bluuebunny/crossref_metadata_2025_split huggingface dataset:
Translation of monosynaptic circuits underlying amygdala fMRI neurofeedback training
Authors: Trambaiolli Lucas , Maffei Chiara , Dann Evan , Biazoli Jr Claudinei , Bezgin Gleb , Yendiki Anastasia , Haber Suzanne 
Published: August 2024

AbstractfMRI neurofeedback using autobiographical memory recall to upregulate the amygdala is associated with resting-state functional connectivity (rsFC) changes between the amygdala and the salience and default mode networks (SN and DMN, respectively). We hypothesize the existence of anatomical circuits underlying these rsFC changes. Using a cross-species brain parcellation, we identified in non-human primates locations homologous to the regions of interest (ROIs) from studies showing pre-to-post-neurofeedback changes in rsFC with the left amygdala. We injected bidirectional tracers in the basolateral, lateral, and central amygdala nuclei of adult macaques and used bright- and dark-field microscopy to identify cells and axon terminals in each ROI (SN: anterior cingulate, ventrolateral, and insular cortices; DMN: temporal pole, middle frontal gyrus, angular gyrus, precuneus, posterior cingulate cortex, parahippocampal gyrus, hippocampus, and thalamus). We also performed additional injections in specific ROIs to validate the results following amygdala injections and delineate potential disynaptic pathways. Finally, we used high-resolution diffusion MRI data from four post-mortem macaque brains and one in vivo human brain to translate our findings to the neuroimaging domain. Different amygdala nuclei had significant monosynaptic connections with all the SN and DMN ipsilateral ROIs. Amygdala connections with the DMN contralateral ROIs are disynaptic through the hippocampus and parahippocampal gyrus. Diffusion MRI in both species benefitted from using the ground-truth tracer data to validate its findings, as we identified false-negative ipsilateral and false-positive contralateral connectivity results. This study provides the foundation for future causal investigations of amygdala neurofeedback modulation of the SN and DMN through these anatomic connections.
Glycosylation: mechanisms, biological functions and clinical implications
Authors: He Mengyuan , Zhou Xiangxiang , Wang Xin 
Published: August 2024

AbstractProtein post-translational modification (PTM) is a covalent process that occurs in proteins during or after translation through the addition or removal of one or more functional groups, and has a profound effect on protein function. Glycosylation is one of the most common PTMs, in which polysaccharides are transferred to specific amino acid residues in proteins by glycosyltransferases. A growing body of evidence suggests that glycosylation is essential for the unfolding of various functional activities in organisms, such as playing a key role in the regulation of protein function, cell adhesion and immune escape. Aberrant glycosylation is also closely associated with the development of various diseases. Abnormal glycosylation patterns are closely linked to the emergence of various health conditions, including cancer, inflammation, autoimmune disorders, and several other diseases. However, the underlying composition and structure of the glycosylated residues have not been determined. It is imperative to fully understand the internal structure and differential expression of glycosylation, and to incorporate advanced detection technologies to keep the knowledge advancing. Investigations on the clinical applications of glycosylation focused on sensitive and promising biomarkers, development of more effective small molecule targeted drugs and emerging vaccines. These studies provide a new area for novel therapeutic strategies based on glycosylation.
Fatty acid metabolism-related enzymes in colorectal cancer metastasis: from biological function to molecular mechanism
Authors: Li Biao , Mi Jing , Yuan Qi 
Published: August 2024

AbstractColorectal cancer (CRC) is a highly aggressive and life-threatening malignancy that metastasizes in ~50% of patients, posing significant challenges to patient survival and treatment. Fatty acid (FA) metabolism regulates proliferation, immune escape, metastasis, angiogenesis, and drug resistance in CRC. FA metabolism consists of three pathways: de novo synthesis, uptake, and FA oxidation (FAO). FA metabolism-related enzymes promote CRC metastasis by regulating reactive oxygen species (ROS), matrix metalloproteinases (MMPs), angiogenesis and epithelial-mesenchymal transformation (EMT). Mechanistically, the PI3K/AKT/mTOR pathway, wnt/β-catenin pathway, and non-coding RNA signaling pathway are regulated by crosstalk of enzymes related to FA metabolism. Given the important role of FA metabolism in CRC metastasis, targeting FA metabolism-related enzymes and their signaling pathways is a potential strategy to treat CRC metastasis.
Integrating fire safety into bridge design is essential for resilient infrastructure
Authors: Franchini Andrea , Barake Bosibori , Galasso Carmine , Moreyra Garlock Maria E. , Mulligan Joseph , Quiel Spencer , Torero Jose L. 
Published: August 2024

