bluuebunny/crossref_metadata_2025 huggingface dataset:
Remolding the tumor microenvironment by bacteria augments adoptive T cell therapy in advanced-stage solid tumors
Authors: Zhu Chaojie , Liu Chao , Wu Qing , Sheng Tao , Zhou Ruyi , Ren En , Zhang Ruizhe , Zhao Zhengjie , Shi Jiaqi , Shen Xinyuan , Sun Zhongquan , Mao Zhengwei , He Kaixin , Zhang Lingxiao , Ding Yuan , Gu Zhen , Wang Weilin , Li Hongjun
Published: November 2024

The intricate tumor microenvironment presents formidable obstacles to the efficacy of adoptive T cell therapy in the management of solid tumors by limiting the infiltration and inducing exhaustion of the transferred T cells. Here, we developed a bacterial-based adjuvant approach that augments the efficacy of adoptive T-cell therapy for solid tumor treatment. Our study reveals that intratumor injection of E. coli MG1655 normalizes tumor vasculatures and reprograms tumor-associated macrophages into M1 phenotype that produce abundant CCL5, together facilitating tumor infiltration of adoptively transferred T cells. The depletion of tumor-associated macrophages or CCL5 neutralization in vivo leads to the significantly decreased solid tumor infiltration of adoptive T cells in the presence of bacteriotherapy. This combinatorial therapy, consisting of E. coli adjuvant and adoptive T-cell therapy, effectively eradicates early-stage melanoma and inhibits the progression of pancreatic tumors. Notably, this dual strategy also strengthened the distal tumor control capabilities of adoptive T-cell therapy through the induction of in situ tumor vaccination. This dual therapeutic approach involving bacterial therapy targeting the interior of solid tumors and adoptive T-cell therapy attacking the tumor periphery exhibits potent therapeutic efficacy in achieving the eradication of advanced-stage tumors, including melanoma and hepatocellular carcinoma, by converging attacks from both inside and outside the tumor tissues.
Neoadjuvant oncolytic virus orienx010 and toripalimab in resectable acral melanoma: a phase Ib trial
Authors: Liu Jiayong , Wang Xuan , Li Zhongwu , Gao Shunyu , Mao Lili , Dai Jie , Li Caili , Cui Chuanliang , Chi Zhihong , Sheng Xinan , Lai Yumei , Tan Zhichao , Lian Bin , Tang Bixia , Yan Xieqiao , Li Siming , Zhou Li , Wei Xiaoting , Li Juan , Guo Jun , Si Lu
Published: November 2024

Neoadjuvant PD-1 inhibitor is promising in cutaneous melanoma but remains unknown in acral melanoma (AM). This phase Ib trial study (Clinicaltrials.gov NCT04197882) assessed the efficacy and safety of the combination of neoadjuvant oncolytic virus orienX010 (ori) and anti-PD-1 toripalimab (tori) for resectable AM. Thirty patients of stage III/IV received neoadjuvant therapy of ori and tori for 12 weeks before surgery, followed by adjuvant treatment with tori for 1 year. Primary endpoints were radiographic and pathological response rates, with secondary endpoints of 1- and 2-year recurrence-free survival (RFS) rates, event-free survival (EFS) rates, and safety. Twenty-seven completed surgery and tori adjuvant treatment and median follow-up was 35.7 months. Radiographic and pathological response rates were 36.7% and 77.8%, with complete response rates of 3.3% and 14.8%, 1- and 2-year RFS rates of 85.2% and 81.5%, and 1- and 2-year EFS rates of 83% and 73%, respectively. Adverse events occurred in all patients, mainly grade 1–2. There was no correlation between PET/CT evaluation and pathological response or progression-free survival/overall survival. Patients with pathological response showed tumor beds with high tertiary lymphoid structures (TLSs) and tumor-infiltrating lymphocytes (TILs). Cytokines and chemokines analysis showed the combination therapy significantly increases the secretion of proinflammatory cytokines and chemokines in both responders and non-responders. Therefore, neoadjuvant ori and tori demonstrated promising antitumor activity with high response rates and high 2-year RFS/EFS for AM with acceptable tolerability.
Neuroprotective effect of L-DOPA-induced interleukin-13 on striatonigral degeneration in cerebral ischemia
Authors: Jeon Eunhae , Seo Myeong-Seong , Lkhagva-Yondon Enkhmaa , Lim Yu-Ree , Kim Seung-Woo , Kang Yu Jeong , Lee Jun Seok , Lee Byoung Dae , Wi Rayul , Won So-Yoon , Chung Young Cheul , Park Eun S. , Kim Eunhee , Jin Byung Kwan , Jeon Myung-Shin
Published: November 2024

