bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sectoral Size‐Resolved Particle Number Emissions With Speciation: Emission Profile‐Based Quantification and a Case Study in the Yangtze River Delta Region, China
Authors: An Jingyu , Lu Yiqun , Huang Dan Dan , Ding Xiang , Hu Qingyao , Yan Rusha , Qiao Liping , Zhou Min , Huang Cheng , Wang Hongli , Fu Qingyan , Yu Fangqun , Wang Lin 
Published: October 2024

AbstractSizes and number concentrations are critical parameters for the impact of atmospheric particles on climate and human health. However, comprehensive studies focusing on size‐resolved particle number (PN) emissions from various sectors are scarce. This study aims to fill this research gap by developing sectoral size‐resolved PN emissions for major species including sulfate, organic mass (OM), and black carbon (BC). The size‐resolved emission profiles derived from various measurements in the literature were integrated with a particle mass emission inventory (EI) for 13 major sectors in the Yangtze River Delta region of China as a case study. The particle number size distribution (PNSD) of emitted particles exhibited two distinct peaks: one at approximately 10 nm and the other in the range of 40–60 nm. The primary contributors to PN emissions in the region in 2017 were power plants, gasoline vehicles, diesel vehicles, and cooking sources. In terms of species, OM dominated PN emissions, followed by primary sulfate and then BC. A regional size‐resolved aerosol model employing the size‐resolved PN EI developed here (referred to as the BIN‐SPE experiment) provided reasonably accurate temporal variations of the total PN concentration and captured the PNSD within the size range of 10–300 nm. Uncertainty analysis of sectoral PN emissions across size ranges was carried out and the performance of the BIN‐SPE experiment was compared with those of three commonly used PN emission parameterizations. Our model evaluations highlight future needs for in‐depth investigations into more advanced size‐resolved emissions and secondary OM formation mechanisms.
Deep Forest Modeling: An Interpretable Deep Learning Method for Mineral Prospectivity Mapping
Authors: Dong Yue‐Lin , Zhang Zhen‐Jie 
Published: October 2024

AbstractAccurate mineral prediction is crucial for reducing costs and uncertainties in mineral discovery and extraction. The use of artificial intelligence and big data has advanced mineral prediction into intelligent forecasting. Machine learning methods have shown significant promise in enhancing outcomes. Currently, neural network‐based approaches dominate deep learning (DL), but they lack interpretability and have high modeling complexity, making them less effective for complex problems and time‐consuming. Deep Forest, an innovative DL paradigm, addresses these issues by dynamically adjusting complexity and providing importance assessments for predictive factors. This study focuses on the North American Cordillera, known for its rich geological data and potential for porphyry copper deposits (PCDs). Predictions are made using Deep Forest with factors like Euclidean distance between faults and magmatic rock, fault line density, gravity anomalies, and stream‐sediment geochemical data. Deep neural networks, random forest, convolutional neural networks, transformer model and graph convolutional networks are also used for comparison. Deep Forest shows high performance and can avoid the black box problem of DL without relying on other tools in DL, providing a new perspective for the development and application of other non‐neural network DL models for mineral prediction. Feature importance analysis shows that geological structure and magmatism significantly influence PCD prediction. Elevated levels of elements like Al, Co, and Cr in stream sediments help identify mineralization‐related alterations. These findings underscore Deep Forest's capability to accurately and efficiently guide mineral exploration, highlighting its potential as a promising approach for mineral prospecting.
Landmine Detection Using Electromagnetic Time Reversal‐Based Methods: 1. Classical TR, Iterative TR, DORT and TR‐MUSIC
Authors: Karami Hamidreza , Koch André , Romero Carlos , Rubinstein Marcos , Rachidi Farhad 
Published: October 2024

