bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geodynamic Evolution of the Lau Basin
Authors: Peng Diandian , Stegman Dave R. 
Published: August 2024

AbstractThe formation of Lau Basin records an extreme event of plate tectonics, with the associated Tonga trench exhibiting the fastest retreat in the world (16 cm/yr). Yet paleogeographic reconstructions suggest that seafloor spreading in the Lau Basin only initiated around 6 Ma. This kinematics is difficult to reconcile with our present understanding of how subduction drives plate motions. Using numerical models, we propose that eastward migration of the Lau Ridge concurrent with trench retreat explains both the narrow width and thickened crust of the Lau Basin. To match the slab geometry and basin width along the Tonga‐Kermadec trench, our models suggest that fast trench retreat rate of 16 cm/yr might start ~15 Ma. Tonga slab rollback induced vigorous mantle flow underneath the South Fiji Basin which is driving the extension and thinning of the basin and contributing to its observed deeper bathymetry compared to neighboring basins.
Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration
Authors: Raghav Pushpendra , Kumar Mukesh , Liu Yanlan 
Published: August 2024

AbstractEvapotranspiration (ET) plays a critical role in water and energy budgets at regional to global scales. ET is composed of direct evaporation (E) and plant transpiration (T) where the latter is regulated via stomatal conductance (gsc), which depends on a multitude of plant physiological processes and hydrometeorological forcings. In recent years, significant advances have been made toward estimating gsc using a variety of models, ranging from relatively simple empirical models to more complex and data‐intensive plant hydraulic models. Using machine learning (ML) and eddy covariance flux tower data of 642 site years across 84 sites distributed across 10 land covers globally, here we show that structural constraints inherent in current empirical and plant hydraulic models of gsc limit their effectiveness for predicting ET. These constraints also prevent the models from fully utilizing the available hydrometeorological data at eddy covariance sites. Even if these gsc models are calibrated locally, structural simplifications inherent in them limit their capability to accurately capture gsc dynamics. In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. These results underscore the need to prioritize improvements in gsc models for more accurate ET estimation. This, in turn, will help reduce uncertainties in the assessments of plants' role in regulating the Earth's climate.
Rational combinatorial targeting by adapter CAR-T-cells (AdCAR-T) prevents antigen escape in acute myeloid leukemia
Authors: Atar Daniel , Ruoff Lara , Mast Anna-Sophia , Krost Simon , Moustafa-Oglou Moustafa , Scheuermann Sophia , Kristmann Beate , Feige Maximilian , Canak Aysegül , Wolsing Kathrin , Schlager Lennart , Schilbach Karin , Zekri Latifa , Ebinger Martin , Nixdorf Daniel , Subklewe Marion , Schulte Johannes , Lengerke Claudia , Jeremias Irmela , Werchau Niels , Mittelstaet Joerg , Lang Peter , Handgretinger Rupert , Schlegel Patrick , Seitz Christian M. 
Published: August 2024

AbstractTargeting AML by chimeric antigen receptor T-cells (CAR-T) is challenging due to the promiscuous expression of AML-associated antigens in healthy hematopoiesis and high degree of inter- and intratumoral heterogeneity. Here, we present single-cell expression data of AML-associated antigens in 30 primary pediatric AML samples. We identified CD33, CD38, CD371, IL1RAP and CD123 as the most frequently expressed. Notably, high variability was observed not only across the different patient samples but also among leukemic cells of the same patient suggesting the necessity of multiplexed targeting approaches. To address this need, we utilized our modular Adapter CAR (AdCAR) platform, enabling precise qualitative and quantitative control over CAR-T-cell function. We show highly efficient and target-specific activity for newly generated adapter molecules (AMs) against CD33, CD38, CD123, CD135 and CD371, both in vitro and in vivo. We reveal that inherent intratumoral heterogeneity in antigen expression translates into antigen escape and therapy failure to monotargeted CAR-T therapy. Further, we demonstrate in PDX models that rational combinatorial targeting by AdCAR-T-cells can cure heterogenic disease. In conclusion, we elucidate the clinical relevance of heterogeneity in antigen expression in pediatric AML and present a novel concept for precision immunotherapy by combinatorial targeting utilizing the AdCAR platform.
Enzalutamide inhibits PEX10 function and sensitizes prostate cancer cells to ROS activators
Authors: Feng Yuankang , Zhang Yu , Li Hao , Wang Tao , Lu Fubo , Liu Ruoyang , Xie Guoqing , Song Liang , Huang Budeng , Li Xiang , Ding Yinghui , Yang Jinjian , Jia Zhankui , Huang Zhenlin 
Published: August 2024

