bluuebunny/crossref_metadata_2025 huggingface dataset:
Metastable Microstructural States During Short-Term Heat Treatment of the High-Speed Steel PM HS 3-3-4: Modeling and Experimental Validation
Authors: Müller Stefan , Benito Santiago , Schuppener Jannik , Weber Sebastian
Published: January 2025

Short-term heat treatments of tool steels, such as inductive hardening, target the martensitic hardening of functional surfaces from a metastable microstructural state of the multiphase system. Understanding the kinetics of the carbide dissolution, precipitation, growth, and coarsening, and their effect on the austenitic matrix is, thus, instrumental to designing optimal heat treatments. The present work investigates the influence of such processes on the powder-metallurgically produced high-speed steel DIN EN 1.3377 (PM HS 3-3-4). Starting from the as-delivered soft-annealed state, the microstructural evolution during the heat treatment was investigated. The heat treatments were simulated experimentally in a quenching dilatometer and numerically within the software package MatCalc. SEM and XRD provided detailed information about the microstructure, whereas hardness measurements deliver insights into mechanical properties. The developed MatCalc model can predict the carbide dissolution and the associated change in the chemical composition of the matrix during austenitizing as a function of temperature and time. The results in terms of the measured and computed martensite start temperature demonstrated good agreement between the experimental and simulation campaigns.
Intrinsic High-Strain-Rate Softening in a High-Strength Quenching and Partitioning Steel
Authors: Huang C. P. , Wang M. , Zhu K. Y. , Perlade Astrid , Huang M. X.
Published: January 2025

An anomalous high-strain-rate softening phenomenon was demonstrated in a high-strength quenching and partitioning (Q&P) steel. It was found that the high-strain-rate softening in the Q&P steel is caused by the intrinsic carbon-dislocation interaction, rather than transformation induced plasticity effect, dislocation density difference, or adiabatic heating. The key mechanism is ascribed to the disappeared Cottrell drag force during high-strain-rate deformation, which originates from carbon-dislocation interaction and is present during quasi-static deformation.
Should adrenal incidentaloma patients be evaluated for muscle mass, function, and quality? A cross-sectional study
Authors: Alkan Samet , Guney Sedat Can , Akcura Can , Ozdemir Nilufer , Hekimsoy Zeliha
Published: January 2025

Purpose

Our study evaluated skeletal muscle mass, function and quality among mild autonomous cortisol secretion (MACS) patients and non-functioning adrenal incidentaloma (NFAI) patients in comparison with the control group without adrenal mass.

Methods

63 NFAI (49 female, 14 male) and 31 MACS (24 female, 7 male) patients were included in the study. As the control group, 44 patients (31 women, 13 men) who were known to have no radiological adrenal pathology on computed tomography or magnetic resonance imaging performed for other reasons were selected. After recording the laboratory parameters of the patients, anthropometric measurements, handgrip strength test with dynamometer, SARC-F survey and bioelectrical impedance analysis (BIA) measurements were performed.

Results

There was no statistical difference among the groups in terms of age, gender, and BMI parameters. Handgrip strength (HGS), skeletal muscle mass (SMM) index (SMM/BMI), and skeletal muscle quality (HGS/SMM), values used to evaluate muscle strength and quality, were found to be significantly lower in both the MACS and NFAI groups compared to the control group (p = 0.004, p = 0.012 and p = 0.034 respectively). This significance was also present in women subgroup analyses (p = 0.002, p = 0.037 and p = 0.039 respectively), but these parameters lost their statistical significance in men. In the correlation analysis of the female subgroup, 24-h free urine cortisol value was inversely proportional to skeletal muscle quality (rs = -0.417, p = 0.008).