Levodopa (L-DOPA) treatment is a clinically effective strategy for improving motor function in patients with ischemic stroke. However, the mechanisms by which modulating the dopamine system relieves the pathology of the ischemic brain remain unclear. Emerging evidence from an experimental mouse model of ischemic stroke, established by middle cerebral artery occlusion (MCAO), suggested that L-DOPA has the potential to modulate the inflammatory and immune response that occurs during a stroke. Here, we aimed to demonstrate the therapeutic effect of L-DOPA in regulating the systemic immune response and improving functional deficits in mice with ischemia. Transient MCAO led to progressive degeneration of nigrostriatal dopamine neurons and significant rotational behavior in mice. Exogenous L-DOPA treatment attenuated the striatonigral degeneration and reversed motor behavioral impairment. Notably, treatment with L-DOPA significantly increased IL-13 but reduced IFN-γ in infarct lesions. To investigate the role of IL-13 in motor behavior, we stereotaxically injected anti-IL-13 antibodies into the infarct area of the mouse brain one week after MCAO, followed by L-DOPA treatment. The intervention reduced dopamine, IL-13, and IL-10 levels and exacerbated motor function. IL-13 is potentially expressed on CD4 T cells, while IL-10 is mainly expressed on microglia rather than astrocytes. Finally, IL-13 activates the phagocytosis of microglia, which may contribute to neuroprotection by eliminating degenerating neurons. Our study provides evidence that the L-DOPA-activated dopamine system modulates peripheral immune cells, resulting in the expression of anti-inflammatory and neuroprotective cytokines in mice with ischemic stroke.
Two-gigapascal-strong ductile soft magnets
Authors: Han Liuliu , Peter Nicolas J. , Maccari Fernando , Kovács András , Wang Jin , Zhang Yixuan , Xie Ruiwen , Wu Yuxiang , Schwaiger Ruth , Zhang Hongbin , Li Zhiming , Gutfleisch Oliver , Dunin-Borkowski Rafal E. , Raabe Dierk
Published: November 2024

Soft magnetic materials (SMMs) are indispensable for electromechanical energy conversion in high-efficiency applications, but they are exposed to increasing mechanical loading conditions in electric motors due to higher rotational speeds. Enhancing the yield strength of SMMs is essential to prevent the degradation in magnetic performance and failure from plastic deformation, yet most SMMs have yield strengths far below one gigapascal. Here, we present a multicomponent nanostructuring strategy that doubles the yield strength of SMMs while maintaining ductility. We introduce morphologically anisotropic nanoprecipitates through dislocation-driven precipitation induced by preceding deformation during heat treatment in an iron–nickel–cobalt–tantalum material. With all dimensions of the precipitates below the magnetic domain wall width, we achieve a high precipitate number density with a large specific surface area, small interprecipitate spacing, and high lattice mismatch, which impede dislocation glide and strengthen the material. Both the matrix and precipitates are ferromagnetic, yielding a high magnetic moment. This nanostructuring approach offers a pathway to two-gigapascal-strong ductile SMMs with moderately increased coercivity that can be tolerated in exchange for significantly improved mechanical performance for sustainable electrification.
A green solvent enables precursor phase engineering of stable formamidinium lead triiodide perovskite solar cells
Authors: Gallant Benjamin M. , Holzhey Philippe , Smith Joel A. , Choudhary Saqlain , Elmestekawy Karim A. , Caprioglio Pietro , Levine Igal , Sheader Alexandra A. , Hung Esther Y-H. , Yang Fengning , Toolan Daniel T. W. , Kilbride Rachel C. , Zaininger Karl-Augustin , Ball James M. , Christoforo M. Greyson , Noel Nakita K. , Herz Laura M. , Kubicki Dominik J. , Snaith Henry J.
Published: November 2024

Perovskite solar cells (PSCs) offer an efficient, inexpensive alternative to current photovoltaic technologies, with the potential for manufacture via high-throughput coating methods. However, challenges for commercial-scale solution-processing of metal-halide perovskites include the use of harmful solvents, the expense of maintaining controlled atmospheric conditions, and the inherent instabilities of PSCs under operation. Here, we address these challenges by introducing a high volatility, low toxicity, biorenewable solvent system to fabricate a range of 2D perovskites, which we use as highly effective precursor phases for subsequent transformation to α-formamidinium lead triiodide (α-FAPbI3), fully processed under ambient conditions. PSCs utilising our α-FAPbI3 reproducibly show remarkable stability under illumination and elevated temperature (ISOS-L-2) and “damp heat” (ISOS-D-3) stressing, surpassing other state-of-the-art perovskite compositions. We determine that this enhancement is a consequence of the 2D precursor phase crystallisation route, which simultaneously avoids retention of residual low-volatility solvents (such as DMF and DMSO) and reduces the rate of degradation of FA+ in the material. Our findings highlight both the critical role of the initial crystallisation process in determining the operational stability of perovskite materials, and that neat FA+-based perovskites can be competitively stable despite the inherent metastability of the α-phase.
CO2-promoted photocatalytic aryl migration from nitrogen to carbon for switchable transformation of N-arylpropiolamides
Authors: Liu Ge , Ma Denghui , Zhang Jianchen , Yang Fanyuanhang , Gao Yuzhen , Su Weiping
Published: November 2024

Photocatalytic N-to-C aryl migration allows for quick construction of highly useful amide derivatives from readily available compounds. By developing the reactions of sodium sulfinates with the N-aryl-propiolamides, we herein demonstrate that the CO2-promoted visible-light-induced method enables a large variety of aryl groups on nitrogen atoms of the N-arylamides to undergo efficient aryl migration from N atom to C atom to synthesize tetra- and tri-substituted alkenyl amides selectively. 1,4-N-to-C aryl migration is a key step in this transformation which is achieved through photocatalytic radical-polar crossover pathway. The protocol exhibits the remarkably tolerant of the electronic properties of the migrating aryl substituent, as both electron-rich and -poor arenes are compatible with the migration process. As a result, this protocol features with a broad substrate scope, as demonstrated by more than 90 examples including complex bioactive compounds. Notably, abundant, nontoxic and low-cost CO2 acted as an essential and irreplaceable additive to enable the tetra- and tri-substituted alkenyl amides to be synthesized with excellent selectivity.
Allostery can convert binding free energies into concerted domain motions in enzymes
Authors: Galenkamp Nicole Stéphanie , Zernia Sarah , Van Oppen Yulan B. , van den Noort Marco , Milias-Argeitis Andreas , Maglia Giovanni
Published: November 2024

