bluuebunny/crossref_metadata_2025_split huggingface dataset:
Muscle and fat composition in patients with newly diagnosed multiple myeloma
Authors: Abdallah Nadine H. , Nagayama Hiroki , Takahashi Naoki , Gonsalves Wilson , Fonder Amie , Dispenzieri Angela , Dingli David , Buadi Francis K. , Lacy Martha Q. , Hobbs Miriam , Gertz Morie A. , Binder Moritz , Kapoor Prashant , Warsame Rahma , Hayman Suzanne R. , Kourelis Taxiarchis , Hwa Yi L. , Lin Yi , Kyle Robert A. , Rajkumar S. Vincent , Broski Stephen M. , Kumar Shaji K. 
Published: December 2023

AbstractMeasures of muscle and adipose tissue mass have been associated with outcomes in several malignancies, but studies in multiple myeloma (MM) are inconsistent. The aim of this study was to evaluate the association between muscle and fat areas and radiodensity, and overall survival (OS) in patients with newly diagnosed MM. We included 341 patients diagnosed with MM from 2010–2019 who had an 18F-fluorodeoxyglucose positron emission tomography/computed tomography at diagnosis. A cross-sectional image at the third lumbar vertebrae was segmented into muscle and fat components. Median follow up was 5.7 years. There was no association between sarcopenia and baseline disease characteristics or OS. Low muscle radiodensity was associated with higher disease stage, anemia, and renal failure. OS was 5.6 vs. 9.0 years in patients with muscle radiodensity in the lower vs. middle/upper tertiles, respectively (P = 0.02). High subcutaneous adipose tissue (SAT) radiodensity was associated with higher stage, anemia, thrombocytopenia, hypercalcemia, renal failure, and high LDH. OS was 5.4 years vs. not reached in patients with SAT radiodensity in the upper vs. middle/lower tertiles, respectively (P = 0.001). In conclusion, sarcopenia was not associated with OS in MM patients. High SAT radiodensity and low muscle radiodensity were associated with advanced disease stage and adverse laboratory characteristics.
Inhibition of demethylase by IOX1 modulates chromatin accessibility to enhance NSCLC radiation sensitivity through attenuated PIF1
Authors: Li Qian , Qin Kexin , Tian Yushan , Chen Biao , Zhao Guoping , Xu Shengmin , Wu Lijun 
Published: December 2023

AbstractChromatin accessibility is a critical determinant of gene transcriptional expression and regulated by histones modification. However, the potential for manipulating chromatin accessibility to regulate radiation sensitivity remains unclear. Our findings demonstrated that the histone demethylase inhibitor, 5-carboxy-8-hydroxyquinoline (IOX1), could enhance the radiosensitivity of non-small cell lung cancer (NSCLC) in vitro and in vivo. Mechanistically, IOX1 treatment reduced chromatin accessibility in the promoter region of DNA damage repair genes, leading to decreased DNA repair efficiency and elevated DNA damage induced by γ irradiation. Notably, IOX1 treatment significantly reduced both chromatin accessibility and the transcription of phytochrome interacting factor 1 (PIF1), a key player in telomere maintenance. Inhibition of PIF1 delayed radiation-induced DNA and telomeric DNA damage repair, as well as increased radiosensitivity of NSCLC in vitro and in vivo. Further study indicated that the above process was regulated by a reduction of transcription factor myc-associated zinc finger protein (MAZ) binding to the distal intergenic region of the PIF1. Taken together, IOX1-mediated demethylase inactivation reduced chromatin accessibility, leading to elevated telomere damage which is partly due to PIF1 inhibition, thereby enhancing NSCLC radiosensitivity.
Metal toxin threat in wildland fires determined by geology and fire severity
Authors: Lopez Alandra Marie , Pacheco Juan Lezama , Fendorf Scott 
Published: December 2023