Conclusion

Our study showed that there is a decrease in muscle mass and function in female AI patients, and this decrease is more severe in MACS patients. These results may suggest that mild cortisol excess also has negative effects on skeletal muscle metabolism.
Revolutionizing acute myeloid leukemia treatment: a systematic review of immune-based therapies
Authors: Ebinama Ugochi , George Binsah
Published: January 2025

The established protocol for the management of acute myeloid leukemia (AML) has traditionally involved the administration of induction chemotherapy, followed by consolidation chemotherapy, and subsequent allogeneic stem cell transplantation for eligible patients. However, the prognosis for individuals with relapsed and refractory AML remains unfavorable. In response to the necessity for more efficacious therapeutic modalities, targeted immunotherapy has emerged as a promising advancement in AML treatment. This comprehensive review article specifically examines classical unconjugated and toxin-conjugated monoclonal antibodies, which are currently in the preclinical phase or undergoing evaluation in clinical trials. The review delves into the proposed mechanisms through which these monoclonal antibodies elicit anti-tumor activity and identifies the challenges associated with designing targeted immunotherapy. The review focuses on targeting specific antigens in AML, including FLT3/CD125, CLL-1, CD33, CD38, CD47, CD70, and CD123.
Material characterization of three liquid interlayers for laminated glass solutions
Authors: Hänig Julian , Gutjahr Alina , Bukieda Paulina , Engelmann Michael
Published: January 2025

The demand for versatile and visually appealing glazed structures has been increasing in recent years. To meet contemporary architectural needs, a wider range of functionalities is required, including smart, bendable and thin laminated glazing. In particular, cold poured liquid optically clear adhesives (LOCA) are gaining prominence as interlayers for complex curved cold bending and smart integration, where conventional interlayer films impose limitations. Furthermore, new applications for cold bending of thin glass with LOCA for complex free-form geometries are currently under development. This paper presents the investigation of three LOCA for application as interlayers in laminated glass. Within a comprehensive experimental study, essential material properties were investigated. The research focuses on the viscoelastic, tensile, and creep properties of the LOCA. Additionally, the study considers how the materials age under radiation, high temperature and high moisture in accordance with the product standard for laminated glass. All results are summarized to provide a wide-ranging data base for dimensioning laminated glass made with LOCA. The investigations proof a wide-ranging suitability for laminated glass. The mechanical properties of the LOCA are comparable to conventional interlayer films. Two materials behave medium stiff to stiff and one is more flexible. All LOCA provide ductility which makes them suitable for laminated safety glass applications. High performances paired with the autoclave-free processing LOCA drives for new fields of applications for architectural glazings.
Biological insights into alleviating heavy metal toxicity through the simultaneous supply of biochar biofilters derived from the Mikania micrantha and molybdenum nanoparticles
Authors: Rana Muhammad Shoaib , Chen Hongyu , Deng Shiwen , Imran Muhammad , Abdellah Yousif Abdelrahman Yousif , Li Wanting , Lin Jiayu , Li Jiaxi , Wang Ruilong
Published: January 2025

Cadmium (Cd) contamination in the environment is widespread, making it crucial to reduce Cd accumulation in cereal crops like wheat. However, strategies that not only mitigate Cd pollution but also address other environmental challenges, such as invasive species management, remain unclear. This study introduces an innovative approach combining molybdenum nanoparticles (Mo NPs, 1 µM) and biochar biofilters derived from the invasive plant Mikania micrantha (IPMM), targeting the biochemical and molecular responses of wheat under Cd stress (100 µM). Our findings showed that this novel combination significantly improved wheat physiological characteristics, growth, root architecture, elemental profile, osmoregulation, carotenoid, chlorophyll, gas exchange, and photosynthetic efficiency. Remarkably, simultaneous supply of IPMM biochar biofilters and Mo NPs substantially modulated the Cd translocation, reducing its accumulation in root (30.54%) and shoot (53.59%). Additionally, this strategy not only preserved mesophyll cell structures and the membrane integrity, but also strengthened and activated the oxidative defense systems through the regulation of genetic expressions. This synergistic approach advances the Cd alleviating techniques and offers a sustainable solution for utilizing invasive plants as a potential resource. By addressing both heavy metal pollution and ecological challenges, it provides a promising solution for safer crop production in Cd-contaminated environments.

