bluuebunny/crossref_metadata_2025_split huggingface dataset:
WCRC-25: A novel luminal Invasive Lobular Carcinoma cell line model
Authors: Elangovan Ashuvinee , Bossart Emily A. , Basudan Ahmed , Tasdemir Nilgun , Shah Osama Shiraz , Ding Kai , Meier Carolin , Heim Tanya , Neumann Carola , Attaran Shireen , Brown Lauren , Hooda Jagmohan , Miller Lori , Liu Tiantong , Puhalla Shannon L. , Gurda Grzegorz , Lucas Peter C. , McAuliffe Priscilla F. , Atkinson Jennifer M. , Lee Adrian V. , Oesterreich Steffi 
Published: September 2023

AbstractBreast cancer is categorized by the molecular and histologic presentation of the tumor, with the major histologic subtypes being No Special Type (NST) and Invasive Lobular Carcinoma (ILC). ILC are characterized by growth in a single file discohesive manner with stromal infiltration attributed to their hallmark pathognomonic loss of E-cadherin (CDH1). Few ILC cell line models are available to researchers. Here we report the successful establishment and characterization of a novel ILC cell line, WCRC-25, from a metastatic pleural effusion from a postmenopausal Caucasian woman with metastatic ILC. WCRC-25 is an ER-negative luminal epithelial ILC cell line with both luminal and Her2-like features. It exhibits anchorage independent growth and haptotactic migration towards Collagen I. Sequencing revealed aCDH1Q706* truncating mutation, together with mutations inFOXA1, CTCF, BRCA2andTP53, which were also seen in a series of metastatic lesions from the patient. Copy number analyses revealed amplification and deletion of genes frequently altered in ILC while optical genome mapping revealed novel structural rearrangements. RNA-seq analysis comparing the primary tumor, metastases and the cell line revealed signatures for cell cycle progression and receptor tyrosine kinase signaling. To assess targetability, we treated WCRC-25 with AZD5363 and Alpelisib confirming WCRC-25 as susceptible to PI3K/AKT signaling inhibition as predicted by our RNA sequencing analysis. In conclusion, we report WCRC-25 as a novel ILC cell line with promise as a valuable research tool to advance our understanding of ILC and its therapeutic vulnerabilities.Financial supportThe work was in part supported by a Susan G Komen Leadership Grant to SO (SAC160073) and NCI R01 CA252378 (SO/AVL). AVL and SO are Komen Scholars, Hillman Foundation Fellows and supported by BCRF. This project used the UPMC Hillman Cancer Center and Tissue and Research Pathology/Pitt Biospecimen Core shared resource which is supported in part by award P30CA047904. This research was also supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. Finally, partial support was provided by the Magee-Womens Research Institute and Foundation, The Shear Family Foundation, and The Metastatic Breast Cancer Network.
Tap Dancing Frogs: Posterior Toe Tapping and Feeding inDendrobates tinctorius
Authors: Parrish Thomas Q , Fischer Eva K 
Published: September 2023

AbstractAnimals have myriad adaptations to help them hunt and feed in the most efficient and effective manner. One mysterious behavior related to hunting and feeding is the posterior toe tapping behavior of some frogs. Biologists and hobbyists alike have long noticed this behavior, but there is little empirical data to explain its causes and consequences. To test the hypothesis that tapping is related to feeding and modulated by environmental context, we conducted a series of related experiments in the Dyeing poison frog,Dendrobates tinctorius. We first confirmed that tap rate was higher during feeding as has been observed in other species. Interestingly, this effect was heightened in the presence of a conspecific. We next asked whether frogs tapped less under conditions when prey were visible, but inaccessible. Finally, we asked whetherD. tinctoriusadjusted tap rate based on substrate characteristics and whether prey capture success was higher when tapping. In addition to confirming an association between tapping and feeding, our work demonstrates modulation of toe tapping based on social context, prey accessibility, and substrate characteristics. Based on our findings, we suggest that tapping could act to induce prey movement and thereby facilitate prey detection and capture by frogs.Significance StatementThe toe tapping of some amphibians is an intriguing behavior that has attracted attention from researchers and hobbyists, yet the functional role of toe tapping remains poorly understood. Previous studies have noted an association between toe tapping and feeding in other species, and our work does so quantitatively and experimentally in Dyeing poison frogs,Dendrobates tinctorius. We demonstrate that frogs modulate tap rate based on the presence of conspecifics, prey accessibility, and substrate type. We speculate that – alongside other potential functions – toe tapping may act as a vibrational stimulus to facilitate prey detection and capture.
Structural insights into the orthosteric inhibition of P2X receptors by non-ATP-analog antagonists
Authors: Sheng Danqi , Yue Chenxi , Jin Fei , Wang Yao , Ichikawa Muneyoshi , Yu Ye , Guo Chang-Run , Hattori Motoyuki 
Published: September 2023