Enzymatic mechanisms are typically inferred from structural data. However, understanding enzymes require unravelling the intricate dynamic interplay between dynamics, conformational substates, and multiple protein structures. Here, we use single-molecule nanopore analysis to investigate the catalytic conformational changes of adenylate kinase (AK), an enzyme that catalyzes the interconversion of various adenosine phosphates (ATP, ADP, and AMP). Kinetic analysis validated by hidden Markov models unravels the details of domain motions during catalysis. Our findings reveal that allosteric interactions between ligands and cofactor enable converting binding energies into directional conformational changes of the two catalytic domains of AK. These coordinated motions emerged to control the exact sequence of ligand binding and the affinity for the three different substrates, thereby guiding the reactants along the reaction coordinates. Interestingly, we find that about 10% of enzymes show altered allosteric regulation and ligand affinities, indicating that a subset of enzymes folds in alternative catalytically active forms. Since molecules or proteins might be able to selectively stabilize one of the folds, this observation suggests an evolutionary path for allostery in enzymes. In AK, this complex catalytic framework has likely emerged to prevent futile ATP/ADP hydrolysis and to regulate the enzyme for different energy needs of the cell.
An inhibitory segment within G-patch activators tunes Prp43-ATPase activity during ribosome assembly
Authors: Portugal-Calisto Daniela , Geiger Alexander Gregor , Rabl Julius , Vadas Oscar , Oborská-Oplová Michaela , Mazur Jarosław , Richina Federica , Klingauf-Nerurkar Purnima , Michel Erich , Leitner Alexander , Boehringer Daniel , Panse Vikram Govind
Published: November 2024

Mechanisms by which G-patch activators tune the processive multi-tasking ATP-dependent RNA helicase Prp43 (DHX15 in humans) to productively remodel diverse RNA:protein complexes remain elusive. Here, a comparative study between a herein and previously characterized activators, Tma23 and Pxr1, respectively, defines segments that organize Prp43 function during ribosome assembly. In addition to the activating G-patch, we discover an inhibitory segment within Tma23 and Pxr1, I-patch, that restrains Prp43 ATPase activity. Cryo-electron microscopy and hydrogen-deuterium exchange mass spectrometry show how I-patch binds to the catalytic RecA-like domains to allosterically inhibit Prp43 ATPase activity. Tma23 and Pxr1 contain dimerization segments that organize Prp43 into higher-order complexes. We posit that Prp43 function at discrete locations on pre-ribosomal RNA is coordinated through toggling interactions with G-patch and I-patch segments. This could guarantee measured and timely Prp43 activation, enabling precise control over multiple RNA remodelling events occurring concurrently during ribosome formation.
Emerging insights in senescence: pathways from preclinical models to therapeutic innovations
Authors: Mansfield Luke , Ramponi Valentina , Gupta Kavya , Stevenson Thomas , Mathew Abraham Binoy , Barinda Agian Jeffilano , Herbstein Florencia , Morsli Samir
Published: November 2024

Senescence is a crucial hallmark of ageing and a significant contributor to the pathology of age-related disorders. As committee members of the young International Cell Senescence Association (yICSA), we aim to synthesise recent advancements in the identification, characterisation, and therapeutic targeting of senescence for clinical translation. We explore novel molecular techniques that have enhanced our understanding of senescent cell heterogeneity and their roles in tissue regeneration and pathology. Additionally, we delve into in vivo models of senescence, both non-mammalian and mammalian, to highlight tools available for advancing the contextual understanding of in vivo senescence. Furthermore, we discuss innovative diagnostic tools and senotherapeutic approaches, emphasising their potential for clinical application. Future directions of senescence research are explored, underscoring the need for precise, context-specific senescence classification and the integration of advanced technologies such as machine learning, long-read sequencing, and multifunctional senoprobes and senolytics. The dual role of senescence in promoting tissue homoeostasis and contributing to chronic diseases highlights the complexity of targeting these cells for improved clinical outcomes.
Neural network potential for dislocation plasticity in ceramics
Authors: Zhang Shihao , Li Yan , Suzuki Shuntaro , Nakamura Atsutomo , Ogata Shigenobu
Published: November 2024

