bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fundamental equations linking methylation dynamics to maximum lifespan in mammals
Authors: Horvath Steve , Zhang Joshua , Haghani Amin , Lu Ake T. , Fei Zhe 
Published: September 2024

AbstractWe describe a framework that addresses concern that the rate of change in any aging biomarker displays a trivial inverse relation with maximum lifespan. We apply this framework to methylation data from the Mammalian Methylation Consortium. We study the relationship of lifespan with the average rate of change in methylation (AROCM) from two datasets: one with 90 dog breeds and the other with 125 mammalian species. After examining 54 chromatin states, we conclude three key findings: First, a reciprocal relationship exists between the AROCM in bivalent promoter regions and maximum mammalian lifespan: AROCM $$\propto$$
∝
1/MaxLifespan. Second, the correlation between average methylation and age bears no relation to maximum lifespan, Cor(Methyl,Age) ⊥ MaxLifespan. Third, the rate of methylation change in young animals is related to that in old animals: Young animals’ AROCM $$\propto$$
∝
Old AROCM. These findings critically hinge on the chromatin context, as different results emerge in other chromatin contexts.
Regional patterns of human cortex development correlate with underlying neurobiology
Authors: Lotter Leon D. , Saberi Amin , Hansen Justine Y. , Misic Bratislav , Paquola Casey , Barker Gareth J. , Bokde Arun L. W. , Desrivières Sylvane , Flor Herta , Grigis Antoine , Garavan Hugh , Gowland Penny , Heinz Andreas , Brühl Rüdiger , Martinot Jean-Luc , Paillère Marie-Laure , Artiges Eric , Papadopoulos Orfanos Dimitri , Paus Tomáš , Poustka Luise , Hohmann Sarah , Fröhner Juliane H. , Smolka Michael N. , Vaidya Nilakshi , Walter Henrik , Whelan Robert , Schumann Gunter ,   IMAGEN Consortium, Nees Frauke , Banaschewski Tobias , Eickhoff Simon B. , Dukart Juergen 
Published: September 2024

AbstractHuman brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
Underestimation of personal carbon footprint inequality in four diverse countries
Authors: Nielsen Kristian S. , Bauer Jan M. , Debnath Ramit , Emogor Charles A. , Geiger Sonja M. , Ghai Sakshi , Gwozdz Wencke , Hahnel Ulf J. J. 
Published: September 2024

AbstractExtensive research highlights global and within-country inequality in personal carbon footprints. However, the extent to which people are aware of these inequalities remains unclear. Here we use an online survey distributed across four diverse countries: Denmark, India, Nigeria and the USA, to show widespread underestimation of carbon footprint inequality, irrespective of participants’ country and income segment. Of the 4,003 participants, within each country, 50% of participants were sampled from the top 10% income group. Our results show links between carbon footprint inequality perceptions and climate policy support, but with significant variations observed across the four countries and with participants’ income segments. Furthermore, there are links to the perceived fairness of actual carbon footprint inequality, highlighting the need to raise awareness about carbon footprint inequality and further unpack its implications for climate justice and policy.
Acidity suppresses CD8 + T-cell function by perturbing IL-2, mTORC1, and c-Myc signaling
Authors: Vuillefroy de Silly Romain , Pericou Laetitia , Seijo Bili , Crespo Isaac , Irving Melita 
Published: September 2024