Graphical Abstract
Open science 2.0: revolutionizing spatiotemporal data sharing and collaboration
Authors: Wang Siqin , Huang Xiao , Zhang Mengxi , Bao Shuming , Liu Lingbo , Fu Xiaokang , Zhang Ting , Song Yongze , Kedron Peter , Wilson John , Ye Xinyue , Yang Chaowei , Guan Wendy
Published: January 2025

The Spatial Data Lab (SDL) project is a collaborative initiative by the Center for Geographic Analysis at Harvard University, KNIME, Future Data Lab, China Data Institute, and George Mason University. Co-sponsored by the NSF IUCRC Spatiotemporal Innovation Center, SDL aims to advance applied research in spatiotemporal studies across various domains such as business, environment, health, mobility, and more. The project focuses on developing an open-source infrastructure for data linkage, analysis, and collaboration. Key objectives include building spatiotemporal data services, a reproducible, replicable, and expandable (RRE) platform, and workflow-driven data analysis tools to support research case studies. Additionally, SDL promotes spatiotemporal data science training, cross-party collaboration, and the creation of geospatial tools that foster inclusivity, transparency, and ethical practices. Guided by an academic advisory committee of world-renowned scholars, the project is laying the foundation for a more open, effective, and robust scientific enterprise.
Prediction of mechanical properties of eco-friendly concrete using machine learning algorithms and partial dependence plot analysis
Authors: Roy Tonmoy , Das Pobithra , Jagirdar Ravi , Shhabat Mousa , Abdullah Md Shahriar , Kashem Abul , Rahman Raiyan
Published: January 2025

Rice husk ash concrete (RHAC) shows promise as a beneficial supplementary material in concrete. However, determining mechanical properties such as compressive strength (CS) and splitting tensile strength (STS) of RHAC through conventional lab-scale methods is laborious and time-consuming. In this research, seven important variables were selected as inputs to predict CS and STS using machine learning (ML) models, including Gaussian Process Regression (GPR), Random Forest Regression (RFR), and Decision Tree Regression (DTR) with grid search optimization. The result presented revealed that selected machine learning models provide well accuracy for CS and STS estimates. Among these, the DTR model demonstrated superior performance, with CS prediction R2, RMSE, MAE, and MAPE values of 0.964, 3.314, 2.225, and 5.068, at the testing stage respectively. For STS at the testing stage, DTR achieved R2 of 0.969, RMSE of 0.177, MAE of 0.1322, and MAPE of 3.413. GPR and RFR models also performed well, with R2 values of 0.9434 and 0.9530 for CS prediction. The partial dependence plot (PDP) analysis revealed the optimal mix design parameters for achieving the desired strength. These results offer valuable insights for sustainable construction, allowing engineers to efficiently predict and optimize material performance, reducing the reliance on time-consuming lab methods.
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

During 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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Transition from irrigation with untreated wastewater to treated wastewater and associated benefits and risks
Authors: Heyde Benjamin J. , Braun Melanie , Soufi Leila , Lüneberg Kathia , Gallego Sara , Amelung Wulf , Axtmann Katharina , Bierbaum Gabriele , Glaeser Stefanie P. , Grohmann Elisabeth , Arredondo-Hernández René , Mulder Ines , Pulami Dipen , Smalla Kornelia , Zarfl Christiane , Siebe Christina , Siemens Jan
Published: January 2025

Investments in “Clean water and sanitation” drive a transition from irrigation with untreated to irrigation with treated wastewater. While this transition reduces many health risks, it may decrease crop yields, and soil carbon storage, cause a release of accumulated pollutants from soils, and increase the spread of antibiotic resistance in the environment. A holistic view on multiple SDGs is necessary to maximize benefits and minimize risks of wastewater treatment for irrigation.
Chromosome-level genome assembly and annotation of the gynogenetic large-scale loach (Paramisgurnus dabryanus)
Authors: Zhang Lei , Zhang Wanting , Cheng Yingyin , Fang Yutong , Guan Xin , Gong Ao , Jiang Yanxin , Duan You , Huang Lei , Younas Waqar , Wang Yaping , Shi Mijuan , Xia Xiao-Qin
Published: January 2025

Abstracts

The large-scale loach (Paramisgurnus dabryanus; Cypriniformes: Cobitidae) is primarily distributed in East Asia. It is an important economic fish species characterized by fast growth, temperature-dependent sex determination and the ability to breathe air. Currently, molecular mechanism studies related to some aspects such as sex determination, toxicology, feed nutrition, growth and genetic evolution have been conducted. However, the lack of a high-quality reference genome has hindered further research. In this study, we performed PacBio HiFi and Hi-C sequencing on a female (ZW) specimen and assembled the first high-quality chromosome-level genome of the large-scale loach. The assembled genome comprises 24 chromosomes, with a total length of 1.04 Gb, a scaffold N50 of 41.7 Mb, and a BUSCO completeness of 95.8%, including 28,311 protein-coding genes. These findings not only provide new insights into the genome structure of the large-scale loach but also establish a crucial reference point for omics studies and serve as an essential genomic resource for breeding programs in this species.
Remaining useful life prediction of lithium-ion batteries using a novel particle flow filter framework with grey model
Authors: Shuai Wang , Yiting Li , Shoubin Zhou , Lifei Chen , Pecht Michael
Published: January 2025

