bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rock Typing and Reservoir Quality Analysis of the Abu Madi Reservoir: Distribution Prediction Using Artificial Neural Networks in the West El Manzala Area, Onshore Nile Delta, Egypt
Authors: Elmaadawy Khaled Gamal , El Hassan Mohamed Mahmoud Abu , Sallam Ahmed Mashhout 
Published: November 2023

AbstractIn the Nile Delta gas province of Egypt, the Abu Madi Formation is the most promising sandstone gas reservoir. This study aimed to investigate reservoir rock typing and quality by integrating petrophysical and petrographical data, including well logs, image logs, and cores. Furthermore, it sought to predict the permeability and reservoir quality of uncored wells by integrating artificial neural network technique with core analysis data and evaluate the effectiveness of this approach as an exploration tool in the West El Manzala area. The core petrography revealed the presence of microfacies consisting of arenites and wackes. The measured porosity, permeability, and pore sizes obtained from the cores, along with the parameters of the reservoir quality index, normalized porosity, and flow zone indicator, indicated that the Abu Madi reservoirs could be subdivided into three categories based on reservoir quality. High reservoir quality (RT-I) is characterized by megapores within the hydraulic flow unit (HFU-1) associated with bioturbated coarse to gravelly sandstone facies. Moderate reservoir quality (RT-II) is characterized by macropores within the hydraulic flow unit (HFU)-II associated with massive coarse to gravelly sandstone facies. Poor reservoir quality (RT-III) was characterized by mesopores within the HFU-III hydraulic flow unit related to laminated silty mudstone facies. The findings of this study demonstrate that the combination of reservoir rock typing and artificial neural networks is an extremely successful method for petroleum exploration in the West El Manzala region.
A note on 1-parameter stable unfoldings
Authors: Breva Ribes I. , Oset Sinha R. 
Published: November 2023

AbstractWe give two characterisations of when a map-germ admits a 1-parameter stable unfolding, one related to the $${\mathscr {K}}_e$$

K
e

-codimension and another related to the normal form of a versal unfolding. We then prove that there are infinitely many finitely determined map-germs of multiplicity 4 from $${\mathbb {K}}^3$$

K

3

to $${\mathbb {K}}^3$$

K

3

which do not admit a 1-parameter stable unfolding.
Post-truth and scientific authority
Authors: Benetka Gerhard , Schor-Tschudnowskaja Anna 
Published: November 2023

AbstractPost-truth refers to a social situation in which trust in clear and solid knowledge has been shaken, even though the ‘demand’ or ‘need’ for such solid knowledge has not diminished. This contradictory situation is particularly evident in the way in which science appears in public: on the one hand, expertise is transformed into a set of opinions that can be shared or not shared, as political decision-making seeks to legitimise itself more and more through ‘experts’. On the other hand, in times of crisis or rapid social change in general, the call for the replacement of politics by science grows louder: to bring the pandemic under control, virologists are supposed to say what measures should be taken to restrict individual freedoms. Such scientification of politics ultimately affects both fields, so that the fact that politics and science follow different functional principles is no longer recognised on either side: ‘evidence-based’ politics forgets that the political field is about balancing interests and setting values. In our article, however, we ask about the connection of this paradoxical situation with ‘the’ scientific practice itself: to what extent has science itself contributed to this strangely contradictory social role of its production of knowledge? And how does it seek to address the crisis of post-truth?
Global Distribution of Relativistic Electron Precipitation and the Dependences on Substorm Injection and Solar Wind Ram Pressure: Long‐Term POES Observations
Authors: Chen Huayue , Gao Xinliang , Lu Quanming , Tsurutani Bruce T. 
Published: November 2023