AbstractCD8 + T cells have critical roles in tumor control, but a range of factors in their microenvironment such as low pH can suppress their function. Here, we demonstrate that acidity restricts T-cell expansion mainly through impairing IL-2 responsiveness, lowers cytokine secretion upon re-activation, and reduces the cytolytic capacity of CD8 + T cells expressing low-affinity TCR. We further find decreased mTORC1 signaling activity and c-Myc levels at low pH. Mechanistically, nuclear/cytoplasmic acidification is linked to mTORC1 suppression in a Rheb-, Akt/TSC2/PRAS40-, GATOR1- and Lkb1/AMPK-independent manner, while c-Myc levels drop due to both decreased transcription and higher levels of proteasome-mediated degradation. In addition, lower intracellular levels of glutamine, glutamate, and aspartate, as well as elevated proline levels are observed with no apparent impact on mTORC1 signaling or c-Myc levels. Overall, we suggest that, due to the broad impact of acidity on CD8 + T cells, multiple interventions will be required to restore T-cell function unless intracellular pH is effectively controlled.
Epigenetic inheritance and gene expression regulation in early Drosophila embryos
Authors: Ciabrelli Filippo , Atinbayeva Nazerke , Pane Attilio , Iovino Nicola 
Published: September 2024

AbstractPrecise spatiotemporal regulation of gene expression is of paramount importance for eukaryotic development. The maternal-to-zygotic transition (MZT) during early embryogenesis in Drosophila involves the gradual replacement of maternally contributed mRNAs and proteins by zygotic gene products. The zygotic genome is transcriptionally activated during the first 3 hours of development, in a process known as “zygotic genome activation” (ZGA), by the orchestrated activities of a few pioneer factors. Their decisive role during ZGA has been characterized in detail, whereas the contribution of chromatin factors to this process has been historically overlooked. In this review, we aim to summarize the current knowledge of how chromatin regulation impacts the first stages of Drosophila embryonic development. In particular, we will address the following questions: how chromatin factors affect ZGA and transcriptional silencing, and how genome architecture promotes the integration of these processes early during development. Remarkably, certain chromatin marks can be intergenerationally inherited, and their presence in the early embryo becomes critical for the regulation of gene expression at later stages. Finally, we speculate on the possible roles of these chromatin marks as carriers of epialleles during transgenerational epigenetic inheritance (TEI).
Self-supervised learning on MeerKAT wide-field continuum images
Authors: Lastufka E. , Bait O. , Taran O. , Drozdova M. , Kinakh V. , Piras D. , Audard M. , Dessauges-Zavadsky M. , Holotyak T. , Schaerer D. , Voloshynovskiy S. 
Published: September 2024

Context. Self-supervised learning (SSL) applied to natural images has demonstrated a remarkable ability to learn meaningful, low-dimension representations without labels, resulting in models that are adaptable to many different tasks. Until now, applications of SSL to astronomical images have been limited to Galaxy Zoo datasets, which require a significant amount of preprocessing to prepare sparse images centered on a single galaxy. With wide-field survey instruments at the forefront of the Square Kilometer Array (SKA) era, this approach to gathering training data is impractical.
Aims. We demonstrate that continuum images from surveys such as the MeerKAT Galactic Cluster Legacy Survey (MGCLS) can be successfully used with SSL, without extracting single-galaxy cutouts.
Methods. Using the SSL framework DINO, we experimented with various preprocessing steps, augmentations, and architectures to determine the optimal approach for this data. We trained both ResNet50 and Vision Transformer (ViT) backbones.
Results. Our models match state-of-the-art results (trained on Radio Galaxy Zoo) for FRI/FRII morphology classification. Furthermore, they predict the number of compact sources via linear regression with much higher accuracy. Open-source foundation models trained on natural images such as DINOv2 also excel at simple FRI/FRII classification; the advantage of domain-specific backbones is much smaller models trained on far less data. Smaller models are more efficient to fine-tune, and doing so results in a similar performance between our models, the state-of-the-art, and open-source models on multi-class morphology classification.
Conclusions. Using source-rich crops from wide-field images to train multi-purpose models is an easily scalable approach that significantly reduces data preparation time. For the tasks evaluated in this work, twenty thousand crops is sufficient training data for models that produce results similar to state-of-the-art. In the future, complex tasks like source detection and characterization, together with domain-specific tasks, ought to demonstrate the true advantages of training models with radio astronomy data over natural-image foundation models.
Applying lean production system philosophy to reduce patient waiting time in healthcare services: Simulation-based optimization and validations through experiment
Authors: Hassan Sana , Amjad Asim , Farooq Muhammad Umar , Anwar Saqib , Ammarullah Muhammad Imam 
Published: September 2024

