bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting KCa3.1 channels to overcome erlotinib resistance in non-small cell lung cancer cells
Authors: Todesca Luca Matteo , Gerke Matthias , Bulk Emma Etmar , Bachmann Magdalena , Rudersdorf Alisa , Antonuzzo Lorenzo , Pillozzi Serena , Düfer Martina , Szabo Ildiko , Schwab Albrecht 
Published: January 2024

AbstractAlmost all non-small cell lung cancer (NSCLC) patients initially responding to EGFR tyrosine kinase inhibitors (TKIs) develop acquired resistance. Since KCa3.1 channels, expressed in mitochondria and plasma membrane, regulate similar behavioral traits of NSCLC cells as EGFR, we hypothesized that their blockade contributes to overcoming EGFR-TKI resistance. Meta-analysis of microarray data revealed that KCa3.1 channel expression in erlotinib-resistant NSCLC cells correlates with that of genes of integrin and apoptosis pathways. Using erlotinib-sensitive and –resistant NSCLC cells we monitored the role of mitochondrial KCa3.1 channels in integrin signaling by studying cell-matrix adhesion with single-cell force spectroscopy. Apoptosis was quantified with fluorescence-based assays. The function of mitochondrial KCa3.1 channels in these processes was assessed by measuring the mitochondrial membrane potential and by quantifying ROS production. Functional assays were supplemented by biochemical analyses. We show that KCa3.1 channel inhibition with senicapoc in erlotinib-resistant NSCLC cells increases cell adhesion by increasing β1-integrin expression, that in turn depends on mitochondrial ROS release. Increased adhesion impairs migration of NSCLC cells in a 3D matrix. At the same time, the senicapoc-dependent ROS production induces cytochrome C release and triggers apoptosis of erlotinib-resistant NSCLC cells. Thus, KCa3.1 channel blockade overcomes EGFR-TKI resistance by inhibiting NSCLC motility and inducing apoptosis.
Modulation of tumor microenvironment by targeting histone acetylation in bladder cancer
Authors: Nunes Sandra P. , Morales Lucia , Rubio Carolina , Munera-Maravilla Ester , Lodewijk Iris , Suárez-Cabrera Cristian , Martínez Victor G. , Pérez-Escavy Mercedes , Pérez-Crespo Miriam , Alonso Sánchez Miguel , Montesinos Esther , San José-Enériz Edurne , Agirre Xabier , Prósper Felipe , Pineda-Lucena Antonio , Henrique Rui , Dueñas Marta , Correia Margareta P. , Jerónimo Carmen , Paramio Jesús M. 
Published: January 2024

AbstractAlterations in the epigenetic machinery in both tumor and immune cells contribute to bladder cancer (BC) development, constituting a promising target as an alternative therapeutic option. Here, we have explored the effects of a novel histone deacetylase (HDAC) inhibitor CM-1758, alone or in combination with immune checkpoint inhibitors (ICI) in BC. We determined the antitumor effects of CM-1758 in various BC cell lines together with the induction of broad transcriptional changes, with focus on the epigenetic regulation of PD-L1. Using an immunocompetent syngeneic mouse model of metastatic BC, we studied the effects of CM-1758 alone or in combination with anti-PD-L1 not only on tumor cells, but also in the tumor microenvironment. In vitro, we found that CM-1758 has cytotoxic and cytostatic effects either by inducing apoptosis or cell cycle arrest in BC cells at low micromolar levels. PD-L1 is epigenetically regulated by histone acetylation marks and is induced after treatment with CM-1758. We also observed that treatment with CM-1758 led to an important delay in tumor growth and a higher CD8 + T cell tumor infiltration. Moreover, anti-PD-L1 alone or in combination with CM-1758 reprogramed macrophage differentiation towards a M1-like polarization state and increased of pro-inflammatory cytokines systemically, yielding potential further antitumor effects. Our results suggest the possibility of combining HDAC inhibitors with immunotherapies for the management of advanced metastatic BC.
Combining stochastic resetting with Metadynamics to speed-up molecular dynamics simulations
Authors: Blumer Ofir , Reuveni Shlomi , Hirshberg Barak 
Published: January 2024

AbstractMetadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective variables are usually not known a priori and finding them can be very challenging. We recently presented a collective variables-free approach to enhanced sampling using stochastic resetting. Here, we combine the two methods, showing that it can lead to greater acceleration than either of them separately. We also demonstrate that resetting Metadynamics simulations performed with suboptimal collective variables can lead to speedups comparable with those obtained with optimal collective variables. Therefore, applying stochastic resetting can be an alternative to the challenging task of improving suboptimal collective variables, at almost no additional computational cost. Finally, we propose a method to extract unbiased mean first-passage times from Metadynamics simulations with resetting, resulting in an improved tradeoff between speedup and accuracy. This work enables combining stochastic resetting with other enhanced sampling methods to accelerate a broad range of molecular simulations.
The low-density lipoprotein receptor promotes infection of multiple encephalitic alphaviruses
Authors: Ma Hongming , Adams Lucas J. , Raju Saravanan , Sariol Alan , Kafai Natasha M. , Janova Hana , Klimstra William B. , Fremont Daved H. , Diamond Michael S. 
Published: January 2024

AbstractMembers of the low-density lipoprotein receptor (LDLR) family, including LDLRAD3, VLDLR, and ApoER2, were recently described as entry factors for different alphaviruses. However, based on studies with gene edited cells and knockout mice, blockade or abrogation of these receptors does not fully inhibit alphavirus infection, indicating the existence of additional uncharacterized entry factors. Here, we perform a CRISPR-Cas9 genome-wide loss-of-function screen in mouse neuronal cells with a chimeric alphavirus expressing the Eastern equine encephalitis virus (EEEV) structural proteins and identify LDLR as a candidate receptor. Expression of LDLR on the surface of neuronal or non-neuronal cells facilitates binding and infection of EEEV, Western equine encephalitis virus, and Semliki Forest virus. Domain mapping and binding studies reveal a low-affinity interaction with LA domain 3 (LA3) that can be enhanced by concatenation of LA3 repeats. Soluble decoy proteins with multiple LA3 repeats inhibit EEEV infection in cell culture and in mice. Our results establish LDLR as a low-affinity receptor for multiple alphaviruses and highlight a possible path for developing inhibitors that could mitigate infection and disease.
A link between repeating and non-repeating fast radio bursts through their energy distributions
Authors: Kirsten F. , Ould-Boukattine O. S. , Herrmann W. , Gawroński M. P. , Hessels J. W. T. , Lu W. , Snelders M. P. , Chawla P. , Yang J. , Blaauw R. , Nimmo K. , Puchalska W. , Wolak P. , van Ruiten R. 
Published: January 2024

AbstractFast radio bursts (FRBs) are extremely energetic, millisecond-duration radio flashes that reach Earth from extragalactic distances. Broadly speaking, FRBs can be classified as repeating or (apparently) non-repeating. It is still unclear, however, whether the two types share a common physical origin and differ only in their activity rate. Here we report on an observing campaign that targeted one hyperactive repeating source, FRB 20201124A, for more than 2,000 h using four 25–32 m class radio telescopes. We detected 46 high-energy bursts, many more than one would expect given previous observations of lower-energy bursts using larger radio telescopes. We find a high-energy burst distribution that resembles that of the non-repeating FRB population, suggesting that apparently non-repeating FRB sources may simply be the rarest bursts from repeating sources. Also, we discuss how FRB 20201124A contributes strongly to the all-sky FRB rate and how similar sources would be observable even at very high redshift.
African savanna raptors show evidence of widespread population collapse and a growing dependence on protected areas
Authors: Shaw Phil , Ogada Darcy , Dunn Leah , Buij Ralph , Amar Arjun , Garbett Rebecca , Herremans Marc , Virani Munir Z. , Kendall Corinne J. , Croes Barbara M. , Odino Martin , Kapila Shiv , Wairasho Peter , Rutz Christian , Botha André , Gallo-Orsi Umberto , Murn Campbell , Maude Glyn , Thomsett Simon 
Published: January 2024