AbstractSharply increased reactive oxygen species (ROS) are thought to induce oxidative stress, damage cell structure and cause cell death; however, its role in prostate cancer remains unclear. Enzalutamide is a widely used anti-prostate cancer drug that antagonizes androgen binding with its receptor. Further exploration of the mechanism and potential application strategies of enzalutamide is crucial for the treatment of prostate cancer. Here, we confirmed PEX10 can be induced by ROS activators while reduce ROS level in prostate cancer cells, which weakened the anti-tumor effect of ROS activators. The androgen receptor (AR) can promote the expression of PEX10 by acting as an enhancer in cooperation with FOXA1. The anti-tumor drug enzalutamide inhibits PEX10 by inhibiting the function of AR, and synergize with ROS activators ML210 or RSL3 to produce a stronger anti-tumor effect, thereby sensitizing cells to ROS activators. This study reveals a previously unrecognized function of enzalutamide and AR by regulating PEX10 and suggests a new strategy of enzalutamide application in prostate cancer treatment.
Heterozygous knockout of Synaptotagmin13 phenocopies ALS features and TP53 activation in human motor neurons
Authors: Lehmann Johannes , Aly Amr , Steffke Christina , Fabbio Luca , Mayer Valentin , Dikwella Natalie , Halablab Kareen , Roselli Francesco , Seiffert Simone , Boeckers Tobias M. , Brenner David , Kabashi Edor , Mulaw Medhanie , Ho Ritchie , Catanese Alberto 
Published: August 2024

AbstractSpinal motor neurons (MNs) represent a highly vulnerable cellular population, which is affected in fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). In this study, we show that the heterozygous loss of SYT13 is sufficient to trigger a neurodegenerative phenotype resembling those observed in ALS and SMA. SYT13+/− hiPSC-derived MNs displayed a progressive manifestation of typical neurodegenerative hallmarks such as loss of synaptic contacts and accumulation of aberrant aggregates. Moreover, analysis of the SYT13+/− transcriptome revealed a significant impairment in biological mechanisms involved in motoneuron specification and spinal cord differentiation. This transcriptional portrait also strikingly correlated with ALS signatures, displaying a significant convergence toward the expression of pro-apoptotic and pro-inflammatory genes, which are controlled by the transcription factor TP53. Our data show for the first time that the heterozygous loss of a single member of the synaptotagmin family, SYT13, is sufficient to trigger a series of abnormal alterations leading to MN sufferance, thus revealing novel insights into the selective vulnerability of this cell population.
The radiative feedback continuum from Snowball Earth to an ice-free hothouse
Authors: Eisenman Ian , Armour Kyle C. 
Published: August 2024

AbstractPaleoclimate records have been used to estimate the modern equilibrium climate sensitivity. However, this requires understanding how the feedbacks governing the climate response vary with the climate itself. Here we warm and cool a state-of-the-art climate model to simulate a continuum of climates ranging from a nearly ice-covered Snowball Earth to a nearly ice-free hothouse. We find that the pre-industrial (PI) climate is near a stability optimum: warming leads to a less-stable (more-sensitive) climate, as does cooling of more than 2K. Physically interpreting the results, we find that the decrease in stability for climates colder than the PI occurs mainly due to the albedo and lapse-rate feedbacks, and the decrease in stability for warmer climates occurs mainly due to the cloud feedback. These results imply that paleoclimate records provide a stronger constraint than has been calculated in previous studies, suggesting a reduction in the uncertainty range of the climate sensitivity.
Structural basis of Cdk7 activation by dual T-loop phosphorylation
Authors: Düster Robert , Anand Kanchan , Binder Sophie C. , Schmitz Maximilian , Gatterdam Karl , Fisher Robert P. , Geyer Matthias 
Published: August 2024

