bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oncogenic EML4-ALK assemblies suppress growth factor perception and modulate drug tolerance
Authors: Gonzalez-Martinez David , Roth Lee , Mumford Thomas R. , Guan Juan , Le Anh , Doebele Robert C. , Huang Bo , Tulpule Asmin , Niewiadomska-Bugaj Magdalena , Bivona Trever G. , Bugaj Lukasz J. 
Published: November 2024

AbstractDrug resistance remains a challenge for targeted therapy of cancers driven by EML4-ALK and related fusion oncogenes. EML4-ALK forms cytoplasmic protein condensates, which result from networks of interactions between oncogene and adapter protein multimers. While these assemblies are associated with oncogenic signaling, their role in drug response is unclear. Here, we use optogenetics and live-cell imaging to find that EML4-ALK assemblies suppress transmembrane receptor tyrosine kinase (RTK) signaling by sequestering RTK adapter proteins including GRB2 and SOS1. Furthermore, ALK inhibition, while suppressing oncogenic signaling, simultaneously releases the sequestered adapters and thereby resensitizes RTK signaling. Resensitized RTKs promote rapid and pulsatile ERK reactivation that originates from paracrine ligands shed by dying cells. Reactivated ERK signaling promotes cell survival, which can be counteracted by combination therapies that block paracrine signaling. Our results identify a regulatory role for RTK fusion assemblies and uncover a mechanism of tolerance to targeted therapies.
Atomically resolved imaging of the conformations and adsorption geometries of individual β-cyclodextrins with non-contact AFM
Authors: Grabarics Márkó , Mallada Benjamín , Edalatmanesh Shayan , Jiménez-Martín Alejandro , Pykal Martin , Ondráček Martin , Kührová Petra , Struwe Weston B. , Banáš Pavel , Rauschenbach Stephan , Jelínek Pavel , de la Torre Bruno 
Published: November 2024

AbstractGlycans, consisting of covalently linked sugar units, are a major class of biopolymers essential to all known living organisms. To better understand their biological functions and further applications in fields from biomedicine to materials science, detailed knowledge of their structure is essential. However, due to the extraordinary complexity and conformational flexibility of glycans, state-of-the-art glycan analysis methods often fail to provide structural information with atomic precision. Here, we combine electrospray deposition in ultra-high vacuum with non-contact atomic force microscopy and theoretical calculations to unravel the structure of β-cyclodextrin, a cyclic glucose oligomer, with atomic-scale detail. Our results, established on the single-molecule level, reveal the different adsorption geometries and conformations of β-cyclodextrin. The position of individual hydroxy groups and the location of the stabilizing intramolecular H-bonds are deduced from atomically resolved images, enabling the unambiguous assignment of the molecular structure and demonstrating the potential of the method for glycan analysis.
Climate change alters the future of natural floristic regions of deep evolutionary origins
Authors: Minev-Benzecry Samuel , Daru Barnabas H. 
Published: November 2024

AbstractBiogeographic regions reflect the organization of biotas over long evolutionary timescales but face alterations from recent anthropogenic climate change. Here, we model species distributions for 189,269 vascular plant species of the world under present and future climates and use this data to generate biogeographic regions based on phylogenetic dissimilarity. Our analysis reveals declines in phylogenetic beta diversity for years 2040 to 2100, leading to a future homogenization of biogeographic regions. While some biogeographic boundaries will persist, climate change will alter boundaries separating biogeographic realms. Such boundary alterations will be determined by altitude variation, heterogeneity of temperature seasonality, and past climate velocity. Our findings suggest that human activities may now surpass the geological forces that shaped floristic regions over millions of years, calling for the mitigation of climate impacts to meet international biodiversity targets.
Sulfate residuals on Ru catalysts switch CO2 reduction from methanation to reverse water-gas shift reaction
Authors: Chen Min , Liu Longgang , Chen Xueyan , Qin Xiaoxiao , Zhang Jianghao , Xie Shaohua , Liu Fudong , He Hong , Zhang Changbin 
Published: November 2024