AbstractThe frequent occurrences of bridge fires and the substantial disruptions and direct/indirect economic losses resulting from these events highlight the immediate need for effective fire-safety-oriented design of new bridges and retrofit approaches for vulnerable existing bridges. In this Perspective, we discuss why a holistic engineering approach integrating innovative fire analysis methods and structural design/retrofit strategies into multi-hazard and future-oriented risk modeling frameworks represents the way forward to more sustainable and resilient infrastructure in an uncertain and rapidly changing built environment.
Deciphering the genetics and mechanisms of predisposition to multiple myeloma
Authors: Went Molly , Duran-Lozano Laura , Halldorsson Gisli H. , Gunnell Andrea , Ugidos-Damboriena Nerea , Law Philip , Ekdahl Ludvig , Sud Amit , Thorleifsson Gudmar , Thodberg Malte , Olafsdottir Thorunn , Lamarca-Arrizabalaga Antton , Cafaro Caterina , Niroula Abhishek , Ajore Ram , Lopez de Lapuente Portilla Aitzkoa , Ali Zain , Pertesi Maroulio , Goldschmidt Hartmut , Stefansdottir Lilja , Kristinsson Sigurdur Y. , Stacey Simon N. , Love Thorvardur J. , Rognvaldsson Saemundur , Hajek Roman , Vodicka Pavel , Pettersson-Kymmer Ulrika , Späth Florentin , Schinke Carolina , Van Rhee Frits , Sulem Patrick , Ferkingstad Egil , Hjorleifsson Eldjarn Grimur , Mellqvist Ulf-Henrik , Jonsdottir Ingileif , Morgan Gareth , Sonneveld Pieter , Waage Anders , Weinhold Niels , Thomsen Hauke , Försti Asta , Hansson Markus , Juul-Vangsted Annette , Thorsteinsdottir Unnur , Hemminki Kari , Kaiser Martin , Rafnar Thorunn , Stefansson Kari , Houlston Richard , Nilsson Björn 
Published: August 2024

AbstractMultiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.
Imprints of massive black-hole binaries on neighbouring decihertz gravitational-wave sources
Authors: Stegmann Jakob , Zwick Lorenz , Vermeulen Sander M. , Antonini Fabio , Mayer Lucio 
Published: August 2024

AbstractThe most massive black holes in our Universe form binaries at the centre of merging galaxies. The recent evidence for a gravitational-wave (GW) background from pulsar timing may constitute the first observation that these supermassive black-hole binaries (SMBHBs) merge. Yet, the most massive SMBHBs are out of reach of interferometric GW detectors and are exceedingly difficult to resolve individually with pulsar timing. These limitations call for unexplored strategies to detect individual SMBHBs in the uncharted frequency band ≲10−5 Hz to establish their abundance and decipher the coevolution with their host galaxies. Here we show that SMBHBs imprint detectable long-term modulations on GWs from stellar-mass binaries residing in the same galaxy at a distance d ≲ 1 kpc. We determine that proposed decihertz GW interferometers sensitive to numerous stellar-mass binaries could uncover modulations from ~O(10−1–104) SMBHBs with masses ~O(107–108) M⊙out to redshift z ≈ 3.5. This offers a unique opportunity to map the population of SMBHBs through cosmic time, which might remain inaccessible otherwise.
Quantum confinement-induced anti-electrooxidation of metallic nickel electrocatalysts for hydrogen oxidation
Authors: Zhou Yuanyuan , Yuan Wei , Li Mengting , Xie Zhenyang , Song Xiaoyun , Yang Yang , Wang Jian , Li Li , Ding Wei , Lin Wen-Feng , Wei Zidong 
Published: August 2024