AbstractAccentuated by climate change, catastrophic wildfires are a growing, distributed global public health risk from inhalation of smoke and dust. Underrecognized, however, are the health threats arising from fire-altered toxic metals natural to soils and plants. Here, we demonstrate that high temperatures during California wildfires catalyzed widespread transformation of chromium to its carcinogenic form in soil and ash, as hexavalent chromium, particularly in areas with metal-rich geologies (e.g., serpentinite). In wildfire ash, we observed dangerous levels (327-13,100 µg kg−1) of reactive hexavalent chromium in wind-dispersible particulates. Relatively dry post-fire weather contributed to the persistence of elevated hexavalent chromium in surficial soil layers for up to ten months post-fire. The geographic distribution of metal-rich soils and fire incidents illustrate the broad global threat of wildfire smoke- and dust-born metals to populations. Our findings provide new insights into why wildfire smoke exposure appears to be more hazardous to humans than pollution from other sources.
California’s zero-emission vehicle adoption brings air quality benefits yet equity gaps persist
Authors: Yu Qiao , He Brian Yueshuai , Ma Jiaqi , Zhu Yifang 
Published: December 2023

AbstractZero-emission vehicle (ZEV) adoption is a key climate mitigation tool, but its environmental justice implications remain unclear. Here, we quantify ZEV adoption at the census tract level in California from 2015 to 2020 and project it to 2035 when all new passenger vehicles sold are expected to be ZEVs. We then apply an integrated traffic model together with a dispersion model to simulate air quality changes near roads in the Greater Los Angeles. We found that per capita ZEV ownership in non-disadvantaged communities (non-DACs) as defined by the state of California is 3.8 times of that in DACs. Racial and ethnic minorities owned fewer ZEVs regardless of DAC designation. While DAC residents receive 40% more pollutant reduction than non-DACs due to intercommunity ZEV trips in 2020, they remain disproportionately exposed to higher levels of traffic-related air pollution. With more ZEVs in 2035, the exposure disparity narrows. However, to further reduce disparities, the focus must include trucks, emphasizing the need for targeted ZEV policies that address persistent pollution burdens among DAC and racial and ethnic minority residents.
CENP-A and CENP-B collaborate to create an open centromeric chromatin state
Authors: Nagpal Harsh , Ali-Ahmad Ahmad , Hirano Yasuhiro , Cai Wei , Halic Mario , Fukagawa Tatsuo , Sekulić Nikolina , Fierz Beat 
Published: December 2023

AbstractCentromeres are epigenetically defined via the presence of the histone H3 variant CENP-A. Contacting CENP-A nucleosomes, the constitutive centromere associated network (CCAN) and the kinetochore assemble, connecting the centromere to spindle microtubules during cell division. The DNA-binding centromeric protein CENP-B is involved in maintaining centromere stability and, together with CENP-A, shapes the centromeric chromatin state. The nanoscale organization of centromeric chromatin is not well understood. Here, we use single-molecule fluorescence and cryoelectron microscopy (cryoEM) to show that CENP-A incorporation establishes a dynamic and open chromatin state. The increased dynamics of CENP-A chromatin create an opening for CENP-B DNA access. In turn, bound CENP-B further opens the chromatin fiber structure and induces nucleosomal DNA unwrapping. Finally, removal of CENP-A increases CENP-B mobility in cells. Together, our studies show that the two centromere-specific proteins collaborate to reshape chromatin structure, enabling the binding of centromeric factors and establishing a centromeric chromatin state.
Cell-type-directed design of synthetic enhancers
Authors: Taskiran Ibrahim I. , Spanier Katina I. , Dickmänken Hannah , Kempynck Niklas , Pančíková Alexandra , Ekşi Eren Can , Hulselmans Gert , Ismail Joy N. , Theunis Koen , Vandepoel Roel , Christiaens Valerie , Mauduit David , Aerts Stein 
Published: December 2023

AbstractTranscriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2–6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create ‘dual-code’ enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.
Deep in situ microscopy for real-time analysis of mammalian cell populations in bioreactors
Authors: Guez Jean-Sébastien , Lacroix Pierre-Yves , Château Thierry , Vial Christophe 
Published: December 2023

AbstractAn in situ microscope based on pulsed transmitted light illumination via optical fiber was combined to artificial-intelligence to enable for the first time an online cell classification according to well-known cellular morphological features. A 848 192-image database generated during a lab-scale production process of antibodies was processed using a convolutional neural network approach chosen for its accurate real-time object detection capabilities. In order to induce different cell death routes, hybridomas were grown in normal or suboptimal conditions in a stirred tank reactor, in the presence of substrate limitation, medium addition, pH regulation problem or oxygen depletion. Using such an optical system made it possible to monitor real-time the evolution of different classes of animal cells, among which viable, necrotic and apoptotic cells. A class of viable cells displaying bulges in feast or famine conditions was also revealed. Considered as a breakthrough in the catalogue of process analytical tools, in situ microscopy powered by artificial-intelligence is also of great interest for research.
A hybrid dependency-based approach for Urdu sentiment analysis
Authors: Sehar Urooba , Kanwal Summrina , Allheeib Nasser I. , Almari Sultan , Khan Faiza , Dashtipur Kia , Gogate Mandar , Khashan Osama A. 
Published: December 2023

AbstractIn the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse backgrounds, races, cultures, and age groups, spanning a wide range of topics. Businesses can leverage this data to extract valuable insights, improve their services, and effectively reach a broader audience based on users’ expressed opinions on social media platforms. To harness the potential of this extensive and unstructured data, a deep understanding of Natural Language Processing (NLP) is crucial. Existing approaches for sentiment analysis (SA) often rely on word co-occurrence frequencies, which prove inefficient in practical scenarios. Identifying this research gap, this paper presents a framework for concept-level sentiment analysis, aiming to enhance the accuracy of sentiment analysis (SA). A comprehensive Urdu language dataset was constructed by collecting data from YouTube, consisting of various talks and reviews on topics such as movies, politics, and commercial products. The dataset was further enriched by incorporating language rules and Deep Neural Networks (DNN) to optimize polarity detection. For sentiment analysis, the proposed framework employs predefined rules to trigger sentiment flow from words to concepts, leveraging the dependency relations among different words in a sentence based on Urdu language grammatical rules. In cases where predefined patterns are not triggered, the framework seamlessly switches to its sub-symbolic counterpart, passing the data to the DNN for sentence classification. Experimental results demonstrate that the proposed framework surpasses state-of-the-art approaches, including LSTM, CNN, SVM, LR, and MLP, achieving an improvement of 6–7% on Urdu dataset. In conclusion, this research paper introduces a novel framework for concept-level sentiment analysis of Urdu language data sourced from social media platforms. By combining language rules and DNN, the proposed framework demonstrates superior performance compared to existing methodologies, showcasing its effectiveness in accurately analyzing sentiment in Urdu text data.
Direct ink writing of high-resolution cellulose structures
Authors: Rezaei Farnaz , Carlsson Daniel O. , Hedin Dahlstrom Jimmy , Lindh Jonas , Johansson Stefan 
Published: December 2023

Abstract3D printing is envisioned to play an important role in the production of membranes for e.g., water purification and bio-separation applications due to the prospect of creating new and cleverly designed structures. Among different 3D printing techniques, direct ink writing offers the opportunity to print a wide variety of materials with high-detail resolution. There is a range of parameters that need to be optimized in order to develop robust printing techniques at that scale. In this study, cellulose acetate (CA), which is a biocompatible material, has been used as an ink. In order to examine the printability and the possibility of printing features as small as a few µm, nozzles with different diameters and inks with varying amounts and molecular weights of CA were investigated. Findings in this study indicate that, depending on the wetting on the underlaying structure, the nozzle's internal and external diameter affects the detail resolution of the printed structure. Different inks result in different widths of printed strands and generally a higher amount and higher molecular weights of CA results in higher detail resolution. However, too high amount of CA and molecular weight will increase the clogging risk in the nozzle. In this study, the internal size of the nozzle was 3 µm, and by selecting a suitable ink, it was possible to print strands down to 1 µm size and 6 µm inter-strand distance in the air, bridging supports with limited sagging. Furthermore, wall structures consisting of 300 layers, corresponding to about 300 µm in total height, were successfully printed.
Quantum Hall coherent perfect absorption in graphene
Authors: Jahani Dariush , Alikhani Mohammadreza , Abdi Yaser 
Published: December 2023