AbstractIn this paper, we present a review and classification of the published works on the use of Electromagnetic Time Reversal (EMTR)‐based methods to locate landmines. Different approaches for landmine localization using EMTR are investigated. Specifically, the classical time‐domain EMTR, iterative EMTR, EMTR‐DORT (Décomposition de l’Opérateur du Retournement Temporel), and EMTR‐MUSIC (MUltiple SIgnal Classification) are implemented using different numerical techniques. The main properties of the mentioned EMTR‐based approaches are reviewed and the TR‐MUSIC method is selected as the most promising approach for the problem of interest, among all the reviewed methods. In the TR‐MUSIC method, the transfer matrix is calculated in the first step. Then, the singular value decomposition of the transfer matrix is performed. In the last step, the location of the landmines is obtained through the evaluation of the pseudospectrum. As opposed to other EMTR‐based techniques, TR‐MUSIC features very high resolution (in the order of /10 or higher) with a reasonable number of sensors, allowing the detection of multiple closely spaced targets.
Unveiling the role of transgelin as a prognostic and therapeutic target in kidney fibrosis via a proteomic approach
Authors: Kwon Soie , Cheon Seongmin , Kim Kyu-Hong , Seo Areum , Bae Eunjin , Lee Jae Wook , Cha Ran-Hui , Hwang Jin Ho , Kim Yong Chul , Kim Dong Ki , Kim Yon Su , Han Dohyun , Yang Seung-Hee 
Published: October 2024

AbstractChronic kidney disease (CKD) progression involves tubulointerstitial fibrosis, a process characterized by excessive extracellular matrix accumulation. To identify potential biomarkers for kidney fibrosis, we performed mass spectrometry-based proteomic profiling of human kidney tubular epithelial cells and kidney tissue from a 5/6 nephrectomy rat model. Multidisciplinary analysis across kidney fibrosis models revealed 351 differentially expressed proteins associated with kidney fibrosis, and they were enriched in processes related to the extracellular matrix, kidney aging, and mitochondrial functions. Network analysis of the selected proteins revealed five crucial proteins, of which transgelin emerged as a candidate protein that interacts with known fibrosis-related proteins. Concordantly, the gene expression of transgelin in the kidney tissue from the 5/6 nephrectomy model was elevated. Transgelin expression in kidney tissue gradually increased from intermediate to advanced fibrosis stages in 5/6 Nx rats and mice with unilateral ureteral obstruction. Subsequent validation in kidney tissue and urine samples from patients with CKD confirmed the upregulation of transgelin, particularly under advanced disease stages. Moreover, we investigated whether blocking TAGLN ameliorated kidney fibrosis and reduced reactive oxygen species levels in cellular models. In conclusion, our proteomic approach identified TAGLN as a potential noninvasive biomarker and therapeutic target for CKD-associated kidney fibrosis, suggesting its role in modulating mitochondrial dysfunction and oxidative stress responses.
Perspectives on obesity imaging: [18F]2FNQ1P a specific 5-HT6 brain PET radiotracer
Authors: Courault Pierre , Bouvard Sandrine , Bouillot Caroline , Bolbos Radu , Zeinyeh Waël , Iecker Thibaut , Liger François , Billard Thierry , Zimmer Luc , Chauveau Fabien , Lancelot Sophie 
Published: October 2024

Abstract
Background
Estimates suggest that approximatively 25% of the world population will be overweight in 2025. Better understanding of the pathophysiology of obesity will help to develop future therapeutics. Serotonin subtype 6 receptors (5-HT6) have been shown to be critically involved in appetite reduction and weight loss. However, it is not known if the pathological cascade triggered by obesity modifies the density of 5-HT6 receptors in the brain.

Methods
Influence of diet-induced obesity (DIO) in Wistar rats was explored using MRI (whole-body fat) and PET ([18F]2FNQ1P as a specific 5-HT6 radiotracer). The primary goal was to monitor the 5-HT6 receptor density before and after a 10-week diet (DIO group). The secondary goal was to compare 5-HT6 receptor densities between DIO group, Wistar control diet group, Zucker rats (with genetic obesity) and Zucker lean strain rats.