AbstractRelativistic electron precipitation (REP) into the Earth's atmosphere is one of the fundamental mechanisms causing radiation belt electron flux dropout. It is important to know the preferred regions of REP events and the interplanetary and magnetospheric conditions under which the events take place. In this study of the POES relativistic electron data during 1998–2017, we have examined all REP events from L = 3–10 using an automatic algorithm. The REP events preferentially occur in MLT = 17–03 at L = 4–6.5, where the precipitation fluxes also peak. The monthly average REP event number is correlated with both monthly average AE (auroral electrojet index) and Pd (solar wind ram pressure) indices, so we separately investigate the spatial dependences of the events on one index by restricting the other one to a low level. The occurrence rate of REP events increases with both the AE* and the indices (where AE* and are time‐modified from the AE and Pd indices). During large AE* but low , the events occur mainly in the dusk sector (MLT = 17–22) near the plasmapause. For large but low AE* intervals, most of the events occur outside the plasmapause in the midnight sector (MLT = 23–03). Possible REP loss mechanisms are discussed based on our findings. Our study provides new insights into the distribution and dependences of REP in the Earth's magnetosphere.
Fungal antigenic variation using mosaicism and reassortment of subtelomeric genes’ repertoires
Authors: Meier Caroline S. , Pagni Marco , Richard Sophie , Mühlethaler Konrad , Almeida João M. G. C. F. , Nevez Gilles , Cushion Melanie T. , Calderón Enrique J. , Hauser Philippe M. 
Published: November 2023

AbstractSurface antigenic variation is crucial for major pathogens that infect humans. To escape the immune system, they exploit various mechanisms. Understanding these mechanisms is important to better prevent and fight the deadly diseases caused. Those used by the fungus Pneumocystis jirovecii that causes life-threatening pneumonia in immunocompromised individuals remain poorly understood. Here, though this fungus is currently not cultivable, our detailed analysis of the subtelomeric sequence motifs and genes encoding surface proteins suggests that the system involves the reassortment of the repertoire of ca. 80 non-expressed genes present in each strain, from which single genes are retrieved for mutually exclusive expression. Dispersion of the new repertoires, supposedly by healthy carrier individuals, appears very efficient because identical alleles are observed in patients from different countries. Our observations reveal a unique strategy of antigenic variation. They also highlight the possible role in genome rearrangements of small imperfect mirror sequences forming DNA triplexes.
Deep brain stimulation of thalamic nucleus reuniens promotes neuronal and cognitive resilience in an Alzheimer’s disease mouse model
Authors: Shoob Shiri , Buchbinder Nadav , Shinikamin Ortal , Gold Or , Baeloha Halit , Langberg Tomer , Zarhin Daniel , Shapira Ilana , Braun Gabriella , Habib Naomi , Slutsky Inna 
Published: November 2023

AbstractThe mechanisms that confer cognitive resilience to Alzheimer’s Disease (AD) are not fully understood. Here, we describe a neural circuit mechanism underlying this resilience in a familial AD mouse model. In the prodromal disease stage, interictal epileptiform spikes (IESs) emerge during anesthesia in the CA1 and mPFC regions, leading to working memory disruptions. These IESs are driven by inputs from the thalamic nucleus reuniens (nRE). Indeed, tonic deep brain stimulation of the nRE (tDBS-nRE) effectively suppresses IESs and restores firing rate homeostasis under anesthesia, preventing further impairments in nRE-CA1 synaptic facilitation and working memory. Notably, applying tDBS-nRE during the prodromal phase in young APP/PS1 mice mitigates age-dependent memory decline. The IES rate during anesthesia in young APP/PS1 mice correlates with later working memory impairments. These findings highlight the nRE as a central hub of functional resilience and underscore the clinical promise of DBS in conferring resilience to AD pathology by restoring circuit-level homeostasis.
Evidence for ground state coherence in a two-dimensional Kondo lattice
Authors: Wan Wen , Harsh Rishav , Meninno Antonella , Dreher Paul , Sajan Sandra , Guo Haojie , Errea Ion , de Juan Fernando , Ugeda Miguel M. 
Published: November 2023