AbstractEfficient heterogeneous catalyst design primarily focuses on engineering the active sites or supports, often neglecting the impact of trace impurities on catalytic performance. Herein, we demonstrate that even trace amounts of sulfate (SO42−) residuals on Ru/TiO2 can totally change the CO2 reduction from methanation to reverse-water gas shift (RWGS) reaction under atmospheric pressure. We reveal that air annealing causes the trace amount of SO42− to migrate from TiO2 to Ru/TiO2 interface, leading to the significant changes in product selectivity from CH4 to CO. Detailed characterizations and DFT calculations show that the sulfate at Ru/TiO2 interface notably enhances the H transfer from Ru particles to the TiO2 support, weakening the CO intermediate activation on Ru particles and inhibiting the further hydrogenation of CO to CH4. This discovery highlights the vital role of trace impurities in CO2 hydrogenation reaction, and also provides broad implications for the design and development of more efficient and selective heterogeneous catalysts.
Dependence of cyanobacterium growth and Mars-specific photobioreactor mass on total pressure, pN2 and pCO2
Authors: Verseux Cyprien , Ramalho Tiago P. , Bohuon Emma , Kunst Nils , Lang Viktoria , Heinicke Christiane 
Published: November 2024

AbstractIn situ resource utilization systems based on cyanobacteria could support the sustainability of crewed missions to Mars. However, their resource-efficiency will depend on the extent to which gases from the Martian atmosphere must be processed to support cyanobacterial growth. The main purpose of the present work is to help assess this extent. We therefore start with investigating the impact of changes in atmospheric conditions on the photoautotrophic, diazotrophic growth of the cyanobacterium Anabaena sp. PCC 7938. We show that lowering atmospheric pressure from 1 bar down to 80 hPa, without changing the partial pressures of metabolizable gases, does not reduce growth rates. We also provide equations, analogous to Monod’s, that describe the dependence of growth rates on the partial pressures of CO2 and N2. We then outline the relationships between atmospheric pressure and composition, the minimal mass of a photobioreactor’s outer walls (which is dependent on the inner-outer pressure difference), and growth rates. Relying on these relationships, we demonstrate that the structural mass of a photobioreactor can be decreased – without affecting cyanobacterial productivity – by reducing the inner gas pressure. We argue, however, that this reduction would be small next to the equivalent system mass of the cultivation system. A greater impact on resource-efficiency could come from the selection of atmospheric conditions which minimize gas processing requirements while adequately supporting cyanobacterial growth. The data and equations we provide can help identify these conditions.
Efficacy of xanomeline and trospium chloride in schizophrenia: pooled results from three 5-week, randomized, double-blind, placebo-controlled, EMERGENT trials
Authors: Kaul Inder , Sawchak Sharon , Claxton Amy , Sauder Colin , Hassman Howard H. , Kakar Rishi , Walling David P. , Citrome Leslie , Zhu Haiyuan , Miller Andrew C. , Brannan Stephen K. 
Published: November 2024

AbstractIn the 5-week, randomized, double-blind, placebo-controlled EMERGENT-1 (NCT03697252), EMERGENT-2 (NCT04659161), and EMERGENT-3 (NCT04738123) trials, xanomeline and trospium chloride (formerly known as KarXT) significantly improved symptoms of schizophrenia and was generally well tolerated. We pooled data from the EMERGENT trials to further characterize the efficacy of xanomeline/trospium and provide sufficient statistical power to analyze responses in participant subgroups. In pooled analyses, xanomeline/trospium significantly improved Positive and Negative Syndrome Scale (PANSS) total score at week 5 versus placebo (least squares mean difference, –9.9; 95% confidence interval, –12.4, –7.3; p < 0.0001; Cohen’s d effect size, 0.65). PANSS subscale and Clinical Global Impression–Severity scores also improved significantly with xanomeline/trospium versus placebo. Subgroup analyses consistently favored xanomeline/trospium over placebo regardless of differences in participant age, sex, race, body mass index, and baseline PANSS total score. These results add to existing evidence demonstrating robust and reliable improvements in symptoms with xanomeline/trospium across a broad spectrum of people with schizophrenia.
A benchmark for domain adaptation and generalization in smartphone-based human activity recognition
Authors: Napoli Otávio , Duarte Dami , Alves Patrick , Soto Darlinne Hubert Palo , de Oliveira Henrique Evangelista , Rocha Anderson , Boccato Levy , Borin Edson 
Published: November 2024