Dislocations in ceramics are increasingly recognized for their promising potential in applications such as toughening intrinsically brittle ceramics and tailoring functional properties. However, the atomistic simulation of dislocation plasticity in ceramics remains challenging due to the complex interatomic interactions characteristic of ceramics, which include a mix of ionic and covalent bonds, and highly distorted and extensive dislocation core structures within complex crystal structures. These complexities exceed the capabilities of empirical interatomic potentials. Therefore, constructing neural network potentials (NNPs) emerges as the optimal solution. Yet, creating a training dataset that includes dislocation structures proves difficult due to the complexity of their core configurations in ceramics and the computational demands of density functional theory for large atomic models containing dislocation cores. In this work, we propose a training dataset from properties that are easier to compute via high-throughput calculation. Using this dataset, we have successfully developed NNPs for dislocation plasticity in ceramics, specifically for three typical functional ceramics: ZnO, GaN, and SrTiO3. These NNPs effectively capture the nonstoichiometric and charged core structures and slip barriers of dislocations, as well as the long-range electrostatic interactions between charged dislocations. The effectiveness of this dataset was further validated by measuring the similarity and uncertainty across snapshots derived from large-scale simulations, alongside extensive validation across various properties. Utilizing the constructed NNPs, we examined dislocation plasticity in ceramics through nanopillar compression and nanoindentation, which demonstrated excellent agreement with experimental observations. This study provides an effective framework for constructing NNPs that enable the detailed atomistic modeling of dislocation plasticity, opening new avenues for exploring the plastic behavior of ceramics.
Awake versus asleep deep brain stimulation targeting the caudal zona incerta for essential tremor
Authors: Stenmark Persson Rasmus , Blomstedt Yulia , Fytagoridis Anders , Hariz Marwan , Blomstedt Patric
Published: November 2024

To compare awake and asleep deep brain stimulation (DBS) surgery for Essential Tremor (ET), we conducted this retrospective cohort study of patients consecutively operated with DBS targeting the caudal Zona incerta (cZi). 37 underwent surgery awake and 55 asleep. Tremor before surgery and on/off stimulation one year after surgery were evaluated using the Essential Tremor Rating Scale (ETRS). Procedural time, electrode localization, stimulation parameters and adverse events were noted and compared. ETRS scores were similar at baseline between the groups except for contralateral arm tremor, which was slightly worse in the awake group. Total ETRS, contralateral arm tremor and activities of daily living scores showed no significant difference between the groups on-stimulation at one-year follow-up. Compared to the awake group, the asleep group had shorter procedural time and lower stimulation parameters. There were no intracranial haemorrhages nor surgery site-infections. Both groups showed a good improvement of tremor at one-year follow-up. Image-guided DBS surgery targeting the cZi enables safe and efficient asleep surgery for ET.
CelloType: a unified model for segmentation and classification of tissue images
Authors: Pang Minxing , Roy Tarun Kanti , Wu Xiaodong , Tan Kai
Published: November 2024

Cell segmentation and classification are critical tasks in spatial omics data analysis. Here we introduce CelloType, an end-to-end model designed for cell segmentation and classification for image-based spatial omics data. Unlike the traditional two-stage approach of segmentation followed by classification, CelloType adopts a multitask learning strategy that integrates these tasks, simultaneously enhancing the performance of both. CelloType leverages transformer-based deep learning techniques for improved accuracy in object detection, segmentation and classification. It outperforms existing segmentation methods on a variety of multiplexed fluorescence and spatial transcriptomic images. In terms of cell type classification, CelloType surpasses a model composed of state-of-the-art methods for individual tasks and a high-performance instance segmentation model. Using multiplexed tissue images, we further demonstrate the utility of CelloType for multiscale segmentation and classification of both cellular and noncellular elements in a tissue. The enhanced accuracy and multitask learning ability of CelloType facilitate automated annotation of rapidly growing spatial omics data.
Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days
Authors: Nunn Brook L. , Timmins-Schiffman Emma , Mudge Miranda C. , Plubell Deanna L. , Chebli Gabriella , Kubanek Julia , Riffle Michael , Noble William S. , Harvey Elizabeth , Nunn Tasman A. , Rynearson Tatiana , Huntemann Marcel , LaButti Kurt , Foster Brian , Foster Bryce , Roux Simon , Palaniappan Krishnaveni , Mukherjee Supratim , Reddy T. B. K. , Daum Chris , Copeland Alex , Chen I-Min A. , Ivanova Natalia N. , Kyrpides Nikos C. , Glavina del Rio Tijana , Eloe-Fadrosh Emiley A.
Published: November 2024

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.
GAFchromic EBT film lateral resolution and contrast reproduction in the UV-blue range
Authors: Garzella Francesco , Insero Giacomo , Battisti Antonella , Sgarbossa Antonella , Mello Tommaso , Fusi Franco , Romano Giovanni
Published: November 2024

The sensitivity of radiochromic films to UV-blue light is increasingly considered for light dosimetry purposes, owing to their bidimensional detection capabilities and ease of use. While film response to radiation intensity has been widely investigated by commercial scanners, spatial resolution studies remain scarce, especially for small field-of-view applications. These are of growing interest due to the antimicrobial or photo-bio-stimulating effects of UV-blue light sources in in vitro, ex vivo and in vivo models, where precise knowledge of irradiation conditions with adequate spatial resolution is crucial. In this study, we report the spatial lateral resolution and contrast reproduction of GAFchromic EBT2 and EBT3 models. Upon film irradiation by a 405 nm laser source or 365 nm LED, a confocal microscope setup was employed to read the film response at 405, 470, 488, 532 and 570 nm wavelengths, with radiant exposure of 10–70 J/cm2. The measured lateral resolution ranged from 8 to 33 μm. The film capability to reproduce contrast across various spatial frequencies (4–14 lines/mm) was evaluated using modulation transfer function analysis with irradiation performed at 365 nm and 405 nm, revealing a pronounced dependency on both radiant exposure and reading wavelength. These results confirm the film capacity to detect and resolve light intensity variability with a ~ 10 μm resolution, with notable applications in micro-beam profiling and light dosimetry.
HDBind: encoding of molecular structure with hyperdimensional binary representations
Authors: Jones Derek , Zhang Xiaohua , Bennion Brian J. , Pinge Sumukh , Xu Weihong , Kang Jaeyoung , Khaleghi Behnam , Moshiri Niema , Allen Jonathan E. , Rosing Tajana S.
Published: November 2024