Results
Wistar rats fed with high-fat diet showed higher body fat gain than Wistar control diet rats on MRI. [18F]2FNQ1P PET analysis highlighted significant clusters of voxels (located in hippocampus, striatum, cingulate, temporal cortex and brainstem) with increased binding after high-fat diet (p < 0.05, FWE corrected).

Conclusion
This study sheds a new light on the influence of high-fat diet on 5-HT6 receptors. This study also positions [18F]2FNQ1P PET as an innovative tool to explore neuronal consequences of obesity or eating disorder pathophysiology.
Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy
Authors: Li Qing , Geng Shan , Luo Hao , Wang Wei , Mo Ya-Qi , Luo Qing , Wang Lu , Song Guan-Bin , Sheng Jian-Peng , Xu Bo 
Published: October 2024

AbstractColorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.
Circadian clock dysregulation: a potential mechanism of depression in obstructive sleep apnea patients
Authors: Gabryelska Agata , Turkiewicz Szymon , Kaczmarski Piotr , Gajewski Adrian , Białasiewicz Piotr , Strzelecki Dominik , Chałubiński Maciej , Sochal Marcin 
Published: October 2024

AbstractObstructive sleep apnea (OSA) is characterized by co-occurrence with affective disorders. Our study aims to investigate the association of circadian clock gene expressions, and the presence and severity of depressive symptoms in OSA patients. The study included 184 individuals, who underwent polysomnography (PSG) and had their peripheral blood collected in the evening before and the morning after the PSG. Patients were divided into two groups: the OSA (apnea-hypopnea index (AHI) > 5) and the control group (AHI < 5). RNA was extracted from peripheral blood leukocytes. Expression levels of the selected genes (BMAL1, CLOCK, PER1, CRY1, NPAS2, and NR1D1) were assessed by qRT-PCR. Questionnaire data was collected in the morning (including the Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Chronotype Questionnaire (CQ), and Montgomery–Åsberg Depression Rating Scale (MADRS)). The expression of all examined circadian clock genes in OSA patients was upregulated in the morning compared to the evening (except NPAS2). No differences were observed between OSA and control groups at either time point. Additionally, there was a positive correlation between the severity of depressive symptoms (assessed with MADRS) and morning expression of circadian genes in the group of OSA patients. Finally, in multivariable linear regression, ISI score (B = 0.750, p < 0.001), AM score of CQ (B = 0.416, p = 0.007), and morning PER1 gene expression (B = 4.310, p = 0.042) were found to be predictive factors for greater severity of depression symptoms in OSA patients. Dysregulated circadian clock gene expression in OSA patients is linked to depressive symptom severity, suggesting circadian disruption may underlie affective symptoms in OSA.
HNRNPC mediates lymphatic metastasis of cervical cancer through m6A-dependent alternative splicing of FOXM1
Authors: Liu Yun-Yun , Xia Meng , Chen Zhi-Bo , Liao Yuan-Dong , Zhang Chun-Yu , Yuan Li , Pan Yu-Wen , Huang Hua , Lu Huai-Wu , Yao Shu-Zhong 
Published: October 2024

AbstractCervical cancer (CCa) patients with lymph node (LN) metastasis face poor prognoses and have limited treatment options. Aberrant N6-methyladenosine (m6A) modification of RNAs are known to promote tumor metastasis, but their role in CCa remains unclear. Our study reveals that HNRNPC, an alternative splicing (AS) factor and m6A reader, increases tumor-related variants through m6A-dependent manner, thereby promoting lymphatic metastasis in CCa. We found that HNRNPC overexpression correlates with lymphatic metastasis and poorer prognoses in CCa patients. Functionally, knocking down HNRNPC markedly inhibited the migration and invasion of several CCa cell lines, while supplementing HNRNPC restored the malignant phenotypes of these cells. Mechanistically, HNRNPC regulates exon skipping of FOXM1 by binding to its m6A-modified motif. Mutating the m6A site on FOXM1 weakened the interaction between HNRNPC and FOXM1 pre-RNA, leading to a reduction in the metastasis-related FOXM1-S variant. In conclusion, our findings demonstrate that m6A-dependent alternative splicing mediated by HNRNPC is essential for lymphatic metastasis in CCa, potentially providing novel clinical markers and therapeutic strategies for patients with advanced CCa.
Mechanochemically responsive polymer enables shockwave visualization
Authors: Centellas Polette J. , Mehringer Kyle D. , Bowman Andrew L. , Evans Katherine M. , Vagholkar Parth , Thornell Travis L. , Huang Liping , Morgan Sarah E. , Soles Christopher L. , Simon Yoan C. , Chan Edwin P. 
Published: October 2024