Remaining useful life (RUL) prediction is a crucial aspect of the prognostics health management of lithium-ion batteries (LIBs). Owing to the influence of resampling technology, particle degradation is often observed in the particle filter-based RUL prediction of LIBs, resulting in a low prediction accuracy and large uncertainty. In this paper, a novel particle flow filter with the grey model method (GM-PFF) is proposed to forecast the RUL and state of health of batteries. First, the least squares method is employed to obtain the initial values for double exponential empirical model parameters. Subsequently, the grey model is used to predict the current cycle capacity of LIBs as an observation value for the particle flow filter, solving the inaccurate estimation problem of the state of particle flow filter observation values, and the particle flow filter method is employed to update model parameters. Finally, a test dataset is divided into early, middle, and late stages to predict the RUL of LIBs and obtain the probability distributions. On the CALCE and NASA PCoE LIB dataset, GM-PFF reduces RMSE by 1% compared to PFF, exhibiting a higher prediction accuracy and effectively addressing the particle degradation problem.
Global transcriptional modulation and nutritional status of soybean plants following foliar application of zinc borate as a suspension concentrate fertilizer
Authors: Vendemiatti Eloisa , Moreira Rafael Oliveira , dos Reis Gabriel Lasmar , Hernandez-De Lira Inty Omar , Peña-Yewtukhiw Eugenia , Hippler Franz Walter Rieger , Torres-Dorante Luis Omar , Pavuluri Kiran , Valentine Alex , Nascimento Vitor L. , Benedito Vagner Augusto
Published: January 2025

The management of micronutrients, such as boron (B) and zinc (Zn), is critical for plant growth and crop yields. One method of rapid intervention crop management to mitigate nutritional deficiency is the foliar supply of B and Zn. Our study investigates the effect of foliar-supplied B and Zn availability on the global transcriptional modulation in soybean (Glycine max). The transcriptional response to B was more widespread compared to Zn. RNA-Seq of leaves under different B levels revealed modulated genes with potential roles in nutritional homeostasis and stress response that may be key to controlling B status in the plant. We also identified putative B transporters whose expression levels were significantly affected by B supplementation with foliar fertilization of plants growing under low B conditions. Furthermore, a gene lacking functional annotation (Glyma.03G180300) emerged as a novel potential marker of B status. Two genes (Glyma.16G118000, Glyma.16G199000) were consistently induced by Zn availability, highlighting their potential as biomarkers for assessing its status in soybean plants. This work advances our understanding of nutritional homeostasis in soybean plants and identifies target genes and potential molecular mechanisms involved in nutritional response. Our study informs fertilizer design targeting specific nutrient transporters, thereby enhancing nutrient efficiency in crops.
Label-free proteomic analysis of Duchenne and Becker muscular dystrophy showed decreased sarcomere proteins and increased ubiquitination-related proteins
Authors: da Silva Juliana Cristina Tobar , Nogueira Mariângela Rangel Alves , da Silva Yara Martins , Nogueira Fábio César Sousa , Canedo Nathalie Henriques Silva , Carneiro Katia , de Abreu Pereira Denise
Published: January 2025