AbstractThe conversion of natural habitats to farmland is a major cause of biodiversity loss and poses the greatest extinction risk to birds worldwide. Tropical raptors are of particular concern, being relatively slow-breeding apex predators and scavengers, whose disappearance can trigger extensive cascading effects. Many of Africa’s raptors are at considerable risk from habitat conversion, prey-base depletion and persecution, driven principally by human population expansion. Here we describe multiregional trends among 42 African raptor species, 88% of which have declined over a ca. 20–40-yr period, with 69% exceeding the International Union for Conservation of Nature criteria classifying species at risk of extinction. Large raptors had experienced significantly steeper declines than smaller species, and this disparity was more pronounced on unprotected land. Declines were greater in West Africa than elsewhere, and more than twice as severe outside of protected areas (PAs) than within. Worryingly, species suffering the steepest declines had become significantly more dependent on PAs, demonstrating the importance of expanding conservation areas to cover 30% of land by 2030—a key target agreed at the UN Convention on Biological Diversity COP15. Our findings also highlight the significance of a recent African-led proposal to strengthen PA management—initiatives considered fundamental to safeguarding global biodiversity, ecosystem functioning and climate resilience.
Recent gene selection and drug resistance underscore clinical adaptation across Candida species
Authors: Schikora-Tamarit Miquel Àngel , Gabaldón Toni 
Published: January 2024

AbstractUnderstanding how microbial pathogens adapt to treatments, humans and clinical environments is key to infer mechanisms of virulence, transmission and drug resistance. This may help improve therapies and diagnostics for infections with a poor prognosis, such as those caused by fungal pathogens, including Candida. Here we analysed genomic variants across approximately 2,000 isolates from six Candida species (C. glabrata, C. auris, C. albicans, C. tropicalis, C. parapsilosis and C. orthopsilosis) and identified genes under recent selection, suggesting a highly complex clinical adaptation. These involve species-specific and convergently affected adaptive mechanisms, such as adhesion. Using convergence-based genome-wide association studies we identified known drivers of drug resistance alongside potentially novel players. Finally, our analyses reveal an important role of structural variants and suggest an unexpected involvement of (para)sexual recombination in the spread of resistance. Our results provide insights on how opportunistic pathogens adapt to human-related environments and unearth candidate genes that deserve future attention.
Antagonistic interactions between phage and host factors control arbitrium lysis–lysogeny decision
Authors: Zamora-Caballero Sara , Chmielowska Cora , Quiles-Puchalt Nuria , Brady Aisling , Gallego del Sol Francisca , Mancheño-Bonillo Javier , Felipe-Ruíz Alonso , Meijer Wilfried J. J. , Penadés José R. , Marina Alberto 
Published: January 2024

AbstractPhages can use a small-molecule communication arbitrium system to coordinate lysis–lysogeny decisions, but the underlying mechanism remains unknown. Here we determined that the arbitrium system in Bacillus subtilis phage phi3T modulates the bacterial toxin–antitoxin system MazE–MazF to regulate the phage life cycle. We show that phi3T expresses AimX and YosL, which bind to and inactivate MazF. AimX also inhibits the function of phi3T_93, a protein that promotes lysogeny by binding to MazE and releasing MazF. Overall, these mutually exclusive interactions promote the lytic cycle of the phage. After several rounds of infection, the phage-encoded AimP peptide accumulates intracellularly and inactivates the phage antiterminator AimR, a process that eliminates aimX expression from the aimP promoter. Therefore, when AimP increases, MazF activity promotes reversion back to lysogeny, since AimX is absent. Altogether, our study reveals the evolutionary strategy used by arbitrium to control lysis–lysogeny by domesticating and fine-tuning a phage-defence mechanism.
A Dataset of Amphibian Species in U.S. National Parks
Authors: LaFrance Benjamin J. , Ray Andrew M. , Fisher Robert N. , Grant Evan H. Campbell , Shafer Charles , Beamer David A. , Spear Stephen F. , Pierson Todd W. , Davenport Jon M. , Niemiller Matthew L. , Pyron R. Alexander , Glorioso Brad M. , Barichivich William J. , Halstead Brian J. , Roberts Kory G. , Hossack Blake R. 
Published: January 2024

