bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Role of Local Acceleration and Radial Diffusion in Multi‐MeV Electron Flux Enhancements
Authors: Saikin A. A. , Drozdov A. Y. , Jaynes A. N. , Kondrashov D. , Boyd A. , Shprits Y. Y. 
Published: January 2025

AbstractDuring the Van Allen Probes era, several multi‐MeV (>4 MeV) electron flux enhancements were observed. The cause of electron acceleration up to multi‐MeV remains an ongoing science topic. In this study, we focus on examining the relationship between phase space density (PSD) radial profile shapes and the occurrence of multi‐MeV electron flux enhancement events. This will determine which process (local acceleration or radial diffusion) is dominant in producing multi‐MeV electron flux enhancements at a specific L*. Growing peaks in PSD radial profiles are associated with the local acceleration (i.e., a wave‐particle interaction) of multi‐MeV electrons. For each growing peak in PSD, we determined the L* where the local acceleration occurs for each respective electron energy. Similarly, we also identify which PSD profiles are related to acceleration via radial diffusion profiles. Both sets of profiles are compared with the Van Allen Probe‐A observed multi‐MeV electron flux enhancements. Results show that both mechanisms (local acceleration and radial diffusion) can facilitate multi‐MeV electron acceleration, however each mechanism has a preferable L* region where it is the dominant acceleration process.
GenAI synthesis of histopathological images from Raman imaging for intraoperative tongue squamous cell carcinoma assessment
Authors: Yan Bing , Wen Zhining , Xue Lili , Wang Tianyi , Liu Zhichao , Long Wulin , Li Yi , Jing Runyu 
Published: January 2025

Abstract
The presence of a positive deep surgical margin in tongue squamous cell carcinoma (TSCC) significantly elevates the risk of local recurrence. Therefore, a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection. In this study, we integrate Raman imaging technology with an artificial intelligence (AI) generative model, proposing an innovative approach for intraoperative margin status diagnosis. This method utilizes Raman imaging to swiftly and non-invasively capture tissue Raman images, which are then transformed into hematoxylin-eosin (H&E)-stained histopathological images using an AI generative model for histopathological diagnosis. The generated H&E-stained images clearly illustrate the tissue’s pathological conditions. Independently reviewed by three pathologists, the overall diagnostic accuracy for distinguishing between tumor tissue and normal muscle tissue reaches 86.7%. Notably, it outperforms current clinical practices, especially in TSCC with positive lymph node metastasis or moderately differentiated grades. This advancement highlights the potential of AI-enhanced Raman imaging to significantly improve intraoperative assessments and surgical margin evaluations, promising a versatile diagnostic tool beyond TSCC.
Maternal weight during pregnancy and risk of childhood acute lymphoblastic leukemia in offspring
Authors: Liu Jiaye , Kharazmi Elham , Liang Qunfeng , Chen Yafei , Sundquist Jan , Sundquist Kristina , Fallah Mahdi 
Published: January 2025

Abstract
In addition to biological factors, maternal exposures during pregnancy can contribute to leukemogenesis in offspring. We conducted a population-based cohort study in Sweden to investigate the association between risk of acute lymphoblastic leukemia (ALL) in offspring and maternal anthropometrics during pregnancy. A total of 2,961,435 live-born singletons during 1983–2018 were followed from birth to ALL diagnosis, end of age 18, or end of 2018. 1388 children were diagnosed with ALL (55.6% boys). We observed an increased risk of ALL among daughters of overweight/obese mothers in early pregnancy [Body mass index (BMI) ≥ 25 kg/m2; Standardized incidence ratio (SIR) = 1.4, 95% CI: 1.2–1.6] compared with the risk in daughters of mothers with normal BMI. This association was not found in their sons (SIR = 1.0, 95% CI: 0.9–1.1). Similar results were found for the association between ALL and maternal BMI before delivery. We did not find an association between low or high gestational weight gain (GWG) and risk of ALL (both SIRs = 1.0) in male/female offspring. These suggest that maternal overweight/obesity are important risk factors for childhood ALL in daughters, whereas GWG is not associated with risk of ALL. Further research on this mother-daughter association may shed light on a possible sex hormone/chromosome-related etiology of ALL.
Metasurface higher-order poincaré sphere polarization detection clock
Authors: Yang Hui , Ou Kai , Liu Qiang , Peng Meiyu , Xie Zhenwei , Jiang Yuting , Jia Honghui , Cheng Xinbin , Jing Hui , Hu Yueqiang , Duan Huigao 
Published: January 2025