Value stream mapping (VSM) is an initial and critical tool for deploying lean concepts in the manufacturing and service sectors, including hospitals. Therefore, the aim of this research is to analyze the current working environment of a radiology department, identify the wastes in the operations by mapping the current patient flow, and test the best possible improvement plan with the help of discrete event simulation modeling using the Arena platform to develop an optimum future map to mitigate the wastes. Therefore, the current patient flow in the x-ray section of a radiology department was mapped using VSM for two types of patients named routine (RP) and procedure (PP). VSM results highlighted a high waiting time (TWT) of 188 and 3732 min for RP and PP. A total of seven scenarios were developed and analyzed to determine the impact of changes on five key performance indicators. Simulation results of the current scenario showed that there were 567 patients coming out of the system with a lead time of 200 and 926 min for RP and PP. Total waiting time obtained for RP and PP was 177 and 860 min, with a maximum wait time of 31 min/patient and an average of 43 patients in the system (WIP). The simulation results of the seventh scenario provided the best results, with 6% improvement in the number of patients getting out of the system and 75% and 55% decreased lead time for RP and PP. Total waiting time for RP and PP was reduced by 80% and 60%, with WIP falling by 62%. Arena Optimizer showed that by adding a technician and radiologist to the system, the optimum patient waiting time in the queue would be 6 min, and the lead time for RP and PP would be (160) and (884 min), respectively. Based on it, a future VSM was created; it provided a reduction of 72% and 60% in (TWT) for RP and PP, which could improve the number of patients to be entertained by the radiology services without adding any new x-ray machines. The results of the present case provide healthcare planners with a road map to discover the waste in operations since the monetary investment and organizational dedication required drive out non-value activities. Therefore, simulation helps to select the best possible improvement strategy for the system without pausing and making physical changes in busy and complex units of hospitals.
Creating individual styles through discourse variation in Singapore Mandarin
Authors: Teo Ming Chew , Lin Jingxia 
Published: September 2024

Abstract
By applying the concepts of indexicality and enregisterment, this paper demonstrates how different discourse
particles and their collocations index various personae in Singapore Mandarin and how media representations enregister them within
the community. The theory of persona is shown to explain the majority of seemingly random individual differences in discourse
particle usage exhibited by two TV hosts. Finally, it is important to note that not all variation between the two hosts can be
attributed to the enactment of personae. Psychological factors, such as bilingual lexical activation, should also be considered
influences on linguistic variation, alongside linguistic and social factors.
Fostering primary students’ competences for democratic culture in EFL
Authors: Abe Motoko , Beecroft Raphaëlle 
Published: September 2024

Abstract
The PEACE project was a teaching unit which was designed, implemented and evaluated in two primary school classes in Japan
and Germany respectively. The project was carried out in an asynchronous virtual exchange format between the two classes. The Reference
Framework of Competences for Democratic Culture was used as a basis for the teaching unit, with the framework’s descriptors for young
learners serving as tools for designing and assessing both the teaching unit and its outcomes in the form of the participating students’
products and utterances. Using the NVivo coding software for content analysis, the study investigated the deployment of the various areas of
competence by the students during the teaching unit and compared these across the classes. This was done to gain insights into both the
context-dependency of the deployment of competences for democratic culture as well as the practicability and potentials of carrying out a
bilateral asynchronous virtual exchange aiming to promote competences for democratic culture in young learners.
Electrical discharge machining of super alloy incoloy 925: a study based on box behnken design and response surface methodology
Authors: Chaurasia Satish , Dutta Hrishikesh , Singh Samarjit , Debnath Kishore , Bhowmik Abhijit 
Published: September 2024