AbstractNational parks and other protected areas are important for preserving landscapes and biodiversity worldwide. An essential component of the mission of the United States (U.S.) National Park Service (NPS) requires understanding and maintaining accurate inventories of species on protected lands. We describe a new, national-scale synthesis of amphibian species occurrence in the NPS system. Many park units have a list of amphibian species observed within their borders compiled from various sources and available publicly through the NPSpecies platform. However, many of the observations in NPSpecies remain unverified and the lists are often outdated. We updated the amphibian dataset for each park unit by collating old and new park-level records and had them verified by regional experts. The new dataset contains occurrence records for 292 of the 424 NPS units and includes updated taxonomy, international and state conservation rankings, hyperlinks to a supporting reference for each record, specific notes, and related fields which can be used to better understand and manage amphibian biodiversity within a single park or group of parks.
Multi-frequency steady-state visual evoked potential dataset
Authors: Mu Jing , Liu Shuo , Burkitt Anthony N. , Grayden David B. 
Published: January 2024

AbstractThe Steady-State Visual Evoked Potential (SSVEP) is a widely used modality in Brain-Computer Interfaces (BCIs). Existing research has demonstrated the capabilities of SSVEP that use single frequencies for each target in various applications with relatively small numbers of commands required in the BCI. Multi-frequency SSVEP has been developed to extend the capability of single-frequency SSVEP to tasks that involve large numbers of commands. However, the development on multi-frequency SSVEP methodologies is falling behind compared to the number of studies with single-frequency SSVEP. This dataset was constructed to promote research in multi-frequency SSVEP by making SSVEP signals collected with different frequency stimulation settings publicly available. In this dataset, SSVEPs were collected from 35 participants using single-, dual-, and tri-frequency stimulation and with three different multi-frequency stimulation variants.
Genome assembly and population genomic data of a pulmonate snail Ellobium chinense
Authors: Kwak Haena , Lee Damin , Kim Yukyung , Park Joohee , Yeum Heeseung , Kim Donghee , Dong Yun-Wei , Nakano Tomoyuki , Jeong Choongwon , Park Joong-Ki 
Published: January 2024

AbstractEllobium chinense is an airbreathing, pulmonate gastropod species that inhabits saltmarshes in estuaries of the northwestern Pacific. Due to a rapid population decline and their unique ecological niche in estuarine ecosystems, this species has attracted special attention regarding their conservation and the genomic basis of adaptation to frequently changing environments. Here we report a draft genome assembly of E. chinense with a total size of 949.470 Mb and a scaffold N50 of 1.465 Mb. Comparative genomic analysis revealed that the GO terms enriched among four gastropod species are related to signal transduction involved in maintaining electrochemical gradients across the cell membrane. Population genomic analysis using the MSMC model for 14 re-sequenced individuals revealed a drastic decline in Korean and Japanese populations during the last glacial period, while the southern Chinese population retained a much larger effective population size (Ne). These contrasting demographic changes might be attributed to multiple environmental factors during the glacial–interglacial cycles. This study provides valuable genomic resources for understanding adaptation and historical demographic responses to climate change.
Enrichment of lung cancer computed tomography collections with AI-derived annotations
Authors: Krishnaswamy Deepa , Bontempi Dennis , Thiriveedhi Vamsi Krishna , Punzo Davide , Clunie David , Bridge Christopher P. , Aerts Hugo J. W. L. , Kikinis Ron , Fedorov Andrey 
Published: January 2024

AbstractPublic imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve acceptable performance and can be used to automatically annotate large datasets. As part of the effort to enrich public data available within NCI Imaging Data Commons (IDC), here we introduce AI-generated annotations for two collections containing computed tomography images of the chest, NSCLC-Radiomics, and a subset of the National Lung Screening Trial. Using publicly available AI algorithms, we derived volumetric annotations of thoracic organs-at-risk, their corresponding radiomics features, and slice-level annotations of anatomical landmarks and regions. The resulting annotations are publicly available within IDC, where the DICOM format is used to harmonize the data and achieve FAIR (Findable, Accessible, Interoperable, Reusable) data principles. The annotations are accompanied by cloud-enabled notebooks demonstrating their use. This study reinforces the need for large, publicly accessible curated datasets and demonstrates how AI can aid in cancer imaging.
FISHGLOB_data: an integrated dataset of fish biodiversity sampled with scientific bottom-trawl surveys
Authors: Maureaud Aurore A. , Palacios-Abrantes Juliano , Kitchel Zoë , Mannocci Laura , Pinsky Malin L. , Fredston Alexa , Beukhof Esther , Forrest Daniel L. , Frelat Romain , Palomares Maria L. D. , Pecuchet Laurene , Thorson James T. , van Denderen P. Daniël , Mérigot Bastien 
Published: January 2024