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.
Exploiting activation radiation from neutron tomography reveals the hidden elemental composition of 3D art objects for free
Authors: Li Yueer , Creange Sara , Zhou Zhou , Southworth William , Pappot Arie , van Eijck Lambert
Published: November 2024

Neutron tomography is gaining popularity particularly in cultural heritage research, for non-destructively analysing the inner structure of bulk metal artefacts, such as bronzes, but the induced temporary decay radiation is often considered as a drawback. However, this delayed gamma-emission can be put to good use: by performing gamma spectroscopy after neutron tomography, the interior elemental composition of artefacts can be obtained “for free”. Inspired by this, we propose a ray-tracing approach to non-invasively quantify both interior geometry and elemental composition using only a single neutron tomography experiment. This strategy aligns well with both the aim for efficient use of neutron beam time and the expectation from curators and conservators for minimal neutron irradiation. Here, we outline the core principle of this method, demonstrate the extent of its quantification capability on bulk objects of known composition by fusing neutron tomography and delayed-gamma spectroscopy data sets. We also showcase its practical application on an ancient solid-cast Indonesian bronze statuette, by which we gain insights into how the pristine inner bronze segregated into a different composition than the surrounding shell. Similarly, the method allows us to quantify the composition of a hidden offering in the statuette that consecrates the bronze for worship purposes.
The importance of boundary evolution for solar-wind modelling
Authors: Owens Mathew J. , Barnard Luke , Arge Charles N.
Published: November 2024

The solar wind is a continual outflow of plasma and magnetic field from the Sun’s upper atmosphere—the corona—that expands to fills the solar system. Variability in the near-Earth solar-wind conditions can produce adverse space weather that impacts ground- and space-based technologies. Consequently, numerical fluid models of the solar wind are used to forecast conditions a few days ahead. The solar-wind inner-boundary conditions are supplied by models of the corona that are, in turn, constrained by observations of the photospheric magnetic field. While solar eruptions—coronal mass ejections (CMEs)—are treated as time-dependent structures, a single coronal “snapshot” is typically used to determine the ambient solar-wind for a complete model run. Thus, all available time-history information from previous coronal-model solutions is discarded and the solar wind is treated as a steady-state flow, unchanging in the rotating frame of the Sun. In this study, we use 1 year of daily-updated coronal-model solutions to comprehensively compare steady-state solar-wind modelling with a time-dependent method. We demonstrate, for the first time, how the SS approach can fundamentally misrepresent the accuracy of coronal models. We also attribute three key problems with current space-weather forecasting directly to the steady-state approach: (1) the seemingly paradoxical result that forecasts based on observations from 3-days previous are more accurate than forecasts based on the most recent observations; (2) high inconsistency, with forecasts for a given day jumping significantly as new observations become available, changing CME propagation times by up to 17 h; and (3) insufficient variability in the heliospheric magnetic field, which controls solar energetic particle propagation to Earth. The time-dependent approach is shown to alleviate all three issues. It provides a consistent, physical solution which more accurately represents the information present in the coronal models. By incorporating the time history in the solar wind along the Sun-Earth line, the time-dependent approach will provide improvements to forecasting CME propagation to Earth.
Prospective appraisal of clinical diagnostic algorithms for hepatocellular carcinoma surveillance in Chinese patients with chronic hepatitis B infection
Authors: Chan Henry L. Y. , Hu Yao , Malinowsky Katharina , Madin Kairat , Kroeniger Konstantin , Hou Jinlin , Sharma Ashish
Published: November 2024

Hepatocellular carcinoma (HCC) is often detected at advanced stages among patients with hepatitis B virus (HBV), underscoring the urgency for more precise surveillance tests. Here, we compare the clinical performance of the novel - GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], protein-induced by vitamin K absence-II [PIVKA-II]) and GALAD (gender [biological sex], age, AFP, Lens-culinaris AFP [AFP-L3]), PIVKA-II) algorithms to assess the utility of AFP-L3 for distinguishing HCC from benign chronic liver disease (CLD) in Chinese patients with predominantly chronic HBV infection. Eligible adults were enrolled, and biomarkers were measured using Elecsys (Cobas) or µTASWAKO assays. In total, 411 participants provided serum samples (HCC, n = 176 [early-stage, n = 110]; CLD, n = 136; specificity n = 101). HBV was the underlying disease etiology for most participants (HCC, 95%; benign CLD, 72%). For GAAD (Cobas), GALAD (Cobas), and GALAD (µTASWAKO), AUCs were 93.1% (95% CI: 90.0–96.2), 93.2% (90.0–96.3), and 92.7% (88.4–96.9) for early-stage, and 95.6% (93.6–97.6), 95.6% (93.6–97.7), and 95.8% (93.2–98.3) for all-stage HCC, versus CLD, respectively. Interestingly, both GAAD and GALAD algorithms demonstrated comparable diagnostic performance regardless of disease etiology (HBV vs. non-HBV), presence of cirrhosis, geographic region, and within pan-tumor specificity panels (p < 0.001), indicating AFP-L3 may have a negligible role in HCC surveillance.
RLS-associated MEIS transcription factors control distinct processes in human neural stem cells
Authors: Kittke Volker , Zhao Chen , Lam Daniel D. , Harrer Philip , Krezel Wojciech , Schormair Barbara , Oexle Konrad , Winkelmann Juliane
Published: November 2024