AbstractKondo lattices are ideal testbeds for the exploration of heavy-fermion quantum phases of matter. While our understanding of Kondo lattices has traditionally relied on complex bulk f-electron systems, transition metal dichalcogenide heterobilayers have recently emerged as simple, accessible and tunable 2D Kondo lattice platforms where, however, their ground state remains to be established. Here we present evidence of a coherent ground state in the 1T/1H-TaSe2 heterobilayer by means of scanning tunneling microscopy/spectroscopy at 340 mK. Our measurements reveal the existence of two symmetric electronic resonances around the Fermi energy, a hallmark of coherence in the spin lattice. Spectroscopic imaging locates both resonances at the central Ta atom of the charge density wave of the 1T phase, where the localized magnetic moment is held. Furthermore, the evolution of the electronic structure with the magnetic field reveals a non-linear increase of the energy separation between the electronic resonances. Aided by ab initio and auxiliary-fermion mean-field calculations, we demonstrate that this behavior is inconsistent with a fully screened Kondo lattice, and suggests a ground state with magnetic order mediated by conduction electrons. The manifestation of magnetic coherence in TMD-based 2D Kondo lattices enables the exploration of magnetic quantum criticality, Kondo breakdown transitions and unconventional superconductivity in the strict two-dimensional limit.
Structural basis for stabilisation of the RAD51 nucleoprotein filament by BRCA2
Authors: Appleby Robert , Joudeh Luay , Cobbett Katie , Pellegrini Luca 
Published: November 2023

AbstractThe BRCA2 tumour suppressor protein preserves genomic integrity via interactions with the DNA-strand exchange RAD51 protein in homology-directed repair. The RAD51-binding TR2 motif at the BRCA2 C-terminus is essential for protection and restart of stalled replication forks. Biochemical evidence shows that TR2 recognises filamentous RAD51, but existing models of TR2 binding to RAD51 lack a structural basis. Here we used cryo-electron microscopy and structure-guided mutagenesis to elucidate the mechanism of TR2 binding to nucleoprotein filaments of human RAD51. We find that TR2 binds across the protomer interface in the filament, acting as a brace for adjacent RAD51 molecules. TR2 targets an acidic-patch motif on human RAD51 that serves as a recruitment hub in fission yeast Rad51 for recombination mediators Rad52 and Rad55-Rad57. Our findings provide a structural rationale for RAD51 filament stabilisation by BRCA2 and reveal a common recruitment mechanism of recombination mediators to the RAD51 filament.
Subjective data models in bioinformatics and how wet lab and computational biologists conceptualise data
Authors: Yehudi Yo , Hughes-Noehrer Lukas , Goble Carole , Jay Caroline 
Published: November 2023

AbstractBiological science produces “big data” in varied formats, which necessitates using computational tools to process, integrate, and analyse data. Researchers using computational biology tools range from those using computers for communication, to those writing analysis code. We examine differences in how researchers conceptualise the same data, which we call “subjective data models”. We interviewed 22 people with biological experience and varied levels of computational experience, and found that many had fluid subjective data models that changed depending on circumstance. Surprisingly, results did not cluster around participants’ computational experience levels. People did not consistently map entities from abstract data models to the real-world entities in files, and certain data identifier formats were easier to infer meaning from than others. Real-world implications: 1) software engineers should design interfaces for task performance, emulating popular user interfaces, rather than targeting professional backgrounds; 2) when insufficient context is provided, people may guess what data means, whether or not they are correct, emphasising the importance of contextual metadata to remove the need for erroneous guesswork.
Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms
Authors: Pemberton Hugh G. , Wu Jiaming , Kommers Ivar , Müller Domenique M. J. , Hu Yipeng , Goodkin Olivia , Vos Sjoerd B. , Bisdas Sotirios , Robe Pierre A. , Ardon Hilko , Bello Lorenzo , Rossi Marco , Sciortino Tommaso , Nibali Marco Conti , Berger Mitchel S. , Hervey-Jumper Shawn L. , Bouwknegt Wim , Van den Brink Wimar A. , Furtner Julia , Han Seunggu J. , Idema Albert J. S. , Kiesel Barbara , Widhalm Georg , Kloet Alfred , Wagemakers Michiel , Zwinderman Aeilko H. , Krieg Sandro M. , Mandonnet Emmanuel , Prados Ferran , de Witt Hamer Philip , Barkhof Frederik , Eijgelaar Roelant S. 
Published: November 2023