AbstractHuman activity recognition (HAR) using smartphone inertial sensors, like accelerometers and gyroscopes, enhances smartphones’ adaptability and user experience. Data distribution from these sensors is affected by several factors including sensor hardware, software, device placement, user demographics, terrain, and more. Most datasets focus on providing variability in user and (sometimes) device placement, limiting domain adaptation and generalization studies. Consequently, models trained on one dataset often perform poorly on others. Despite many publicly available HAR datasets, cross-dataset generalization remains challenging due to data format incompatibilities, such as differences in measurement units, sampling rates, and label encoding. Hence, we introduce the DAGHAR benchmark, a curated collection of datasets for domain adaptation and generalization studies in smartphone-based HAR. We standardized six datasets in terms of accelerometer units, sampling rate, gravity component, activity labels, user partitioning, and time window size, removing trivial biases while preserving intrinsic differences. This enables controlled evaluation of model generalization capabilities. Additionally, we provide baseline performance metrics from state-of-the-art machine learning models, crucial for comprehensive evaluations of generalization in HAR tasks.
Assessing temporal dynamics of nitrogen surplus in Indian agriculture: district scale data from 1966 to 2017
Authors: Goyal Shekhar Sharan , Kumar Rohini , Bhatia Udit 
Published: November 2024

AbstractNitrogen (N) is essential for agricultural productivity, yet its surplus poses significant environmental risks. Currently, over half of applied nitrogen is lost, resulting in resource wastage, contributing to increased greenhouse gas emissions and biodiversity loss. Excess nitrogen persists in the environment, contaminating soil and water bodies for decades. Quantifying detailed historical N-surplus estimation in India remains limited, despite national and global-scaled assessments. Our study develops a district-level dataset of annual agricultural N-surplus from 1966-2017, integrating 12 different estimates to address uncertainties arising from multiple data sources and methodological choices across major elements of the N surplus. This dataset supports flexible spatial aggregation, aiding policymakers in implementing effective nitrogen management strategies in India. In addition, we verified our estimates by comparing them with previous studies. This work underscores the importance of setting realistic nitrogen management targets that account for inherent uncertainties, paving the way for sustainable agricultural practices in India, reducing environmental impacts, and boosting productivity.
Narrative predicts cardiac synchrony in audiences
Authors: Hammond Hugo , Armstrong Michael , Thomas Graham A. , Dalmaijer Edwin S. , Bull David R. , Gilchrist Iain D. 
Published: November 2024

AbstractAudio-visual media possesses a remarkable ability to synchronise audiences’ neural, behavioural, and physiological responses. This synchronisation is considered to reflect some dimension of collective attention or engagement with the stimulus. But what is it about these stimuli that drives such strong engagement? There are several properties of media stimuli which may lead to synchronous audience response: from low-level audio-visual features, to the story itself. Here, we present a study which separates low-level features from narrative by presenting participants with the same content but in separate modalities. In this way, the presentations shared no low-level features, but participants experienced the same narrative. We show that synchrony in participants’ heart rate can be driven by the narrative information alone. We computed both visual and auditory perceptual saliency for the content and found that narrative was approximately 10 times as predictive of heart rate as low-level saliency, but that low-level audio-visual saliency has a small additive effect towards heart rate. Further, heart rate synchrony was related to a separate cohorts’ continuous ratings of immersion, and that synchrony is likely to be higher at moments of increased narrative importance. Our findings demonstrate that high-level narrative dominates in the alignment of physiology across viewers.
In-vitro and In-silico evaluation of antimicrobial and antibiofilm effect of Neem oil and Calcium hydroxide nanoparticles against Mutans Streptococci and Enterococcus faecalis isolated from endodontic infections
Authors: Nageeb Wedad M. , Adam Sherouk Hussein , Hashem Nasr , Abdelsalam Nelly 
Published: November 2024