MEIS1 and MEIS2 encode highly conserved homeodomain transcription factors crucial for developmental processes in a wide range of tissues, including the brain. They can execute redundant functions when co-expressed in the same cell types, but their roles during early stages of neural differentiation have not been systematically compared. By separate knockout and overexpression of MEIS1 and MEIS2 in human neural stem cells, we find they control specific sets of target genes, associated with distinct biological processes. Integration of DNA binding sites with differential transcriptomics implicates MEIS1 to co-regulate gene expression by interaction with transcription factors of the SOX and FOX families. MEIS1 harbors the strongest risk factor for restless legs syndrome (RLS). Our data suggest that MEIS1 can directly regulate the RLS-associated genes NTNG1, MDGA1 and DACH1, constituting new approaches to study the elusive pathomechanism or RLS.
Theoretical study on the prediction of optical properties and thermal stability of fullerene nanoribbons
Authors: Bai Haonan , Gai Xinwen , Sun Lulu , Ma Ji
Published: November 2024

In this work, we predicted two different configurations of fullerene nanoribbons (quasi-hexagonal phase (qHP) and quasi-tetragonal phase (qTP)) based on two-dimensional fullerenes, with widths of 1, 2, and 3 fullerene units, respectively. Based on first-principles calculations and ab-initio molecular dynamics (AIMD), the thermal stability and optical properties of six fullerene nanoribbons were predicted. AIMD studies indicate that wider qHP nanoribbons (qHPs) exhibit better thermal stability, while increased temperatures lead to greater instability. In contrast, qHP-3 shows the best thermal stability among the six structures. Then, the optical gap between the calculated and experimental quasi-hexagonal two-dimensional fullerenes is compared to illustrate the accuracy of the calculation. The absorption spectra of six fullerene nanoribbons were calculated and the anisotropy of light absorption was analyzed. Finally, the charge transfer modes of each excited state were visualized through electron-hole density plots. This work provides an essential theoretical foundation for understanding new all-carbon materials, specifically fullerenes.
Association of smoking with knee osteoarthritis structural defects and symptoms: an individual participant data meta-analysis
Authors: Salis Zubeyir , Sainsbury Amanda
Published: November 2024

Prior meta-analyses have suggested a protective link between smoking and knee osteoarthritis (KOA), but they relied on aggregate data, potentially obscuring the true relationship. To address this limitation, we conducted an Individual Participant Data (IPD) meta-analysis using data from three large cohorts: the Osteoarthritis Initiative (OAI), the Multicenter Osteoarthritis Study (MOST), and the Cohort Hip and Cohort Knee (CHECK) study. Participants from 16 centers in the USA and Netherlands were categorized as current, former, or never smokers. We assessed six outcomes, three related to structural changes over 4–5 years of follow-up, and three related to changes in KOA symptoms over 2–2.5 years, 5 years, and 7–8 years of follow-up. First, the incidence of radiographic KOA was evaluated in 10,072 knees, defined as having a Kellgren-Lawrence grade ≥ 2 (‘radiographic KOA’) at follow-up but not at baseline. Second, the progression of radiographic KOA was evaluated in 5274 knees, defined as an increase in Kellgren–Lawrence grade between baseline and follow-up in knees that had radiographic KOA at baseline. Third, the incidence of symptomatic KOA was evaluated in 12,910 knees, defined as having radiographic KOA in addition to symptoms at follow-up but not at baseline. Fourth, fifth, and sixth, we investigated changes between baseline and all follow-ups in scores for the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscales of pain, disability, and stiffness (in 2640 knees). There were no differences between smoking groups in any of these six outcomes. Our study, leveraging data from three large cohorts and the advantages of IPD, finds no evidence that smoking offers any protection against KOA, refuting the notion that smoking may benefit joint health.
The early transcriptional and post-transcriptional responses to fluconazole in sensitive and resistant Candida albicans
Authors: Stevens Irene , Silao Fitz Gerald , Huch Susanne , Liu Honglian , Ryman Kicki , Carvajal-Jimenez Adriana , Ljungdahl Per O. , Pelechano Vicent
Published: November 2024

Candida albicans is a leading cause of fungal infections in immunocompromised patients. Management of candidemia relies on a few antifungal agents, with fluconazole being first line therapy. The emergence of fluconazole-resistant strains highlights the pressing need to improve our molecular understanding of the drug response mechanisms. By sequencing the 5’P mRNA degradation intermediates, we establish that co-translational mRNA decay occurs in C. albicans and characterize how in vivo 5´-3´ exonuclease degradation trails the last translating ribosome. Thus, the study of the 5’ Phosphorylated mRNA degradome (5PSeq) offers a simple and affordable way to measure ribosome dynamics and identify codon specific ribosome stalls in response to drugs and amino acid deprivation. Building upon this, we combine RNA-Seq and 5PSeq to study the early response of sensitive and resistant C. albicans isolates to fluconazole. Our results highlight that transcriptional responses, rather than changes in ribosome dynamics, are the main driver of Candida resistance to fluconazole.
The role of PM2.5 exposure in lung cancer: mechanisms, genetic factors, and clinical implications
Authors: Chen Chi-Yuan , Huang Kuo-Yen , Chen Chin-Chuan , Chang Ya-Hsuan , Li Hsin-Jung , Wang Tong-Hong , Yang Pan-Chyr
Published: November 2024