Abstract
Accurately and swiftly characterizing the state of polarization (SoP) of complex structured light is crucial in the realms of classical and quantum optics. Conventional strategies for detecting SoP, which typically involves a sequence of cascaded optical elements, are bulky, complex, and run counter to miniaturization and integration. While metasurface-enabled polarimetry has emerged to overcome these limitations, its functionality predominantly remains confined to identifying SoP within the standard Poincaré sphere framework. The comprehensive detection of SoP on the higher-order Poincaré sphere (HOPS), however, continues to be a huge challenge. Here, we propose a general polarization metrology method capable of fully detecting SoP on any HOPS through a single measurement. The underlying mechanism relies on transforming the optical singularities and Stokes parameters into visualized intensity patterns, facilitating the extraction of all parameters that fully determine a SoP. We actualize this concept through a novel meta-device known as the metasurface photonics polarization clock, which offers an intuitive display of SoP using four distinct pointers. As a proof of concept, we theoretically and experimentally demonstrate fully resolving SoPs on the 0th, 1st, and 2nd HOPSs. Our implementation opens up a new pathway towards real-time polarimetry of arbitrary beams featuring miniaturized size, a simple detection process, and a direct readout mechanism, promising significant advancements in fields reliant on polarization.
The cryptic lncRNA-encoded microprotein TPM3P9 drives oncogenic RNA splicing and tumorigenesis
Authors: Meng Kun , Li Yuying , Yuan Xiaoyi , Shen Hui-Min , Hu Li-Ling , Liu Danya , Shi Fujin , Zheng Dandan , Shi Xinyu , Wen Nengqiao , Cao Yun , Pan Yun-Long , He Qing-Yu , Zhang Chris Zhiyi 
Published: January 2025

Abstract
Emerging evidence demonstrates that cryptic translation from RNAs previously annotated as noncoding might generate microproteins with oncogenic functions. However, the importance and underlying mechanisms of these microproteins in alternative splicing-driven tumor progression have rarely been studied. Here, we show that the novel protein TPM3P9, encoded by the lncRNA tropomyosin 3 pseudogene 9, exhibits oncogenic activity in clear cell renal cell carcinoma (ccRCC) by enhancing oncogenic RNA splicing. Overexpression of TPM3P9 promotes cell proliferation and tumor growth. Mechanistically, TPM3P9 binds to the RRM1 domain of the splicing factor RBM4 to inhibit RBM4-mediated exon skipping in the transcription factor TCF7L2. This results in increased expression of the oncogenic splice variant TCF7L2-L, which activates NF-κB signaling via its interaction with SAM68 to transcriptionally induce RELB expression. From a clinical perspective, TPM3P9 expression is upregulated in cancer tissues and is significantly correlated with the expression of TCF7L2-L and RELB. High TPM3P9 expression or low RBM4 expression is associated with poor survival in patients with ccRCC. Collectively, our findings functionally and clinically characterize the “noncoding RNA”-derived microprotein TPM3P9 and thus identify potential prognostic and therapeutic factors in renal cancer.
Pifithrin-μ sensitizes mTOR-activated liver cancer to sorafenib treatment
Authors: Lv Jiarui , Wang Yanan , Lv Jiacheng , Zheng Cuiting , Zhang Xinyu , Wan Linyan , Zhang Jiayang , Liu Fangming , Zhang Hongbing 
Published: January 2025