AbstractDifferent Streptococcal species including Streptococcus mutans, Streptococcus sobrinus and Enterococcus faecalis are commonly isolated in root canal infections including refractory, recurrent, and persistent cases. Calcium hydroxide (Ca (OH)2) has been widely used in endodontics as an intracanal medicament. However, using new antimicrobial herbal alternatives offers promising potentials which can be additionally enhanced by using nanoparticles (NPs). In this study, we evaluate the antimicrobial efficacy and antibiofilm effect of Neem oil including its NPs preparations and we compare the effect of conventional Ca (OH)2 to Ca (OH)2 NPs using standard disc diffusion method and quantitative microtitre dish biofilm formation assay against common pathogens isolated from root canal samples. Molecular docking was used to test the binding of 10 Streptococcal macromolecules to 5 candidate neem active constituents. Neem NPs 0.125 mg/ml showed better antibacterial effect than both Neem 15 mg/ml and Neem 0.15 mg/ml. Ca (OH)2 NPs 0.125 mg/ml also showed better antibacterial effect than each of Ca (OH)2 10 mg/ml and Ca (OH)2 0.1 mg/ml. Best biofilm mass inhibition was achieved by Neem oil 0.15 mg/ml at 74.55% ( IQ: 67.36–87.65) and Neem NPs 0.0125 mg/ml at 59.33% (IQ: 51-–75.27). For Ca (OH)2, the best biofilm mass inhibition was observed with Ca (OH)2 NPs 0.125 mg/ml at 54.7% (IQ: 42.37– 77.25). Both neem oil and neem NPs show promising antibacterial and antibiofilm potential against Mutans Streptococci group at low concentrations and hence are good candidates for use as endodontic medications. In silico analysis shows that both Sitosterol and Gedunin appear to be important active constituents of neem and possible drug candidates. Additionally, Ca (OH)2 NPs showed significantly higher antimicrobial effect against Mutans streptococci group than conventional Ca (OH)2 preparations.
A deep learning approach for ovarian cancer detection and classification based on fuzzy deep learning
Authors: El-Latif Eman I. Abd , El-dosuky Mohamed , Darwish Ashraf , Hassanien Aboul Ella 
Published: November 2024

AbstractDifferent oncologists make their own decisions about the detection and classification of the type of ovarian cancer from histopathological whole slide images. However, it is necessary to have an automated system that is more accurate and standardized for decision-making, which is essential for early detection of ovarian cancer. To help doctors, an automated detection and classification of ovarian cancer system is proposed. This model starts by extracting the main features from the histopathology images based on the ResNet-50 model to detect and classify the cancer. Then, recursive feature elimination based on a decision tree is introduced to remove unnecessary features extracted during the feature extraction process. Adam optimizers were implemented to optimize the network’s weights during training data. Finally, the advantages of combining deep learning and fuzzy logic are combined to classify the images of ovarian cancer. The dataset consists of 288 hematoxylin and eosin (H&E) stained whole slides with clinical information from 78 patients. H&E-stained Whole Slide Images (WSIs), including 162 effective and 126 invalid WSIs were obtained from different tissue blocks of post-treatment specimens. Experimental results can diagnose ovarian cancer with a potential accuracy of 98.99%, sensitivity of 99%, specificity of 98.96%, and F1-score of 98.99%. The results show promising results indicating the potential of using fuzzy deep-learning classifiers for predicting ovarian cancer.
Decoding viewer emotions in video ads
Authors: Antonov Alexey , Kumar Shravan Sampath , Wei Jiefei , Headley William , Wood Orlando , Montana Giovanni 
Published: November 2024

AbstractUnderstanding and predicting viewers’ emotional responses to videos has emerged as a pivotal challenge due to its multifaceted applications in video indexing, summarization, personalized content recommendation, and effective advertisement design. A major roadblock in this domain has been the lack of expansive datasets with videos paired with viewer-reported emotional annotations. We address this challenge by employing a deep learning methodology trained on a dataset derived from the application of System1’s proprietary methodologies on over 30,000 real video advertisements, each annotated by an average of 75 viewers. This equates to over 2.3 million emotional annotations across eight distinct categories: anger, contempt, disgust, fear, happiness, sadness, surprise, and neutral, coupled with the temporal onset of these emotions. Leveraging 5-second video clips, our approach aims to capture pronounced emotional responses. Our convolutional neural network, which integrates both video and audio data, predicts salient 5-second emotional clips with an average balanced accuracy of 43.6%, and shows particularly high performance for detecting happiness (55.8%) and sadness (60.2%). When applied to full advertisements, our model achieves a strong average AUC of 75% in determining emotional undertones. To facilitate further research, our trained networks are freely available upon request for research purposes. This work not only overcomes previous data limitations but also provides an accurate deep learning solution for video emotion understanding.
Experimental evidence of phase transition of silica polymorphs in basaltic eucrites: implications for thermal history of protoplanetary crust
Authors: Kanemaru Rei , Imae Naoya , Yamaguchi Akira , Nakato Aiko , Isa Junko , Kimura Makoto , Nishido Hirotsugu , Usui Tomohiro , Mikouchi Takashi 
Published: November 2024