Lung cancer is one of the most critical global health threats, as the second most common cancer and leading cause of cancer deaths globally. While smoking is the primary risk factor, an increasing number of cases occur in nonsmokers, with lung cancer in nonsmokers (LCNS) now recognized as the fifth leading cause of cancer mortality worldwide. Recent evidence identifies air pollution, particularly fine particulate matter (PM2.5), as a significant risk factor in LCNS. PM2.5 can increase oxidative stress and inflammation, induce genetic alterations and activation of oncogenes (including the epidermal growth factor receptor, EGFR), and contribute to lung cancer progression. This review summarizes the current understanding of how exposure to PM2.5 induces lung carcinogenesis and accelerates lung cancer development. It underscores the importance of prevention and early detection while calling for targeted therapies to combat the detrimental effects of air pollution. An integrated approach that combines research, public health policy, and clinical practice is essential to reduce the lung cancer burden and improve outcomes for those affected by PM2.5 exposurrre.
Quantification of dimethylamine in low concentration particulate matter by reducing the concentration of 9-fluorenylmethyl chloroformate
Authors: García-Alonso Susana , Gómez-Moreno Francisco Javier , Alonso-Blanco Elisabeth , Pérez-Pastor Rosa María
Published: November 2024

This study measures trace levels of dimethylamine in ambient air particulate matter by reducing the concentration of 9-fluorenylmethyl chloroformate. This miniaturized method used is cleaner, simpler, and faster for routine monitoring.
A bio-nano-engineered platform fabricated from cerium oxide-carbon nanoparticles stabilized with chitosan for label-free sensing of a lung cancer biomarker
Authors: Mishra Upendra Kumar , Srivastava Saurabh , Singh Kshitij RB , Kumar Atul , Singh Vivekanand , Mishra Devendra P. , Chandel Vishal Singh , Singh Jay , Pandey Shyam S. , Srivastava Saurabh
Published: November 2024

This study reports the synthesis of CeO2 and its nanocomposite with carbon nanoparticles stabilized by the chitosan polymer matrix for the early detection of a cancer biomarker.
Chiral recognition of amino acids through homochiral metallacycle [ZnCl2L]2
Authors: Maqbool Maria , Ayub Khurshid
Published: November 2024

Chiral discrimination of the enantiomers of alanine.
Construction of strontium-loaded injectable lubricating hydrogel and its role in promoting repair of cartilage defects
Authors: Duan Congcong , Jiang Hongyue , Zhang Shichen , Wang Yixing , Liu Peng , Xu Bin , Tian Wenjing , Han Bing
Published: November 2024

We incorporated Sr2+ into GelMA and combined it with FT to form a dual-network hydrogel. The FT network would provide lubrication to the defect area under shear force, while the release of Sr2+ would contribute positively to defect repair.
Cultivating the future leaders of chemical biology
Authors: Rulka Anna , Adams Elizabeth , Kawamura Akane , Wallace Stephen
Published: November 2024

The inaugural RSC Chemistry Biology Interface Community Leadership Retreat for Early Career Researchers provides unique and immersive training in diverse research skills essential to emerging future leaders in chemical biology.
Borates vs. aluminates: comparing the anion for lithium-ion batteries
Authors: Ould Darren M. C. , Penrod Megan E. , McConnell Jessica B. , Zabara Mohammed A. , Berge Astrid H. , O’Keefe Christopher A. , Bond Andrew D. , Menkin Svetlana , Grey Clare P. , Wright Dominic S.
Published: November 2024

Of a series of related borate and aluminate salts investigated, the unsolvated aluminate Li[Al(hfip)4] (hfip = (CF3)2CHO) resulted in superior battery cycling and is a promising electrolyte for next-generation lithium batteries.
Palladium-catalyzed annulation and intermolecular hydroamination involving norbornene derivatives: synthesis of indanones and N-alkylamines
Authors: Li Wenguang , Cheng Xinfeng , Cao Man , Sheng Heyun , Gao Wenchao , Chen Ming , Zhang Xu , Li Wentao , Yu Yongqi , Li Ting
Published: November 2024

A palladium-catalyzed divergent reaction of primary benzamides using norbornene derivatives as a controlled switch is reported. When NBE is used, indanones are synthesized. Employing norbornadiene instead of NBE enables the assembly of N-alkylamines.
Study of flux growth of Cr-containing borates and oxyborates under the conditions of low Cr2O3 solubility
Authors: Moshkina Evgeniya , Mikhashenok Natalya , Kokh Dieter , Pavlovskiy Maxim , Cherepakhin Alexander , Eremin Evgeniy , Zolotov Andrey , Molokeev Maxim
Published: November 2024

Due to the deep study of crystallization processes in multicomponent flux systems based on Bi2Mo3O12 and Li2WO4, we managed to obtain HoCr3(BO3)4 and Cu2CrBO5 crystals of enough size for orientational physical property measurements.
First-principles study on the adsorption and sensing properties of methyl acetate on VTe2 doped systems (Ti, Sc, Ru, Y)
Authors: Wang Guan-nan , Zhang Hong
Published: November 2024