Abstract
Incoloy 925, a Nikel-based superalloy, exhibits low machinability with conventional machining techniques due to its inhomogeneous properties. Therefore, there is a need to establish a non-conventional method to efficiently machine this alloy. This work is a novel attempt to present the electric discharge machining (EDM) of the superalloy Incoloy 925 and subsequent multi-response optimization. The model for the analysis was designed using the Box Behnken Design (BBD) technique, and the Response Surface Methodology (RSM) was used for the optimization of the results. The machining was performed using a cylindrical copper tool of 11 mm diameter. The effect of pulse-on time (Ton), current, and pulse-off time (Toff) on the material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) was investigated. The results from variance analysis confirmed the significance of all the three input factors. The investigation revealed that the maximum MRR (99.2154 mm3/min) was obtained at a pulse-on time of 90 μs, pulse-off time of 5 μs, and current of 30 A. The minimum TWR (0.8866 mm3/min) were achieved at Ton = 60 μs, Toff = 8 μs and current = 10 A. The microscopic images of the machined surfaces revealed very few micro-voids and globules and no cracks, resulting in a fine surface finish of 1.2436 μm, achieved through optimal discharge energy transfer and copper electrodes. The optimal values MRR, TWR, and SR according to composite desirability function are 99.1524 mm3/min, 1.0915 mm3/min, and 1.3925 μm. The experimental results were accurately predicted using RSM and an artificial neural network (ANN), with the ANN showing a predicted correlation coefficient (R) close to 1 indicating high accuracy of the model.
Room temperature dual-mode internal quantum deficiency measurement with propagated uncertainty to 0.03% (k = 2)
Authors: Heitmann Solheim Johanne , Bardalen Eivind , Gran Jarle 
Published: September 2024

Abstract
We present improvements in dual-mode calibration of predictable quantum efficient detectors and demonstrate the importance of calculating absolute uncertainties instead of relative uncertainties. We have implemented a new uncertainty component for the thermal fluctuations in the temperature signal which results in a propagated Type A uncertainty, matching the observed standard deviation. A new thermal drift correction method exploiting a monitor thermistor on the heat sink is relaxing the need for thermal stabilisation of the experimental set-up. With beam position uncertainty ±0.25 mm and background electrical power varying from 10 μW to 900 μW, the measured internal quantum deficiency (IQD) is in average 0.00% ± 0.03% (k = 2). The IQD exhibits clear systematic effects of beam position and background power, showing the need for improved design of dual-mode modules to further improve the uncertainty.
CZTSSe thin film solar cells with two absorber layers and a PbS layer
Authors: Zhou Xin , Xue Yuming , Wang Luoxin 
Published: September 2024

Abstract
In this paper, we simulated a novel CZTSSe (copper-zinc-tin-sulfide-selenide) thin film solar cell with two absorber layers and a PbS (a lead sulfide) layer by SCAPS-1D. We investigated the effect of changes in the thickness of the absorbing layer and the acceptor concentration on this cell. Meanwhile, we also optimized the bandgap width of CZTSSe and the thickness of PbS. Moreover, an effective method has been applied with the aim of boosting conversion efficiency by adding a BSF (back surface field) layer to the cell. The BSF layer helps to enhance optical behavior and reduces recombination losses, consequently reducing the Voc (open circuit voltage) deficit. With the highest conversion efficiency calculated in the simulation, a cell conversion efficiency of 27.70% can be achieved, which is significantly higher than the basic structure, providing a large electrical power as well as a more optimal filling factor at the same time.
Modulation of plant transcription factors and priming of stress tolerance by plant growth-promoting bacteria: a systematic review
Authors: Kaleh Abdussabur M , Singh Pooja , Chua Kah Ooi , Harikrishna Jennifer Ann 
Published: September 2024

Abstract

Background
Plant growth-promoting bacteria (PGPB) have been shown to improve plant growth and stress tolerance through mechanisms including improved access to nutrients and biotic competition with pathogens. As such, the use of PGPB can help to address challenges to crop productivity, but information on interactions between PGPB and their plant hosts, especially at the level of gene regulation, is distributed across diverse studies involving several different plants and PGPB.