AbstractCyclin-dependent kinase 7 (Cdk7) is required in cell-cycle and transcriptional regulation owing to its function as both a CDK-activating kinase (CAK) and part of transcription factor TFIIH. Cdk7 forms active complexes by associating with Cyclin H and Mat1, and is regulated by two phosphorylations in the activation segment (T loop): the canonical activating modification at T170 and another at S164. Here we report the crystal structure of the human Cdk7/Cyclin H/Mat1 complex containing both T-loop phosphorylations. Whereas pT170 coordinates basic residues conserved in other CDKs, pS164 nucleates an arginine network unique to the ternary Cdk7 complex, involving all three subunits. We identify differential dependencies of kinase activity and substrate recognition on the individual phosphorylations. CAK function is unaffected by T-loop phosphorylation, whereas activity towards non-CDK substrates is increased several-fold by T170 phosphorylation. Moreover, dual T-loop phosphorylation stimulates multisite phosphorylation of the RNA polymerase II (RNAPII) carboxy-terminal domain (CTD) and SPT5 carboxy-terminal repeat (CTR) region. In human cells, Cdk7 activation is a two-step process wherein S164 phosphorylation precedes, and may prime, T170 phosphorylation. Thus, dual T-loop phosphorylation can regulate Cdk7 through multiple mechanisms, with pS164 supporting tripartite complex formation and possibly influencing processivity, while pT170 enhances activity towards key transcriptional substrates.
A unified model for interpretable latent embedding of multi-sample, multi-condition single-cell data
Authors: Madrigal Ariel , Lu Tianyuan , Soto Larisa M. , Najafabadi Hamed S. 
Published: August 2024

AbstractSingle-cell analysis across multiple samples and conditions requires quantitative modeling of the interplay between the continuum of cell states and the technical and biological sources of sample-to-sample variability. We introduce GEDI, a generative model that identifies latent space variations in multi-sample, multi-condition single-cell datasets and attributes them to sample-level covariates. GEDI enables cross-sample cell state mapping on par with state-of-the-art integration methods, cluster-free differential gene expression analysis along the continuum of cell states, and machine learning-based prediction of sample characteristics from single-cell data. GEDI can also incorporate gene-level prior knowledge to infer pathway and regulatory network activities in single cells. Finally, GEDI extends all these concepts to previously unexplored modalities that require joint consideration of dual measurements, such as the joint analysis of exon inclusion/exclusion reads to model alternative cassette exon splicing, or spliced/unspliced reads to model the mRNA stability landscapes of single cells.
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys
Authors: Siddiqui Anas , Hine Nicholas D. M. 
Published: August 2024

AbstractMachine Learned Interatomic Potentials (MLIPs) combine the predictive power of Density Functional Theory (DFT) with the speed and scaling of interatomic potentials, enabling theoretical spectroscopy to be applied to larger and more complex systems than is possible with DFT. In this work, we train an MLIP for quaternary Transition Metal Dichalcogenide (TMD) alloy systems of the form Mo1−xWxS2−2ySe2y, using the equivariant Neural Network (NN) MACE. We demonstrate the ability of this potential to calculate vibrational properties of alloy TMDs including phonon spectra for pure monolayers, and Vibrational Density of States (VDOS) and first-order Raman spectra for alloys across the range of x and y. We show that we retain DFT level accuracy while greatly extending feasible system size and extent of sampling over alloy configurations. We are able to characterize the first-order Raman active modes across the whole range of concentration, particularly for the “disorder-induced” modes.
Transcriptomics and weighted protein network analyses of the LRRK2 protein interactome reveal distinct molecular signatures for sporadic and LRRK2 Parkinson’s Disease
Authors: Zhao Yibo , Bracher-Smith Matthew , Li Yuelin , Harvey Kirsten , Escott-Price Valentina , Lewis Patrick A. , Manzoni Claudia 
Published: August 2024