AbstractThis study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVIDIA-net (nv-Net) were trained and tested using manual segmentations from preoperative MRI of glioblastoma (GBM) and low-grade gliomas (LGG) from the BraTS 2021 dataset (1251 in total), in addition to 275 GBM and 205 LGG acquired clinically across 12 hospitals worldwide. Data was split into 80% training, 5% validation, and 15% internal test data. An additional external test-set of 158 GBM and 69 LGG was used to assess generalisability to other hospitals’ data. All models’ median Dice similarity coefficient (DSC) for both test sets were within, or higher than, previously reported human inter-rater agreement (range of 0.74–0.85). For both test sets, nn-Unet achieved the highest DSC (internal = 0.86, external = 0.93) and the lowest Hausdorff distances (10.07, 13.87 mm, respectively) for all tumor classes (p < 0.001). By applying Sparsified training, missing MRI sequences did not statistically affect the performance. nn-Unet achieves accurate segmentations in clinical settings even in the presence of incomplete MRI datasets. This facilitates future clinical adoption of automated glioma segmentation, which could help inform treatment planning and glioma monitoring.
Incidence and risk of pancreatic cancer in patients with acute or chronic pancreatitis: a population-based cohort study
Authors: Park Seon Mee , Kim Ki Bae , Han Joung-Ho , Kim Nayoung , Kang Tae Uk , Swan Heather , Kim Hyun Jung 
Published: November 2023

AbstractWe aimed to evaluate the incidence and risk of pancreatic cancer (PC) in pancreatitis. We identified patients with acute pancreatitis (AP) (n = 225,811, 50.0%) and chronic pancreatitis (CP) (n = 225,685, 50.0%) from Korean population-based data and matched them with age- and sex-matched controls (n = 4,514,960). We analyzed the incidence and adjusted hazard ratios (aHRs) of PC among patients followed for more than 2 years or 5 years, and assessed risk changes over time in single episode of AP (SAP), recurrent AP (RAP), CP with AP, and CP without AP groups. We also performed subgroup analysis for both sexes. The incidences (per 104 person-years) and risks (aHR) of PC were higher in the RAP (12.69, 5.00) or CP with AP (12.12, 5.74) groups compared to the SAP (2.31, 1.32) or CP without AP (2.28, 1.57) groups. The risks of PC decreased over time, however, the risk of PC remained elevated in the RAP and CP with AP groups for more than 8 years. Females with RAP, SAP, and CP with AP had higher risks of PC than males. The risk of PC is higher and persists for longer duration in patients with RAP and CP with AP compared to those with SAP or CP without AP.
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
Authors: Helland Ragnhild Holden , Ferles Alexandros , Pedersen André , Kommers Ivar , Ardon Hilko , Barkhof Frederik , Bello Lorenzo , Berger Mitchel S. , Dunås Tora , Nibali Marco Conti , Furtner Julia , Hervey-Jumper Shawn , Idema Albert J. S. , Kiesel Barbara , Tewari Rishi Nandoe , Mandonnet Emmanuel , Müller Domenique M. J. , Robe Pierre A. , Rossi Marco , Sagberg Lisa M. , Sciortino Tommaso , Aalders Tom , Wagemakers Michiel , Widhalm Georg , Witte Marnix G. , Zwinderman Aeilko H. , Majewska Paulina L. , Jakola Asgeir S. , Solheim Ole , Hamer Philip C. De Witt , Reinertsen Ingerid , Eijgelaar Roelant S. , Bouget David 
Published: November 2023

AbstractExtent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.
Comparative transcriptome analysis reveals candidate genes for cold stress response and early flowering in pineapple
Authors: Yow Ashley G. , Laosuntisuk Kanjana , Young Roberto A. , Doherty Colleen J. , Gillitt Nicholas , Perkins-Veazie Penelope , Jenny Xiang Qiu-Yun , Iorizzo Massimo 
Published: November 2023