Muscular dystrophies (MD) are a group of hereditary diseases marked by progressive muscle loss, leading to weakness and degeneration of skeletal muscles. These conditions often result from structural defects in the Dystrophin–Glycoprotein Complex (DGC), as seen in Duchenne Muscular Dystrophy (DMD) and Becker Muscular Dystrophy (BMD). Since MDs currently have no cure, research has focused on identifying potential therapeutic targets to improve patients’ quality of life. In this study, skeletal muscle tissue samples from DMD and BMD patients, as well as non-dystrophic controls, were analyzed using label-free mass spectrometry (MS/MS) to characterize the proteomic profile of these conditions and identify biomarkers for differential diagnosis. In-silico analysis revealed that dystrophic muscle tissues are linked to biological processes related to cellular energy metabolism, including oxidation of organic compounds, energy production, and cellular respiration. Enrichment of functions associated with cell structure and RNA binding was also observed, including cytoskeletal protein binding and RNA binding. The human phenotypes most related to the proteomic signature were abnormal circulating metabolites, muscle physiology, and weakness. Quantitative analysis identified significant changes in proteins associated with sarcomere organization and protein ubiquitination, such as myomesin, myozenin, and E3 ubiquitin-protein ligase rififylin, suggesting these as potential therapeutic targets.
DLCDroid an android apps analysis framework to analyse the dynamically loaded code
Authors: Bhan Rati , Pamula Rajendra , Kumar K Susheel , Jyotish Nand Kumar , Tripathi Prasun Chandra , Faruki Parvez , Gajrani Jyoti
Published: January 2025

To combat dynamically loaded code in anti-emulated environments, DLCDroid is an Android app analysis framework. DL-CDroid uses the reflection API to effectively identify information leaks due to dynamically loaded code within malicious apps, incorporating static and dynamic analysis techniques. The Dynamically Loaded Code (DLC) technique employs Java features to allow Android apps to dynamically expand their functionality at runtime. Unfortunately, malicious app developers often exploit DLC techniques to transform seemingly benign apps into malware once installed on real devices. Even the most sophisticated static analysis tools struggle to detect data breaches caused by DLC. Our analysis demonstrates that conventional tools areill-equipped to handle DLC. DLCDroid leverages dynamic code interposition techniques for API hooking to expose concealed malicious behavior without requiring modifications to the Android framework. DLCDroid can unveil suspicious behavior that remains hidden when relying solely on static analysis. We evaluate DLCDroid’s performance using a dataset comprising real-world benign and malware apps from reputed repositories like VirusShare and the Google Play Store. Compared to state-of-the-art approaches, the results indicate a significant improvement in detecting sensitive information leaks, more than 95.6% caused by reflection API. Furthermore, we enhance DLCDroid’s functionality by integrating it with an event-based trigger solution, making the framework more scalable and fully automated in its analysis process.
Machine learning approach for noninvasive intracranial pressure estimation using pulsatile cranial expansion waveforms
Authors: Frigieri Gustavo , Brasil Sérgio , Cardim Danilo , Czosnyka Marek , Ferreira Matheus , Paiva Wellingson S. , Hu Xiao
Published: January 2025

Noninvasive methods for intracranial pressure (ICP) monitoring have emerged, but none has successfully replaced invasive techniques. This observational study developed and tested a machine learning (ML) model to estimate ICP using waveforms from a cranial extensometer device (brain4care [B4C] System). The model explored multiple waveform parameters to optimize mean ICP estimation. Data from 112 neurocritical patients with acute brain injuries were used, with 92 patients randomly assigned to training and testing, and 20 reserved for independent validation. The ML model achieved a mean absolute error of 3.00 mmHg, with a 95% confidence interval within ±7.5 mmHg. Approximately 72% of estimates from the validation sample were within 0-4 mmHg of invasive ICP values. This proof-of-concept study demonstrates that noninvasive ICP estimation via the B4C System and ML is feasible. Prospective studies are needed to validate the model’s clinical utility across diverse settings.
Human response times are governed by dual anticipatory processes with distinct neural signatures
Authors: Ramayya Ashwin G. , Buch Vivek , Richardson Andrew , Lucas Timothy , Gold Joshua I.
Published: January 2025

Human behavior is strongly influenced by anticipation, but the underlying neural mechanisms are poorly understood. We obtained intracranial electrocephalography (iEEG) measurements in neurosurgical patients as they performed a simple sensory-motor task with variable (short or long) foreperiod delays that affected anticipation of the cue to respond. Participants showed two forms of anticipatory response biases, distinguished by more premature false alarms (FAs) or faster response times (RTs) on long-delay trials. These biases had distinct neural signatures in prestimulus neural activity modulations that were distributed and intermixed across the brain: the FA bias was most evident in preparatory motor activity immediately prior to response-cue presentation, whereas the RT bias was most evident in visuospatial activity at the beginning of the foreperiod. These results suggest that human anticipatory behavior emerges from a combination of motor-preparatory and attention-like modulations of neural activity, implemented by anatomically widespread and intermixed, but functionally identifiable, brain networks.