Abstract
TSC2, a suppressor of mTOR, is inactivated in up to 20% of HBV-associated liver cancer. This subtype of liver cancer is associated with aggressive behavior and early recurrence after hepatectomy. Being the first targeted regimen for advanced liver cancer, sorafenib has limited efficacy in HBV-positive patients. In this study, we observed that mTOR-activated cells, due to the loss of either TSC2 or PTEN, were insensitive to the treatment of sorafenib. Mechanistically, HSP70 enhanced the interaction between active mTOR-potentiated CREB1 and CREBBP to boost the transcription of the antioxidant response regulator SESN3. In return, elevated SESN3 enhanced cellular antioxidant capacity and rendered cells resistant to sorafenib. Pifithrin-μ, an HSP70 inhibitor, synergized with sorafenib in the induction of ferroptosis in mTOR-activated liver cancer cells and suppression of TSC2-deficient hepatocarcinogenesis. Our findings highlight the pivotal role of the mTOR-CREB1-SESN3 axis in sorafenib resistance of liver cancer and pave the way for combining pifithrin-μ and sorafenib for the treatment of mTOR-activated liver cancer.
Overexpression of miR-124 enhances the therapeutic benefit of TMZ treatment in the orthotopic GBM mice model by inhibition of DNA damage repair
Authors: Wei Yuchen , Wang Peng , Zhao Jianhui , Fan Xin , Jiang Jun , Mu Xiuli , Wang Yuzhou , Yang Angang , Zhang Rui , Hu Shijie , Guo Zhangyan 
Published: January 2025

Abstract
Glioblastoma (GBM) is the most common malignant primary brain cancer with poor prognosis due to the resistant to current treatments, including the first-line drug temozolomide (TMZ). Accordingly, it is urgent to clarify the mechanism of chemotherapeutic resistance to improve the survival rate of patients. In the present study, by integrating comprehensive non-coding RNA-seq data from multiple cohorts of GBM patients, we identified that a series of miRNAs are frequently downregulated in GBM patients compared with the control samples. Among them, a high level of miR-124 is closely associated with a favorable survival rate in the clinical patients. In the phenotype experiment, we demonstrated that miR-124 overexpression increases responsiveness of GBM cells to TMZ-induced cell death, and vice versa. In the mechanistic study, we for the first time identified that RAD51, a key functional molecule in DNA damage repair, is a novel and bona fide target of miR-124 in GBM cells. Given that other miR-124-regulated mechanisms on TMZ sensitivity have been reported, we performed recue experiment to demonstrate that RAD51 is essential for miR-124-mediated sensitivity to TMZ in GBM cells. More importantly, our in vivo functional experiment showed that combinational utilization of miR-124 overexpression and TMZ presents a synergetic therapeutic benefit in the orthotopic GBM mice model. Taken together, we rationally explained a novel and important mechanism of the miR-124-mediated high sensitivity to TMZ-induced cell death in GBM and provided evidence to support that miR-124-RAD51 regulatory axis could be a promising candidate in the comprehensive treatment with TMZ in GBM.
Longitudinal omics data and preclinical treatment suggest the proteasome inhibitor carfilzomib as therapy for ibrutinib-resistant CLL
Authors: Arseni Lavinia , Sigismondo Gianluca , Yazdanparast Haniyeh , Hermansen Johanne U. , Mack Norman , Ohl Sibylle , Kalter Verena , Iskar Murat , Kalxdorf Mathias , Friedel Dennis , Rettel Mandy , Paul Yashna , Ringshausen Ingo , Eldering Eric , Dubois Julie , Kater Arnon P. , Zapatka Marc , Roessner Philipp M. , Tausch Eugen , Stilgenbauer Stephan , Dietrich Sascha , Savitski Mikhail M. , Skånland Sigrid S. , Krijgsveld Jeroen , Lichter Peter , Seiffert Martina 
Published: January 2025

Abstract
Chronic lymphocytic leukemia is a malignant lymphoproliferative disorder for which primary or acquired drug resistance represents a major challenge. To investigate the underlying molecular mechanisms, we generate a mouse model of ibrutinib resistance, in which, after initial treatment response, relapse under therapy occurrs with an aggressive outgrowth of malignant cells, resembling observations in patients. A comparative analysis of exome, transcriptome and proteome of sorted leukemic murine cells during treatment and after relapse suggests alterations in the proteasome activity as a driver of ibrutinib resistance. Preclinical treatment with the irreversible proteasome inhibitor carfilzomib administered upon ibrutinib resistance prolongs survival of mice. Longitudinal proteomic analysis of ibrutinib-resistant patients identifies deregulation in protein post-translational modifications. Additionally, cells from ibrutinib-resistant patients effectively respond to several proteasome inhibitors in co-culture assays. Altogether, our results from orthogonal omics approaches identify proteasome inhibition as potentially attractive treatment for chronic lymphocytic leukemia patients resistant or refractory to ibrutinib.
Disorder-induced enhancement of lithium-ion transport in solid-state electrolytes
Authors: Chen Zhimin , Du Tao , Krishnan N. M. Anoop , Yue Yuanzheng , Smedskjaer Morten M. 
Published: January 2025