Scope
For this review, we analysed recent research publications reporting specifically on plant transcription factor (TF) expression in association with PGPB, to determine if there are any common findings and to identify gaps that offer opportunities for focused future research.

Conclusions
The inoculation of plants with PGPB elicits a dynamic and temporal response. Initially, there is an upregulation of defence-responsive TFs, followed by their downregulation in an intermediate phase, and finally, another upregulation, providing longer term stress tolerance. PGPB priming activates plant defences in the form of induced systemic resistance (ISR), often via the MAMP/MAPK pathways and involving one or more of the major plant hormone-signalling pathways and their crosstalk. Following PGPB priming, the TF families most commonly reported as expressed across different plants and for different pathogens are ERF and WRKY, while the TFs most commonly expressed across different plants for different abiotic stresses are ERF and DREB. There were inconsistencies between studies regarding the timing of the shift from the initial phase to the intermediate phase, and some of the TFs expressed during this process have not been fully characterized. This calls for more research to investigate the regulatory functions and phases of TF expression, to enhance crop resilience. Most reports on abiotic stresses have focused on salinity and drought, with fewer studies addressing nutrient deficiency, heavy metals, flooding and other stresses, highlighting the need for further research in these areas.
Semi-parametric benchmark dose analysis with monotone additive models
Authors: Stringer Alex , Akkaya Hocagil Tugba , Cook Richard J , Ryan Louise M , Jacobson Sandra W , Jacobson Joseph L 
Published: September 2024

Abstract
Benchmark dose analysis aims to estimate the level of exposure to a toxin associated with a clinically significant adverse outcome and quantifies uncertainty using the lower limit of a confidence interval for this level. We develop a novel framework for benchmark dose analysis based on monotone additive dose-response models. We first introduce a flexible approach for fitting monotone additive models via penalized B-splines and Laplace-approximate marginal likelihood. A reflective Newton method is then developed that employs de Boor’s algorithm for computing splines and their derivatives for efficient estimation of the benchmark dose. Finally, we develop a novel approach for calculating benchmark dose lower limits based on an approximate pivot for the nonlinear equation solved by the estimated benchmark dose. The favorable properties of this approach compared to the Delta method and a parameteric bootstrap are discussed. We apply the new methods to make inferences about the level of prenatal alcohol exposure associated with clinically significant cognitive defects in children using data from six NIH-funded longitudinal cohort studies. Software to reproduce the results in this paper is available online and makes use of the novel semibmd R package, which implements the methods in this paper.
collectNET: a web server for integrated inference of cell–cell communication network
Authors: Pan Yan , Gao Zijing , Cui Xuejian , Li Zhen , Jiang Rui 
Published: September 2024

Abstract
Cell–cell communication (CCC) through ligand–receptor (L–R) pairs forms the cornerstone for complex functionalities in multicellular organisms. Deciphering such intercellular signaling can contribute to unraveling disease mechanisms and enable targeted therapy. Nonetheless, notable biases and inconsistencies are evident among the inferential outcomes generated by current methods for inferring CCC network. To fill this gap, we developed collectNET (http://health.tsinghua.edu.cn/collectnet) as a comprehensive web platform for analyzing CCC network, with efficient calculation, hierarchical browsing, comprehensive statistics, advanced searching, and intuitive visualization. collectNET provides a reliable online inference service with prior knowledge of three public L–R databases and systematic integration of three mainstream inference methods. Additionally, collectNET has assembled a human CCC atlas, including 126 785 significant communication pairs based on 343 023 cells. We anticipate that collectNET will benefit researchers in gaining a more holistic understanding of cell development and differentiation mechanisms.
Database URL: http://health.tsinghua.edu.cn/collectnet.