The adsorption of methyl acetate gas on VTe2 sensors doped with four different metal atoms was studied using first-principles calculations. The electronic properties and recovery times were discussed.
Examining the reactivity of oxygen-bridged intramolecular group 13 element/phosphorus and boron/group 15 element frustrated Lewis pairs in 1,2-addition reactions with CS2
Authors: Wu Shi-Hao , Su Ming-Der
Published: November 2024

Our computational findings indicate that only oxygen-bridged intramolecular B/P-Rea, Al/P-Rea, Ga/P-Rea, and In/P-Rea FLPs can promote the 1,2-addition reaction with CS2, both kinetically and thermodynamically.
Benzene hydrogenation utilizing organometallic early transition metal precursors
Authors: Johnson Reece , Hu Peijie , Pugh James , Haridasan Rahul Koottanil , Searles Keith
Published: November 2024

The catalytic hydrogenation of C6H6 occurs when both group IV and group V organometallic precursors are used. Catalytic conversion of C6H6 to C6H12 occurs with high turnover frequencies (80–160 °C, 400 psi H2, TOF = up to 1155 mol C6H6 mol M−1 h−1).
Quenching-induced lattice modifications endowing Li-rich layered cathodes with ultralow voltage decay and long life
Authors: Zeng Lingcai , Liang Haoyan , Wang Yaqian , Ying Xiaolong , Qiu Bao , Pan Jiajie , Zhang Yibin , Wen Wen , Wang Xuechun , Gu Qingwen , Li Junhao , Shi Kaixiang , Shen Yanbin , Liu Quanbing , Liu Zhaoping
Published: November 2024

A versatile brine-quenching strategy implements a combined surface-bulk-compatible structure design to modulate the intrinsic redox properties of Li-rich layered oxides, ultimately achieving ultra-long lifetimes and negligible voltage decay.
Digitally-assisted structure design of a large-size proton exchange membrane fuel cell
Authors: Huo Wenming , Fan Linhao , Xu Yunfei , Benbouzid Mohamed , Xu Wenzhen , Gao Fei , Li Weizhuo , Shan Nian , Xie Biao , Huang Haipeng , Liu Bohao , Amirat Yassine , Fang Chuan , Li Xiaohui , Gan Quanquan , Li Feiqiang , Jiao Kui
Published: November 2024

A digitally-assisted method is proposed to accelerate the structure design of large-size proton exchange membrane fuel cells, including backward engineering and forward design.
Optimization of Fenton-like reaction pathways using Ov-containing ZnO@nitrogen-rich porous carbon: the electron transfer and 1O2 triggered non-radical process
Authors: Zhang Zhenfeng , Xiong Tianli , Peng Haihao , Zhang Honglin , He Siying , Liu Xuran , Liu Yanan , Feng Wenyi , Yang Zhaohui , Xiong Weiping
Published: November 2024

There is not much research on how to control the PDS reaction pathway. This work reports that Ov-containing ZnO@nitrogen-rich porous carbon composites activate PDS to remove SMZ only through 1O2 and electron transfer.
Effect of fermented soybean on metabolic outcomes, anthropometric indices, and body composition: a systematic review and meta-analysis of clinical trials
Authors: Maleki Sedgi Fatemeh , Mozaffari Nazanin , Pashaei Mohammad Reza , Hajizadeh-Sharafabad Fatemeh
Published: November 2024

The aim of the current study was to systematically review and quantify the findings of randomized controlled trials (RCTs) assessing the effect of fermented soy products on anthropometric indices, body composition, and metabolic outcomes.
Structures and properties of the mono- and diprotonated species of acetylenedicarbonyl fluoride
Authors: Hollenwäger Dirk , Nitzer Alexander , Leitz Dominik , Kornath Andreas J.
Published: November 2024

Acetylenedicarbonyl fluoride is obtained monoprotonated in XF/SbF5 (X = H, D). The diprotonation is obtained by a decomposition in R-134a. The Z-conformation of the protonated acyl fluorides was investigated on the MP2-aug-cc-pVTZ level of theory.
Cellulose-based activated carbon aerogels as electrode materials for high capacitance performance supercapacitors
Authors: Yang Kai , Huang Xinfeng , Zhang Yuchun , Fu Peng
Published: November 2024

By comparing the types and proportions of activators, the suitable activation conditions for cellulose-based carbon aerogels are determined, and high-energy-density electrode materials are prepared.
Development of nonisocyanate polyurethane–MWCNT nanocomposites: coatings with enhanced antifouling, corrosion resistance and UV protection properties
Authors: Sulthana Yasmin R. , Gurusamy Thangavelu Senthil A.
Published: November 2024

Castor oil cyclic carbonate and sustainable linalool diamine were subjected to polyaddition to form nonisocyanate polyurethanes (NIPU) and NIPU nanocomposites (NIPU-NC) with MWCNTs / functionalized MWCNTs via non-covalent and covalent incorporation.
Self-powered triboelectric sensor using GaN nanowires and stress concentration structure
Authors: Noh Siyun , Shin Jaehyeok , Jhee Seunghwan , Kang Sumin , Lee Yumin , Kim Jin Soo
Published: November 2024

A self-powered triboelectric sensor with GaN nanowires using a nanoridge structure inspired by the structure of the human epidermis and dermis.