Abstract
Enhancing the ion conduction in solid electrolytes is critically important for the development of high-performance all-solid-state lithium-ion batteries (LIBs). Lithium thiophosphates are among the most promising solid electrolytes, as they exhibit superionic conductivity at room temperature. However, the lack of comprehensive understanding of their ion conduction mechanism, especially the effect of structural disorder on ionic conductivity, is a long-standing problem that limits further innovations in all-solid-state LIBs. Here, we address this challenge by establishing and employing a deep learning potential to simulate Li3PS4 electrolyte systems with varying levels of disorder. The results show that disorder-driven diffusion dynamics significantly enhances the room-temperature conductivity. We further establish bridges between dynamical characteristics, local structural features, and atomic rearrangements by applying a machine learning-based structure fingerprint termed “softness”. This metric allows the classification of the disorder-induced “soft” hopping lithium ions. Our findings offer insights into ion conduction mechanisms in complex disordered structures, thereby contributing to the development of superior solid-state electrolytes for LIBs.
Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics
Authors: Liu Xiang , Sun Haidan , Hou Xinhang , Sun Jiameng , Tang Min , Zhang Yong-Biao , Zhang Yongqian , Sun Wei , Liu Chao ,   Urine Test Sample Working Group, Gao Youhe , Tang Shuxuan , Shen Ziyun , Liu Kehui , Jia Lulu , Wei Jing , Wu Jianqiang , Tang Xiaoyue , Li Yanchang , Wang Guibin , Sui Xinying , Zhang Lihua , Yuan Huiming , Liu Xinxin , Liu Dong , Zhang Qi , Qiu Xindan , Wang Guanbo , Hu Mo , Tian Ye , Tan Minjie , Xue Peng , Guo Liman , Zhang Qing , Chen Yongsheng , Ji Jianguo , Hu Weiyi , Zhu Wenyuan , Huang Min , Qi Yingzi , Liu Xianming , Du Xiaoxian , Luo Ji , Chen Lingsheng , Zhao Yinghua 
Published: January 2025

Abstract
Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography−mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.
A principle-based framework to determine countries’ fair warming contributions to the Paris Agreement
Authors: Li Mingyu , Pelz Setu , Lamboll Robin , Wang Can , Rogelj Joeri 
Published: January 2025

Abstract
Equity is a cornerstone of global climate policy, yet differing perspectives mean that international agreement on how to allocate mitigation efforts remains elusive. A rich literature informs this question, but a gap remains in approaches that appropriately consider non-CO2 emissions and their warming contributions. In this study, we address this gap and define a global warming budget applicable to all anthropogenic greenhouse gases that is allocated to countries based on principles drawn from international treaties and environmental law. We find that by 2021 a range of 84 to 90 countries, including but not limited to all major developed countries, exhausted their budget share compatible with keeping warming to 1.5 °C (with 50% likelihood) under all allocation approaches considered in this study. A similar picture emerges for limiting warming to 2 °C (with 67% likelihood). A large group of countries will hence exceed their fair shares even if their pledges under the Paris Agreement represent their deepest possible emission reductions. Considerations of fairness should therefore start exploring aspects beyond domestic emissions reductions.
Solvent-dripping modulated 3D/2D heterostructures for high-performance perovskite solar cells
Authors: Chang Xiaoming , Azmi Randi , Yang Tinghuan , Wu Nan , Jeong Sang Young , Xi Herui , Satrio Utomo Drajad , Vishal Badri , Isikgor Furkan H. , Faber Hendrik , Ling Zhaoheng , He Mingjie , Marengo Marco , Dally Pia , Prasetio Adi , Yang Yu-Ying , Xiao Chuanxiao , Woo Han Young , Zhao Kui , Heeney Martin , De Wolf Stefaan , Tsetseris Leonidas , Anthopoulos Thomas D. 
Published: January 2025