AbstractUnderstanding the physical and chemical response of materials to impulsive deformation is crucial for applications ranging from soft robotic locomotion to space exploration to seismology. However, investigating material properties at extreme strain rates remains challenging due to temporal and spatial resolution limitations. Combining high-strain-rate testing with mechanochemistry encodes the molecular-level deformation within the material itself, thus enabling the direct quantification of the material response. Here, we demonstrate a mechanophore-functionalized block copolymer that self-reports energy dissipation mechanisms, such as bond rupture and acoustic wave dissipation, in response to high-strain-rate impacts. A microprojectile accelerated towards the polymer permanently deforms the material at a shallow depth. At intersonic velocities, the polymer reports significant subsurface energy absorption due to shockwave attenuation, a mechanism traditionally considered negligible compared to plasticity and not well explored in polymers. The acoustic wave velocity of the material is directly recovered from the mechanochemically-activated subsurface volume recorded in the material, which is validated by simulations, theory, and acoustic measurements. This integration of mechanochemistry with microballistic testing enables characterization of high-strain-rate mechanical properties and elucidates important insights applicable to nanomaterials, particle-reinforced composites, and biocompatible polymers.
One Health collaboration is more effective than single-sector actions at mitigating SARS-CoV-2 in deer
Authors: Cook Jonathan D. , Rosenblatt Elias , Direnzo Graziella V. , Campbell Grant Evan H. , Mosher Brittany A. , Arce Fernando , Christensen Sonja A. , Ghai Ria R. , Runge Michael C. 
Published: October 2024

AbstractOne Health aims to achieve optimal health outcomes for people, animals, plants, and shared environments. We describe a multisector effort to understand and mitigate SARS-CoV-2 transmission risk to humans via the spread among and between captive and wild white-tailed deer. We first framed a One Health problem with three governance sectors that manage captive deer, wild deer populations, and public health. The problem framing included identifying fundamental objectives, causal chains for transmission, and management actions. We then developed a dynamic model that linked deer herds and simulated SARS-CoV-2. Next, we evaluated management alternatives for their ability to reduce SARS-CoV-2 spread in white-tailed deer. We found that single-sector alternatives reduced transmission, but that the best-performing alternative required collaborative actions among wildlife management, agricultural management, and public health agencies. Here, we show quantitative support that One Health actions outperform single-sector responses, but may depend on coordination to track changes in this evolving system.
HyLight: Strain aware assembly of low coverage metagenomes
Authors: Kang Xiongbin , Zhang Wenhai , Li Yichen , Luo Xiao , Schönhuth Alexander 
Published: October 2024