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absorption in a two-dimensional electron gas (2DEG) with Dirac spectrum is demonstrated to be obtained by controlling the interference of multiple incident radiations, referred to as coherent perfect absorption (CPA). However, when a 2DEG such as graphene is exposed to a magnetostatic bias, it resonantly could absorb electromagnetic radiation by transitions of its Dirac electrons between non-equidistant and nonlinear Landau levels. Here, the magneto-optical terahertz (THz) CPA in graphene under the quantum Hall effect (QHE) regime at both strong and subtesla magnetostatic bias fields is addressed. Our findings show that an effective magneto-optical surface conductivity corresponding to right- and left-handed circular (RHC- and LHC) polarizations could model a magneto-tunable CPA in graphene in THz range. Significantly, graphene under QHE regime reveals different tunable CPA properties for each circularly polarized beams by the intensity of the applied magnetic bias. Moreover, it is observed that different phase modulations at CPA frequencies are achieved for RHC and LHC polarizations. Considering the maximum efficiency for a 2D absorber, our results demonstrate the magnetostatic tuning of CPA in 2D Dirac materials for long-wavelength sensing applications and signal processing.
Application research on reducing radiation-induced lung injury with a trigger operator based on overlap volume histogram (OVH) in breast cancer postoperative radiotherapy
Authors: Li Qianyan , Deng Feifei , Pan Xiang , Bai Han , Bai Jie , Liu Xuhong , Chen Feihu , Ge Ren 
Published: December 2023

AbstractThis study aims to develop a trigger operator based on the Overlap Volume Histogram (OVH) and examined its effectiveness in enhancing plan quality to minimize radiation-induced lung injury in postoperative radiotherapy for breast cancer. This trigger operator was applied for plan re-optimization to the previous Volumetric Modulated Arc Therapy (VMAT) plans of 16 left breast conserving surgery cases. These cases were categorized into a Contiguous Group (CG) and a Separated Group (SG) based on the relative position between the target and the Left-Lung (L-Lung). We investigated the changes in Vx, mean dose, and Normal Tissue Complication Probability (NTCP) values of organs-at-risk (OARs) before and after using the trigger operator. The Pairwise Sample T test was employed to evaluate the differences in indices between the two groups before and after optimizations. The trigger operator effectively initiated plan re-optimization. The values of V5, V10, V20, V30, and V40 of the L-Lung, as well as the mean dose of the heart, all decreased after re-optimization. The Pairwise Sample T test results showed statistically significant differences in the V20, V30, and V40 of the L-Lung in the CG (P < 0.01), and in the V5, V10, V20, V30, and V40 of the L-Lung in the SG (P < 0.01). Our findings suggest that the proposed trigger operator can improve plan quality, thereby reducing radiation-induced lung injury in postoperative radiotherapy for breast cancer.
A pilot study on the immune cell proteome of long COVID patients shows changes to physiological pathways similar to those in myalgic encephalomyelitis/chronic fatigue syndrome
Authors: Peppercorn Katie , Edgar Christina D. , Kleffmann Torsten , Tate Warren P. 
Published: December 2023