Abstract
The controlled growth of two-dimensional (2D) perovskite atop three-dimensional (3D) perovskite films reduces interfacial recombination and impedes ion migration, thus improving the performance and stability of perovskite solar cells (PSCs). Unfortunately, the random orientation of the spontaneously formed 2D phase atop the pre-deposited 3D perovskite film can deteriorate charge extraction owing to energetic disorder, limiting the maximum attainable efficiency and long-term stability of the PSCs. Here, we introduce a meta-amidinopyridine ligand and the solvent post-dripping step to generate a highly ordered 2D perovskite phase on the surface of a 3D perovskite film. The reconstructed 2D/3D perovskite interface exhibits reduced energetic disorder and yields cells with improved performance compared with control 2D/3D samples. PSCs fabricated with the meta-amidinopyridine-induced phase-pure 2D perovskite passivation show a maximum power conversion efficiency of 26.05% (a certified value of 25.44%). Under damp heat and outdoor tests, the encapsulated PSCs maintain 82% and 75% of their initial PCE after 1000 h and 840 h, respectively, demonstrating improved practical durability.
Phase I trial of hydroxychloroquine to enhance palbociclib and letrozole efficacy in ER+/HER2− breast cancer
Authors: Raghavendra Akshara Singareeka , Kettner Nicole M. , Kwiatkowski Danielle , Damodaran Senthil , Wang Yan , Ramirez David , Gombos Dan S. , Hunt Kelly K. , Shen Yu , Keyomarsi Khandan , Tripathy Debu 
Published: January 2025

Abstract
Endocrine therapy with CDK4/6 inhibitors is standard for estrogen receptor-positive, HER2−negative metastatic breast cancer (ER+/HER2− MBC), yet clinical resistance develops. Previously, we demonstrated that low doses of palbociclib activate autophagy, reversing initial G1 cell cycle arrest, while high concentrations induce off-target senescence. The autophagy inhibitor hydroxychloroquine (HCQ) induced on-target senescence at lower palbociclib doses. We conducted a phase I trial (NCT03774472 registered in ClinicalTrials.gov on 8/20/2018) of HCQ (400, 600, 800 mg/day) with palbociclib (75 mg/day continuous) and letrozole, using a 3 + 3 design. Primary objectives included safety, tolerability, and determining the recommended phase 2 dose (RP2D) of HCQ. Secondary objectives included tumor response and biomarker analysis. Fourteen ER+/HER2− MBC patients were evaluable [400 mg (n = 4), 600 mg (n = 4), 800 mg (n = 6)]. Grade 3 adverse events (AEs) included hematological (3 at 800 mg), skin rash (2 at 600 mg), and anorexia (1 at 400 mg), with no serious AEs. The best responses were partial (2), stable (11), and progression (1). Tumor reductions ranged from 11% to 30%, with one 55% increase. The two partial responders sustained tumor size reductions of 30% to 55% over an extended treatment period, lasting nearly 300 days. Biomarker analysis in responders demonstrated significant decreases in Ki67, Rb, and nuclear cyclin E levels and increases in autophagy markers p62 and LAMP1, suggesting a correlation between these biomarkers and treatment response. This phase I study demonstrated that HCQ is safe and well-tolerated and the RP2D was established at 800 mg/day with continuous low-dose palbociclib (75 mg/day) and letrozole (2.5 mg/day). These findings suggest that adding HCQ could potentially enhance the efficacy of low-dose palbociclib and standard letrozole therapy, pending verification in larger randomized studies.
Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters
Authors: Owens C. Braxton , Mathew Nithin , Olaveson Tyce W. , Tavenner Jacob P. , Kober Edward M. , Tucker Garritt J. , Hart Gus L. W. , Homer Eric R. 
Published: January 2025

Abstract
Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. We examine how these steps and different combinations of engineered features impact the accuracy of grain boundary energy predictions using a database of over 7000 grain boundaries. Additionally, we assess how different engineered features support interpretability, offering insights into the physics of the structure-property relationships.