AbstractDifferent strains of identical species can vary substantially in terms of their spectrum of biomedically relevant phenotypes. Reconstructing the genomes of microbial communities at the level of their strains poses significant challenges, because sequencing errors can obscure strain-specific variants. Next-generation sequencing (NGS) reads are too short to resolve complex genomic regions. Third-generation sequencing (TGS) reads, although longer, are prone to higher error rates or substantially more expensive. Limiting TGS coverage to reduce costs compromises the accuracy of the assemblies. This explains why prior approaches agree on losses in strain awareness, accuracy, tendentially excessive costs, or combinations thereof. We introduce HyLight, a metagenome assembly approach that addresses these challenges by implementing the complementary strengths of TGS and NGS data. HyLight employs strain-resolved overlap graphs (OG) to accurately reconstruct individual strains within microbial communities. Our experiments demonstrate that HyLight produces strain-aware and contiguous assemblies at minimal error content, while significantly reducing costs because utilizing low-coverage TGS data. HyLight achieves an average improvement of 19.05% in preserving strain identity and demonstrates near-complete strain awareness across diverse datasets. In summary, HyLight offers considerable advances in metagenome assembly, insofar as it delivers significantly enhanced strain awareness, contiguity, and accuracy without the typical compromises observed in existing approaches.
Climate-driven global redistribution of an ocean giant predicts increased threat from shipping
Authors: Womersley Freya C. , Sousa Lara L. , Humphries Nicolas E. , Abrantes Kátya , Araujo Gonzalo , Bach Steffen S. , Barnett Adam , Berumen Michael L. , Lion Sandra Bessudo , Braun Camrin D. , Clingham Elizabeth , Cochran Jesse E. M. , de la Parra Rafael , Diamant Stella , Dove Alistair D. M. , Duarte Carlos M. , Dudgeon Christine L. , Erdmann Mark V. , Espinoza Eduardo , Ferreira Luciana C. , Fitzpatrick Richard , Cano Jaime González , Green Jonathan R. , Guzman Hector M. , Hardenstine Royale , Hasan Abdi , Hazin Fábio H. V. , Hearn Alex R. , Hueter Robert E. , Jaidah Mohammed Y. , Labaja Jessica , Ladino Felipe , Macena Bruno C. L. , Meekan Mark G. , Morris John J. , Norman Bradley M. , Peñaherrera-Palma Cesar R. , Pierce Simon J. , Quintero Lina Maria , Ramírez-Macías Dení , Reynolds Samantha D. , Robinson David P. , Rohner Christoph A. , Rowat David R. L. , Sequeira Ana M. M. , Sheaves Marcus , Shivji Mahmood S. , Sianipar Abraham B. , Skomal Gregory B. , Soler German , Syakurachman Ismail , Thorrold Simon R. , Thums Michele , Tyminski John P. , Webb D. Harry , Wetherbee Bradley M. , Queiroz Nuno , Sims David W. 
Published: October 2024

AbstractClimate change is shifting animal distributions. However, the extent to which future global habitats of threatened marine megafauna will overlap existing human threats remains unresolved. Here we use global climate models and habitat suitability estimated from long-term satellite-tracking data of the world’s largest fish, the whale shark, to show that redistributions of present-day habitats are projected to increase the species’ co-occurrence with global shipping. Our model projects core habitat area losses of >50% within some national waters by 2100, with geographic shifts of over 1,000 km (∼12 km yr−1). Greater habitat suitability is predicted in current range-edge areas, increasing the co-occurrence of sharks with large ships. This future increase was ∼15,000 times greater under high emissions compared with a sustainable development scenario. Results demonstrate that climate-induced global species redistributions that increase exposure to direct sources of mortality are possible, emphasizing the need for quantitative climate-threat predictions in conservation assessments of endangered marine megafauna.
POLCAM: instant molecular orientation microscopy for the life sciences
Authors: Bruggeman Ezra , Zhang Oumeng , Needham Lisa-Maria , Körbel Markus , Daly Sam , Cheetham Matthew , Peters Ruby , Wu Tingting , Klymchenko Andrey S. , Davis Simon J. , Paluch Ewa K. , Klenerman David , Lew Matthew D. , O’Holleran Kevin , Lee Steven F. 
Published: October 2024

AbstractCurrent methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, which can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design and developed a fast algorithm based on Stokes parameter estimation that can operate over 1,000-fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study α-synuclein fibrils, the actin cytoskeleton of mammalian cells, fibroblast-like cells and the plasma membrane of live human T cells.