AbstractMutations in the LRRK2 gene are the most common genetic cause of familial Parkinson’s Disease (LRRK2-PD) and an important risk factor for sporadic PD (sPD). Multiple clinical trials are ongoing to evaluate the benefits associated with the therapeutical reduction of LRRK2 kinase activity. In this study, we described the changes of transcriptomic profiles (whole blood mRNA levels) of LRRK2 protein interactors in sPD and LRRK2-PD cases as compared to healthy controls with the aim of comparing the two PD conditions. We went on to model the protein-protein interaction (PPI) network centred on LRRK2, which was weighted to reflect the transcriptomic changes on expression and co-expression levels of LRRK2 protein interactors. Our results showed that LRRK2 interactors present both similar and distinct alterations in expression levels and co-expression behaviours in the sPD and LRRK2-PD cases; suggesting that, albeit being classified as the same disease based on clinical features, LRRK2-PD and sPD display significant differences from a molecular perspective. Interestingly, the similar changes across the two PD conditions result in decreased connectivity within a topological cluster of the LRRK2 PPI network associated with protein metabolism/biosynthesis and ribosomal metabolism suggesting protein homoeostasis and ribosomal dynamics might be affected in both sporadic and familial PD in comparison with controls.
A comprehensive overview of liquid biopsy applications in pediatric solid tumors
Authors: Janssen Ferdinand W. , Lak Nathalie S. M. , Janda Claudia Y. , Kester Lennart A. , Meister Michael T. , Merks Johannes H. M. , van den Heuvel-Eibrink Marry M. , van Noesel Max M. , Zsiros Jozsef , Tytgat Godelieve A. M. , Looijenga Leendert H. J. 
Published: August 2024

AbstractLiquid biopsies are emerging as an alternative source for pediatric cancer biomarkers with potential applications during all stages of patient care, from diagnosis to long-term follow-up. While developments within this field are reported, these mainly focus on dedicated items such as a specific liquid biopsy matrix, analyte, and/or single tumor type. To the best of our knowledge, a comprehensive overview is lacking. Here, we review the current state of liquid biopsy research for the most common non-central nervous system pediatric solid tumors. These include neuroblastoma, renal tumors, germ cell tumors, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma and other soft tissue sarcomas, and liver tumors. Within this selection, we discuss the most important or recent studies involving liquid biopsy-based biomarkers, anticipated clinical applications, and the current challenges for success. Furthermore, we provide an overview of liquid biopsy-based biomarker publication output for each tumor type based on a comprehensive literature search between 1989 and 2023. Per study identified, we list the relevant liquid biopsy-based biomarkers, matrices (e.g., peripheral blood, bone marrow, or cerebrospinal fluid), analytes (e.g., circulating cell-free and tumor DNA, microRNAs, and circulating tumor cells), methods (e.g., digital droplet PCR and next-generation sequencing), the involved pediatric patient cohort, and proposed applications. As such, we identified 344 unique publications. Taken together, while the liquid biopsy field in pediatric oncology is still behind adult oncology, potentially relevant publications have increased over the last decade. Importantly, steps towards clinical implementation are rapidly gaining ground, notably through validation of liquid biopsy-based biomarkers in pediatric clinical trials.
The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review
Authors: Schwabe Daniel , Becker Katinka , Seyferth Martin , Klaß Andreas , Schaeffter Tobias 
Published: August 2024

AbstractThe adoption of machine learning (ML) and, more specifically, deep learning (DL) applications into all major areas of our lives is underway. The development of trustworthy AI is especially important in medicine due to the large implications for patients’ lives. While trustworthiness concerns various aspects including ethical, transparency and safety requirements, we focus on the importance of data quality (training/test) in DL. Since data quality dictates the behaviour of ML products, evaluating data quality will play a key part in the regulatory approval of medical ML products. We perform a systematic review following PRISMA guidelines using the databases Web of Science, PubMed and ACM Digital Library. We identify 5408 studies, out of which 120 records fulfil our eligibility criteria. From this literature, we synthesise the existing knowledge on data quality frameworks and combine it with the perspective of ML applications in medicine. As a result, we propose the METRIC-framework, a specialised data quality framework for medical training data comprising 15 awareness dimensions, along which developers of medical ML applications should investigate the content of a dataset. This knowledge helps to reduce biases as a major source of unfairness, increase robustness, facilitate interpretability and thus lays the foundation for trustworthy AI in medicine. The METRIC-framework may serve as a base for systematically assessing training datasets, establishing reference datasets, and designing test datasets which has the potential to accelerate the approval of medical ML products.
Optimizing green and gray infrastructure planning for sustainable urban development
Authors: van Oorschot Janneke , Slootweg Mike , Remme Roy P. , Sprecher Benjamin , van der Voet Ester 
Published: August 2024