AbstractOf those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ~ 10% develop the chronic post-viral debilitating condition, long COVID (LC). Although LC is a heterogeneous condition, about half of cases have typical post-viral fatigue with onset and symptoms that are very similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). A key question is whether these conditions are closely related. ME/CFS is a post-stressor fatigue condition that arises from multiple triggers. To investigate the pathophysiology of LC, a pilot study of patients (n = 6) and healthy controls (n = 5) has used quantitative proteomics to discover changes in peripheral blood mononuclear cell (PBMC) proteins. A principal component analysis separated all long COVID patients from healthy controls. Analysis of 3131 proteins identified 162 proteins differentially regulated, of which 37 were related to immune functions, and 21 to mitochondrial functions. Markov cluster analysis identified clusters involved in immune system processes, and two aspects of gene expression-spliceosome and transcription. These results were compared with an earlier dataset of 346 differentially regulated proteins in PBMC’s from ME/CFS patients (n = 9) analysed by the same methodology. There were overlapping protein clusters and enriched molecular pathways particularly in immune functions, suggesting the two conditions have similar immune pathophysiology as a prominent feature, and mitochondrial functions involved in energy production were affected in both conditions.
Numerical investigation on flow, heat and mass transfer performance of fractional Oldroyd-B hybrid nanofluid as a coolant for power battery
Authors: Xu Xiaoqin 
Published: December 2023

AbstractThis paper introduced for the first time a viscoelastic hybrid nanofluid as the coolant for direct contact cooling power battery. The governing boundary layer equations were established by adopting fractional Oldroyd-B model and fractional Buongiorno’s model. Second-order velocity slip boundary conditions were also considered. Then the solutions were numerically acquired by finite difference coupled with L1 algorithm. Impact of main physical parameters on the flow, heat and mass transfer of the viscoelastic hybrid nanofluid on the cylindrical battery was graphically presented and detailly discussed. Outcomes show that the heat transfer is improved by both Brownian motion(Nb) and thermophoresis(Nt) to different degrees. When Nb grows from 0.05 to 0.1, the average Nusselt number increases by 2.2%, higher than 0.027% of Nt. The slip behavior only affects the velocity distribution near the individual cell and slightly enhances heat and mass transfer. The velocity relaxation fractional derivative contributes to convection, heat and mass transfer on the cell wall, while velocity retardation fractional derivative behaves just the opposite. The proposed viscoelastic hybrid nanofluid with appropriate volume fractions of nanoparticles enhances heat transfer on the cell wall and is strongly recommended as a candidate for power battery coolant.
Acute enhancement of Romanian deadlift performance after consumption of caffeinated chewing gum
Authors: Chen Chun-Hung , Wu Shih-Hao , Shiu Yi-Jie , Yu Sheng-Yan , Chiu Chih-Hui 
Published: December 2023

AbstractThis study investigates the effect of the consumption of caffeinated chewing gum on the performance of Romanian deadlift on the flywheel training device. A total of 19 participants completed a randomized, cross-over, single-blind experiment with food-grade caffeinated chewing gum trial (CAF) or placebo trail (PL). Gum were chewed for 10 min and rest for 15 min prior to the Romanian deadlift test using the inertial resistance training machine. 5 sets of 6 Romanian deadlifts were performed, with a 3-min rest between sets, followed by a 7-day washout period before the next set of trials. The average power, average force, total peak power, peak concentric power, peak eccentric power, heart rate, and rating of perceived exertion (RPE) for each trials were analyzed using paired-T test. Compared to placebo, caffeinated chewing gum trial enhanced peak concentric power (P = 0.016, Cohen's d = 0.44), peak eccentric power (P = 0.005, Cohen's d = 0.55), average power (P = 0.013, Cohen's d = 0.43), and total work (P = 0.026, Cohen's d = 0.28). However, in average force (P = 0.063, Cohen's d = 0.50), RPE (P = 0.266), and heart rate (P = 0.143), were no significant differences between trials. Caffeinated chewing gum with a dose of caffeine of 200 mg for 10 min may acutely enhance Romanian deadlift performance on the flywheel machine.