AbstractThe anion-exchange-membrane fuel cell (AEMFC) is an attractive and cost-effective energy-conversion technology because it can use Earth-abundant and low-cost non-precious metal catalysts. However, non-precious metals used in AEMFCs to catalyse the hydrogen oxidation reaction are prone to self-oxidation, resulting in irreversible failure. Here we show a quantum well-like catalytic structure (QWCS), constructed by atomically confining Ni nanoparticles within a carbon-doped-MoOx/MoOx heterojunction (C-MoOx/MoOx) that can selectively transfer external electrons from the hydrogen oxidation reaction while remaining itself metallic. Electrons of Ni nanoparticles gain a barrier of 1.11 eV provided by the QWCS leading to Ni stability up to 1.2 V versus the reversible hydrogen electrode (VRHE) whereas electrons released from the hydrogen oxidation reaction easily cross the barrier by a gating operation of QWCS upon hydrogen adsorption. The QWCS-catalysed AEMFC achieved a high-power density of 486 mW mgNi−1 and withstood hydrogen starvation operations during shutdown–start cycles, whereas a counterpart AEMFC without QWCS failed in a single cycle.
Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance
Authors: Zhang Jason Z. , Ong Shao-En , Baker David , Maly Dustin J. 
Published: August 2024

AbstractClinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.
Geometric deep learning of protein–DNA binding specificity
Authors: Mitra Raktim , Li Jinsen , Sagendorf Jared M. , Jiang Yibei , Cohen Ari S. , Chiu Tsu-Pei , Glasscock Cameron J. , Rohs Remo 
Published: August 2024

AbstractPredicting protein–DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein–DNA complexes usually exhibit binding to a selected DNA target site, whereas a protein binds, with varying degrees of binding specificity, to a wide range of DNA sequences. This information is not directly accessible in a single structure. Here, to access this information, we present Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict binding specificity from protein–DNA structure. DeepPBS can be applied to experimental or predicted structures. Interpretable protein heavy atom importance scores for interface residues can be extracted. When aggregated at the protein residue level, these scores are validated through mutagenesis experiments. Applied to designed proteins targeting specific DNA sequences, DeepPBS was demonstrated to predict experimentally measured binding specificity. DeepPBS offers a foundation for machine-aided studies that advance our understanding of molecular interactions and guide experimental designs and synthetic biology.
Phosphorus fertilization enhanced overwintering, root system and forage yield of late-seeded alfalfa in sodic soils
Authors: Wang Yuntao , Xie Jihong , Fan Fan , Sun Zhen , Yuan Feng , Wang Qiqi , Yu Linqing , Liu Yaling , Li Jie , Cui Lele 
Published: August 2024

AbstractSowing date and soil fertility are very important factors in the overwintering and production performance of alfalfa (Medicago sativa L.), yet there’s a knowledge gap in knowledge on how late-seeded alfalfa responds to phosphorus (P) fertilization. A field study was conducted in Inner Mongolia from 2020 to 2022 using a split-plot design. The main plots consisted of five sowing dates (31 July, 8, 16, and 24 August, and 1 September), while the subplots involved five P application rates (0, 40, 70, 100, and 130 kg P2O5 ha−1). Throughout the growing seasons, the overwintering rate, root traits, forage yield, and yield components were measured. The results revealed a consistent decrease in overwintering ability and productivity with the delayed sowing. This reduction in overwintering rate was mainly due to diminished root traits, while the decrease in forage yield was largely associated with a reduction in plants per square meter. However, P fertilizer application to late-seeded alfalfa demonstrated potential in enhancing the diameter of both the crown and taproot, thus strengthening the root system and improving the overwintering rate, the rate of increase ranges from 11.6 to 49%. This adjustment could also improve the shoots per square meter and mass per shoot, increasing by 9.4–31.3% and 15.0–27.1% respectively in 2 years, which can offset the decline in forage yield caused by late sowing and might even increase the forage yield. Regression and path analysis indicated that alfalfa forage yield is primarily affected by mass per shoot rather than shoots per square meter. This study recommended that the sowing of alfalfa in similar regions of Inner Mongolia should not be later than mid-August. Moreover, applying P fertilizer (P2O5) at 70.6–85.9 kg ha−1 can enhance the forage yield and persistence of late-seeded alfalfa. Therefore, appropriate late sowing combined with the application of P fertilizer can be used as an efficient cultivation strategy for alfalfa cultivation after a short-season crop harvest in arid and cold regions.
Immune response, oxidative stress, and histological changes of Wistar rats after being administered with Parascaris equorum antigen
Authors: Yehia Salma Adel , Badr Abeer Mahmoud , Bashtar Abdel-Rahman , Ibrahim Mahmoud Abdel-Aziz , Mousa Mohamed Refat , Mostafa Nesma Abbas 
Published: August 2024