AbstractScientific bottom-trawl surveys are ecological observation programs conducted along continental shelves and slopes of seas and oceans that sample marine communities associated with the seafloor. These surveys report taxa occurrence, abundance and/or weight in space and time, and contribute to fisheries management as well as population and biodiversity research. Bottom-trawl surveys are conducted all over the world and represent a unique opportunity to understand ocean biogeography, macroecology, and global change. However, combining these data together for cross-ecosystem analyses remains challenging. Here, we present an integrated dataset of 29 publicly available bottom-trawl surveys conducted in national waters of 18 countries that are standardized and pre-processed, covering a total of 2,170 sampled fish taxa and 216,548 hauls collected from 1963 to 2021. We describe the processing steps to create the dataset, flags, and standardization methods that we developed to assist users in conducting spatio-temporal analyses with stable regional survey footprints. The aim of this dataset is to support research, marine conservation, and management in the context of global change.
A multilayered urban tree dataset of point clouds, quantitative structure and graph models
Authors: Yazdi Hadi , Shu Qiguan , Rötzer Thomas , Petzold Frank , Ludwig Ferdinand 
Published: January 2024

AbstractThe significance of urban trees in promoting human health and well-being has been amplified by urbanization and the climate change effects. Simultaneously, advancements in remote sensing techniques have enhanced the opportunities for studying urban trees. The TreeML-Data has been compiled to support these efforts. It consists of labelled point clouds of 40 scanning projects of streets in Munich, 3,755 leaf-off (scans in winter) point clouds of individual trees, quantitative structure models (QSM), tree structure measurements, and tree graph structure models of these trees. The dataset offers valuable data for generating and evaluating models in various scientific disciplines, which include remote sensing, computer vision, machine learning, urban forestry, urban ecosystem, green architecture, and graph analysis. To ensure its quality, the tree structure measurements and QSM have been crosschecked. For instance, the tree diameter at breast height (DBH) in the sample dataset exhibits a deviation of approximately 1.5 cm (4.3%) when compared to manual measurements. In conclusion, the quality checks confirm its reliability for subsequent studies when compared to manual measurements.
Peristaltic transport of Sutterby nanofluid flow in an inclined tapered channel with an artificial neural network model and biomedical engineering application
Authors: Chinnasamy P. , Sivajothi R. , Sathish S. , Abbas Mohamed , Jeyakrishnan V. , Goel Rajat , Alqahtani Mohammed S. , Loganathan K. 
Published: January 2024

AbstractModern energy systems are finding new applications for magnetohydrodynamic rheological bio-inspired pumping systems. The incorporation of the electrically conductive qualities of flowing liquids into the biological geometries, rheological behavior, and propulsion processes of these systems was a significant effort. Additional enhancements to transport properties are possible with the use of nanofluids. Due to their several applications in physiology and industry, including urine dynamics, chyme migration in the gastrointestinal system, and the hemodynamics of tiny blood arteries. Peristaltic processes also move spermatozoa in the human reproductive system and embryos in the uterus. The present research examines heat transport in a two-dimensional deformable channel containing magnetic viscoelastic nanofluids by considering all of these factors concurrently, which is vulnerable to peristaltic waves and hall current under ion slip and other situations. Nanofluid rheology makes use of the Sutterby fluid model, while nanoscale effects are modeled using the Buongiorno model. The current study introduces an innovative numerical computing solver utilizing a Multilayer Perceptron feed-forward back-propagation artificial neural network (ANN) with the Levenberg–Marquardt algorithm. Data were collected for testing, certifying, and training the ANN model. In order to make the dimensional PDEs dimensionless, the non-similar variables are employed and calculated by the Homotopy perturbation technique. The effects of developing parameters such as Sutterby fluid parameter, Froude number, thermophoresis, ion-slip parameter, Brownian motion, radiation, Eckert number, and Hall parameter on velocity, temperature, and concentration are demonstrated. The machine learning model chooses data, builds and trains a network, and subsequently assesses its performance using the mean square error metric. Current results declare that the improving Reynolds number tends to increase the pressure rise. Improving the Hall parameter is shown to result in a decrease in velocity. When raising a fluid's parameter, the temperature profile rises.