AbstractSilica polymorphs occur under various pressures and temperature conditions, and their characteristics can be used to better understand the complex metamorphic history of planetary materials. Here, we conducted isothermal heating experiments of silica polymorphs in basaltic eucrites to assess their formation and stability. We revealed that each silica polymorph exhibits different metamorphic responses: (1) Quartz recrystallizes into cristobalite when heated at ≥ 1040 °C. (2) Monoclinic (MC) tridymite recrystallizes into no other polymorphs when heated at ≤ 1070 °C. (3) Silica glass recrystallizes into quartz when heated at 900–1010 °C, and recrystallize into cristobalite when heated at ≥ 1040 °C. These results suggest that MC tridymite in eucrites does not recrystallize into other polymorphs during the reheating events, nor does it recrystallize from other silica phases below the solidus temperature of eucrite (~ 1060 °C). Additionally, we found that pseudo-orthorhombic (PO) tridymite crystallizes from quenched melts in the samples heated at ≥ 1070 °C. Previously, cristobalite has been considered as the initial silica phase, which crystallizes from eucritic magma. Our findings suggest that the first crystallizing silica minerals may not always be cristobalite. These require a reconsideration of the formation process of silica minerals in eucrites.
Benchmarking miRNA reference genes in B-cell precursor acute lymphoblastic leukemia
Authors: Mack Teresa , Gianferri Tommaso , Niedermayer Alexandra , Debatin Klaus-Michael , Meyer Lüder H. , Muench Vera 
Published: November 2024

AbstractMicroRNAs (miRNAs) play dual roles in acute lymphoblastic leukemia (ALL) as both tumor suppressors and oncogenes, and miRNA expression profiles can be used for patient risk stratification. Precise assessment of miRNA levels is crucial for understanding their role and function in gene regulation. Quantitative real-time polymerase chain reaction (qPCR) is a reliable, rapid, and cost-effective method for analyzing miRNA expression, assuming that appropriate normalization to stable references is performed to ensure valid data. In this study, we evaluated the stability of six commonly used miRNA references (5sRNA, SNORD44, RNU6, RNU1A1, miR-103a-3p, and miR-532-5p) across nine B-cell precursor (BCP) ALL cell lines, 22 patient-derived xenograft (PDX) BCP ALL samples from different organ compartments of leukemia bearing mice, and peripheral blood mononuclear cells (PBMCs) from six healthy donors. We used four different algorithms (Normfinder, ∆CT, geNorm, and BestKeeper) to assess the most stably expressed reference across all samples. Moreover, we validated our data in an additional set of 13 PDX ALL samples and six healthy controls, identifying miR-103a-3p and miR-532-5p as the most stable references for miRNA normalization in BCP ALL studies. Additionally, we demonstrated the critical importance of using a stable reference to accurately interpret miRNA data.
Innovative hybrid approach: digital and analog fabrication of orbital prosthesis for post-COVID-19 mucormycosis defects using photogrammetry technique
Authors: Bansod Akansha Vilas , Pisulkar Sweta Kale , Beri Arushi , Jain Ritul , Deshmukh Shruti , Umre Utkarsh 
Published: November 2024

AbstractIn addition to anatomical loss, removal of the full or portion of the orbit results in a facial deformity and psychological distress for the patient. This article details a practical case of prosthetic rehabilitation using digital workflow for an orbital deformity caused by post-COVID-19 Mucor mycosis. The main goal of this case study was to create a maxillofacial orbital prosthesis that is well-retained, simple to use, and accurate in terms of appearance. The study addresses the problems involved in fabricating the orbital prosthesis, particularly the unique dimensions and form of the defect, replicating the natural skin tone, and accomplishing retention by the most prudent and patient-friendly approach. Through this article, a digitised algorithm, using photogrammetry technique for facial scan, is suggested for fabricating the prosthesis.