AbstractThe anticipated increase in urban population of 2.5 billion people by 2050 poses significant environmental challenges. While the various environmental impacts of urbanisation have been studied individually, integrated approaches are rare. This study introduces a spatially explicit model to assess urbanization’s effects on ecosystem services (green infrastructure availability, cooling, stormwater retention) and the environmental impact of building construction (material demand, greenhouse gas emissions, land use). Applied to the Netherlands from 2018 to 2050, our results show that integrating green infrastructure development with building construction could increase green areas by up to 5% and stabilize or increase ecosystem service provisioning. Dense building construction with green infrastructure development is generally more beneficial across the Netherlands, reducing resource use and enhancing ecosystem services. Conversely, sparse construction with green infrastructure is more advantageous for newly built areas. These findings offer insights into the environmental consequences of urbanization, guiding sustainable urban planning practices.
The increase of an allelopathic and unpalatable plant undermines reindeer pasture quality and current management in the Norwegian tundra
Authors: Tuomi Maria W. , Utsi Tove Aagnes , Yoccoz Nigel Gilles , Armstrong Claire W. , Gonzalez Victoria , Hagen Snorre B. , Jónsdóttir I. S. , Pugnaire Francisco I. , Shea Katriona , Wardle David A. , Zielosko Sophia , Bråthen Kari Anne 
Published: August 2024

AbstractOngoing Arctic greening can increase productivity and reindeer pasture quality in the tundra. However, greening may also entail proliferation of unpalatable species, with consequences for pastoral social-ecological systems. Here we show extensive greening across 20 reindeer districts in Norway between 2003 and 2020, which has reduced pasture diversity. The allelopathic, evergreen dwarf-shrub crowberry increased its biomass by 60%, with smaller increases of deciduous shrubs and no increase in forbs and graminoids, the most species rich growth forms. There was no evidence for higher reindeer densities promoting crowberry. The current management decision-making process aims at sustainable pasture management but does not explicitly account for pasture changes and reduced diversity. Large-scale shifts towards evergreening and increased allelopathy may thus undermine the resource base for this key Arctic herbivore and the pastoral social-ecological system. Management that is sensitive to changes in pasture diversity could avoid mismanagement of a social-ecological system in transition.
Synergistic atmosphere-ocean-ice influences have driven the 2023 all-time Antarctic sea-ice record low
Authors: Wang Jinfei , Massonnet François , Goosse Hugues , Luo Hao , Barthélemy Antoine , Yang Qinghua 
Published: August 2024

AbstractAntarctic sea ice extent (SIE) reached a new record low in February 2023. Here we examine the evolution of the coupled ocean-atmosphere-sea ice system during the 12 months preceding the record. The impact of preceding conditions is assessed with observations, reanalyses, and output from the regional ocean-sea ice coupled model NEMO3.6-LIM3. We find that the 2022-2023 sea ice annual cycle was characterized by consistently low SIE throughout the year, anomalously rapid sea ice retreat in December 2022, and nearly circumpolar negative SIE anomalies in February 2023. While advection-induced positive air temperature anomalies inhibited the sea ice growth in most regions, strong southerly winds in the Amundsen-Ross Sea caused by an anomalously deep Amundsen Sea Low in spring transported notable volumes of sea ice northward, triggering an unusually active ice-albedo feedback onshore and favoring accelerated melt towards the minimum. This study highlights the impacts of multifactorial processes during the preceding seasons to explain the recent summer sea ice minima.
Interlayer ionic diffusion driven in situ QD-deposition in the Co9S8–LDH hybrid supercapacitor electrode
Authors: Zhang Yanan , Xu Nuo , Xu Jipeng , Shan Chi , Chen Junlei , Guo Liyuan , Qin Long , Wu Fan , Huang Wenhuan 
Published: August 2024

QDs-Co9S8/CoNi-LDH was assembled by selective sulfurization derived from 2D MOF with the loading of Co9S8 quantum dots into layered double hydroxides. The constructed hybrid supercapacitor shown energy density of 33.3 Wh kg−1 at 820.0 W kg−1.