AbstractWorldwide, particularly in developing nations, helminth infections are the leading causes of livestock illness and mortality. Parascaris (P.) equorum, a parasitic worm from the Ascarididae family, significantly impacts the production, health, and working performance of equines. This study aimed to investigate the impact of intraperitoneal sensitization of P. equorum on the immune system, oxidative stress, and histology in Wistar rats. After acclimatization for 7 days, we divided the rats into five groups, each consisting of six rats. Group I, serving as the control, was administered distilled water, followed by groups II (day 7), III (day 14), IV (day 21), and V (day 33). The rats were euthanized every day mentioned (Days 7–33). On day 0, a dosage of 1ml/100 gm rat (containing 500 μg/ml protein content) emulsified crude antigen extract with an incomplete Freund’s adjuvant (1:1 volume), followed by a second dose of the same antigen concentration on day 7. To assess the allergenicity of this nematode, we measured a whole blood profile, serum levels of IFN-γ, IL-5, IL-10, IL-13, and IL-33, total immunoglobulins IgE and IgG, and oxidative stress markers. Also, we examined histological changes in the liver, kidney, and spleen. The results showed that values of total leukocyte count, granulocytes, monocytes, and lymphocytes were significantly (P < 0.05) increased on day 14 post-infection relative to other days of investigation. It was found that the levels of total immunoglobulins (IgE and IgG) and cytokines (INF-γ, IL-5, IL-13, and IL-33) on days 14 and 21 were significantly higher than in the control group. At all periods of the experiment, the injected group exhibited significantly higher concentrations of MDA and NO compared to the control group (P < 0.05). Conversely, GSH and CAT levels (P < 0.05) dropped significantly on days 7, 14, and 21. Different rat tissues showed alterations. Ultimately, this study described the detrimental effects of P. equorum crude antigen administration on the immune system, oxidative states, and histological changes of Wistar rats at various intervals.
Ten years of oil pollution detection in the Eastern Mediterranean shipping lanes opposite the Egyptian coast using remote sensing techniques
Authors: Baghdady Salma M. , Abdelsalam Ali A. 
Published: August 2024

AbstractThe Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014–2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports.
Metal-insulator transition of spinless fermions coupled to dispersive optical bosons
Authors: Lange Florian , Fehske Holger 
Published: August 2024

AbstractIncluding the previously ignored dispersion of phonons we revisit the metal-insulator transition problem in one-dimensional electron-phonon systems on the basis of a modified spinless fermion Holstein model. Using matrix-product-state techniques we determine the global ground-state phase diagram in the thermodynamic limit for the half-filled band case, and show that in particular the curvature of the bare phonon band has a significant effect, not only on the transport properties characterized by the conductance and the Luttinger liquid parameter, but also on the phase space structure of the model as a whole. While a downward curved (convex) dispersion of the phonons only shifts the Tomonaga-Luttinger-liquid to charge-density-wave quantum phase transition towards stronger EP coupling, an upward curved (concave) phonon band leads to a new phase-separated state which, in the case of strong dispersion, can even completely cover the charge-density wave. Such phase separation does not occur in the related Edwards fermion-boson model.
Cluster membership analysis with supervised learning and N-body simulations
Authors: Bissekenov A. , Kalambay M. , Abdikamalov E. , Pang X. , Berczik P. , Shukirgaliyev B. 
Published: August 2024

Context. Membership analysis is an important tool for studying star clusters. There are various approaches to membership determination, including supervised and unsupervised machine-learning (ML) methods.
Aims. We perform membership analysis using the supervised ML approach.
Methods. We trained and tested our ML models on two sets of star cluster data: snapshots from N-body simulations, and 21 different clusters from the Gaia Data Release 3 data.
Results. We explored five different ML models: random forest (RF), decision trees, support vector machines, feed-forward neural networks, and K-nearest neighbors. We find that all models produce similar results, and the accuracy of RF is slightly better. We find that a balance of classes in the datasets is optional for a successful learning. The classification accuracy strongly depends on the astrometric parameters. The addition of photometric parameters does not improve the performance. We find no strong correlation between the classification accuracy and the cluster age, mass, and half-mass radius. At the same time, models trained on clusters with a larger number of members generally produce better results.