AbstractPineapple originates from tropical regions in South America and is therefore significantly impacted by cold stress. Periodic cold events in the equatorial regions where pineapple is grown may induce early flowering, also known as precocious flowering, resulting in monetary losses due to small fruit size and the need to make multiple passes for harvesting a single field. Currently, pineapple is one of the most important tropical fruits in the world in terms of consumption, and production losses caused by weather can have major impacts on worldwide exportation potential and economics. To further our understanding of and identify mechanisms for low-temperature tolerance in pineapple, and to identify the relationship between low-temperature stress and flowering time, we report here a transcriptomic analysis of two pineapple genotypes in response to low-temperature stress. Using meristem tissue collected from precocious flowering-susceptible MD2 and precocious flowering-tolerant Dole-17, we performed pairwise comparisons and weighted gene co-expression network analysis (WGCNA) to identify cold stress, genotype, and floral organ development-specific modules. Dole-17 had a greater increase in expression of genes that confer cold tolerance. The results suggested that low temperature stress in Dole-17 plants induces transcriptional changes to adapt and maintain homeostasis. Comparative transcriptomic analysis revealed differences in cuticular wax biosynthesis, carbohydrate accumulation, and vernalization-related gene expression between genotypes. Cold stress induced changes in ethylene and abscisic acid-mediated pathways differentially between genotypes, suggesting that MD2 may be more susceptible to hormone-mediated early flowering. The differentially expressed genes and module hub genes identified in this study are potential candidates for engineering cold tolerance in pineapple to develop new varieties capable of maintaining normal reproduction cycles under cold stress. In addition, a total of 461 core genes involved in the development of reproductive tissues in pineapple were also identified in this study. This research provides an important genomic resource for understanding molecular networks underlying cold stress response and how cold stress affects flowering time in pineapple.
Two-stage multi-objective optimization for ICU bed allocation under multiple sources of uncertainty
Authors: Wan Fang , Fondrevelle Julien , Wang Tao , Duclos Antoine 
Published: November 2023

AbstractDue to the impact of COVID-19, a significant influx of emergency patients inundated the intensive care unit (ICU), and as a result, the treatment of elective patients was postponed or even cancelled. This paper studies ICU bed allocation for three categories of patients (emergency, elective, and current ICU patients). A two-stage model and an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to obtain ICU bed allocation. In the first stage, bed allocation is examined under uncertainties regarding the number of emergency patients and their length of stay (LOS). In the second stage, in addition to including the emergency patients with uncertainties in the first stage, it also considers uncertainty in the LOS of elective and current ICU patients. The two-stage model aims to minimize the number of required ICU beds and maximize resource utilization while ensuring the admission of the maximum number of patients. To evaluate the effectiveness of the model and algorithm, the improved NSGA-II was compared with two other methods: multi-objective simulated annealing (MOSA) and multi-objective Tabu search (MOTS). Drawing on data from real cases at a hospital in Lyon, France, the NSGA-II, while catering to patient requirements, saves 9.8% and 5.1% of ICU beds compared to MOSA and MOTS. In five different scenarios, comparing these two algorithms, NSGA-II achieved average improvements of 0%, 49%, 11.4%, 9.5%, and 17.1% across the five objectives.
Hydroclimate variability in the central Mediterranean during MIS 17 interglacial (Middle Pleistocene) highlights timing offset with monsoon activity
Authors: Capraro Luca , Incarbona Alessandro , Fornaciari Eliana , Sabatino Nadia , Scaillet Stéphane , Sprovieri Rodolfo , Sprovieri Mario 
Published: November 2023

AbstractMediterranean climates are characterized by warm, dry summers and mild, rainy winters. Previous studies suggest that over the last 1.36 Myr, Mediterranean winter rainfalls were in phase with the African monsoon. Here we present a high-resolution terrestrial and marine dataset for the Marine Isotope Stage 17 interglacial (Middle Pleistocene) from Southern Italy, showing that precipitation rates and regimes in the central Mediterranean varied independently of the monsoon system. Specifically, events of extreme summer precipitation were promoted by increased regional insolation rates and/or extratropical cyclones, and their magnitude was further enhanced by the advection of cool and humid North Atlantic air during stadials. Our findings provide new information on the short- to mid-term natural hydroclimatic variability of the Mediterranean basin, and offer new critical insights on land–ocean interactions at the regional scale by complementing previous analyses on the displacement of storm tracks toward southern Europe.