%). Results show the Bologna sample have larger dimensions for most of the measurements than the Sassari one, especially when considering the longitudinal ones. Some female traits of the Bologna sample are larger than the correspondent ones in the Sassari males. The rate of sexual dimorphism between the populations shows significant differences, with better sex distinction for Bologna than Sassari. This study aims at interpreting these intra-population differences, considering the effect of environmental (physical and social milieu) and genetic factors, underscoring the importance of this local differences for accurate diagnostic criteria.
Optimizing the growth conditions of superconducting MoSi thin films for single photon detection
Authors: Grotowski Stefanie , Zugliani Lucio , Jonas Björn , Flaschmann Rasmus , Schmid Christian , Strohauer Stefan , Wietschorke Fabian , Bruckmoser Niklas , Müller Manuel , Althammer Matthias , Gross Rudolf , Müller Kai , Finley Jonathan
Published: January 2025

We investigate the growth of amorphous MoSi thin films using magnetron co-sputtering and optimize the growth conditions with respect to crystal structure and superconducting properties (e.g., critical temperature
$$T_{\text {c}}$$
). The deposition pressure, Mo:Si stoichiometry and substrate temperature are systematically varied to achieve a transition temperature of 8.4(3) K for films with a thickness of 17.7(8) nm and 6.2(9) K for a 4.3(4) nm thick film. For Mo concentrations above 81% the crystalline phase

$$\hbox {Mo}_\text {3}$$

Mo
3

Si is observed in grazing incidence X-ray diffraction measurements. The same phase appears when the working pressure during deposition is reduced below 3.

$$1 \times 10^{\text {-3}}\hspace{1.66656pt}$$

1
×

10
-3

mbar and when the substrate temperature during deposition is increased above
$$100\hspace{1.66656pt}^{\circ } $$
C. By choosing a sufficient Si concentration and optimum deposition pressure we identify deposition conditions that ensure a homogeneous amorphous growth of the superconducting thin film. We then fabricate superconducting nanowire single-photon detectors which exhibit an unitary internal efficiency to single photons at an operational temperature of 1.2 K while simultaneously having a dark count rate below 1 Hz. Our results establish the link between MoSi film deposition, morphology and the performance of SSPD.
Clinical entity augmented retrieval for clinical information extraction
Authors: Lopez Ivan , Swaminathan Akshay , Vedula Karthik , Narayanan Sanjana , Nateghi Haredasht Fateme , Ma Stephen P. , Liang April S. , Tate Steven , Maddali Manoj , Gallo Robert Joseph , Shah Nigam H. , Chen Jonathan H.
Published: January 2025

Large language models (LLMs) with retrieval-augmented generation (RAG) have improved information extraction over previous methods, yet their reliance on embeddings often leads to inefficient retrieval. We introduce CLinical Entity Augmented Retrieval (CLEAR), a RAG pipeline that retrieves information using entities. We compared CLEAR to embedding RAG and full-note approaches for extracting 18 variables using six LLMs across 20,000 clinical notes. Average F1 scores were 0.90, 0.86, and 0.79; inference times were 4.95, 17.41, and 20.08 s per note; average model queries were 1.68, 4.94, and 4.18 per note; and average input tokens were 1.1k, 3.8k, and 6.1k per note for CLEAR, embedding RAG, and full-note approaches, respectively. In conclusion, CLEAR utilizes clinical entities for information retrieval and achieves >70% reduction in token usage and inference time with improved performance compared to modern methods.
A motor fault diagnosis using hybrid binary differential evolution algorithm and whale optimization algorithm with storage space
Authors: Lee Chun‐Yao , Le Truong‐An , Chu Tzu‐Hao , Hsu Shih‐Che
Published: January 2025

The most common cause of mechanical failure is bearing failure, and the characteristics of each failure correspond to a certain degree of severity. This paper proposes a fault diagnosis model for detecting motor bearings. The model uses three steps: feature extraction, feature selection, and classification. In feature extraction, empirical mode decomposition, fast Fourier transform, and envelope analysis extract important features from the signals measuring the motor. In feature selection, a binary differential evolution and binary whale algorithm are developed and the storage space is increased to eliminate irrelevant features again. Finally, KNN and SVM are used to determine the stability of the bearing fault diagnosis model.
Virtual inertia and damping‐based cascaded control approach for enhancing load frequency control in low‐inertia multi‐area power systems
Authors: Roy Tushar Kanti , Oo Amanullah Maung Than
Published: January 2025

This paper introduces a comprehensive cascaded controller to enhance transient and dynamic stability in load frequency control for low‐inertia multi‐area power systems (LIMAPSs) integrating solar photovoltaic and wind turbine sources. The proposed method combines a composite energy storage‐based virtual synchronous generator with a novel cascaded controller employing an adaptive neuro‐fuzzy inference system (ANFIS) and a fractional‐order proportional–integral with a fractional‐order proportional‐tilt‐integral (FOPI‐FOPTI) control strategy. Firstly, a dynamic model of a thermal power plant incorporating photovoltaic, wind turbine, and virtual synchronous generator is developed. Subsequently, the ANFIS‐FOPI‐FOPTI controller parameters, optimized via the whale optimization algorithm, provide adaptive and robust frequency stability control under disturbances. Finally, extensive simulations demonstrate the proposed approach's effectiveness in enhancing the transient and dynamic stability of LIMAPSs. The simulations are conducted on two‐area power systems and a modified IEEE 10‐generator 39‐bus system, considering disturbances like stochastic load‐generation. Comparative analysis with existing controllers shows the proposed cascaded controller effectively addresses load frequency control challenges in LIMAPSs. It outperforms other control approaches in terms of settling time, overshoot, and specified objective functions, with the lowest integral time absolute error values recorded: 0.1202 for the two‐area system and 0.480 for the modified IEEE 39‐bus four‐area power system.