AbstractP2X receptors are extracellular ATP-gated ion channels that form homo-or heterotrimers and consist of seven subtypes. They are expressed in various tissues, including neuronal and nonneuronal cells, and play critical roles in physiological processes such as neurotransmission, inflammation, pain, and cancer. As a result, P2X receptors have attracted considerable interest as drug targets, and various competitive inhibitors have been developed. However, although several P2X receptor structures from different subtypes have been reported, the limited structural information of P2X receptors in complex with competitive antagonists hampers the understanding of orthosteric inhibition, hindering the further design and optimization of those antagonists for drug discovery.Here, we determined the cryo-EM structures of the mammalian P2X7 receptor in complex with two classical competitive antagonists of pyridoxal-5’-phosphate derivatives, PPNDS and PPADS, at 3.3 and 3.6 Å resolution, respectively, and performed structure-based mutational analysis by patch-clamp recording as well as MD simulations. Our structures revealed the orthosteric site for PPADS/PPNDS, and structural comparison with the previously reported apo-and ATP-bound structures showed how PPADS/PPNDS binding inhibits the conformational changes associated with channel activation. In addition, structure-based mutational analysis identified key residues involved in the PPNDS sensitivity of P2X1 and P2X3, which are known to have higher affinity for PPADS/PPNDS than other P2X subtypes. Overall, our work provides structural insights into the orthosteric inhibition and subtype specificity of P2X receptors by the classical P2X antagonists, pyridoxal-5’-phosphate derivatives, thereby facilitating the rational design of novel competitive antagonists for P2X receptors.
Unsupervised Alignment in Neuroscience: Introducing a Toolbox for Gromov-Wasserstein Optimal Transport
Authors: Sasaki Masaru , Takeda Ken , Abe Kota , Oizumi Masafumi 
Published: September 2023

AbstractBackgroundUnderstanding how sensory stimuli are represented across different brains, species, and artificial neural networks is a critical topic in neuroscience. Traditional methods for comparing these representations typically rely on supervised alignment, which assumes direct correspondence between stimuli representations across brains or models. However, it has limitations when this assumption is not valid, or when validating the assumption itself is the goal of the research.New methodTo address the limitations of supervised alignment, we propose an unsupervised alignment method based on Gromov-Wasserstein optimal transport (GWOT). GWOT optimally identifies correspondences between representations by leveraging internal relationships without external labels, revealing intricate structural correspondences such as one-to-one, group-to-group, and shifted mappings.ResultsWe provide a comprehensive methodological guide and introduce a toolbox called GWTune for using GWOT in neuroscience. Our results show that GWOT can reveal detailed structural distinctions that supervised methods may overlook. We also demonstrate successful unsupervised alignment in key data domains, including behavioral data, neural activity recordings, and artificial neural network models, demonstrating its flexibility and broad applicability.Comparison with existing methodsUnlike traditional supervised alignment methods such as Representational Similarity Analysis, which assume direct correspondence between stimuli, GWOT provides a nuanced approach that can handle different types of structural correspondence, including fine-grained and coarse correspondences. Our method would provide richer insights into the similarity or difference of representations by revealing finer structural differences.ConclusionWe anticipate that our work will significantly broaden the accessibility and application of unsupervised alignment in neuroscience, offering novel perspectives on complex representational structures. By providing a user-friendly toolbox and a detailed tutorial, we aim to facilitate the adoption of unsupervised alignment techniques, enabling researchers to achieve a deeper understanding of cross-brain and cross-species representation analysis.
Insights into Biomarker Correlations in Relation to Stress: A Preliminary Analysis
Authors: Lundström Annika , Mandalios Caterina 
Published: September 2023

AbstractThe objective of this study was to analyze specific biomarkers of interest and find correlations between them using hormonal and cardiovascular measurements. The aim was to explore these physiological patterns during a typical weekday. While this research provides valuable insights into physiological patterns and their potential impact on mental performance, it’s essential to note that the study did not aim to diagnose, treat, or propose specific medical interventions based on the findings. Instead, the focus was solely on observational data collection and analysis for the purpose of exploring correlations and understanding daily physiological fluctuations in the context of stress and cognitive performance. Furthermore, the team observed how a low-level stress-triggered cognitive task could alter, and possibly impair, mental performance due to fluctuations in these selected data points. Five (5) adult, healthy participants (aged between 20 and 35 years) volunteered for the small-scaled study (two male and three female).In the current study, participants with larger hormonal and cardiovascular fluctuations during a 5-minute stress-induced task did not achieve as well as those with more stable physiological measurements. Interestingly, a significant peak in cortisol levels was detected during the mental task, likely due to the stress-induced environment.The current, and vastly limited methods used for at-home, hormonal measurements, as well as the slightly unreliable sensor technology used in general pulse oximeters measuring blood oxygen saturation in this trial, indicate the great need to develop new solutions. This includes innovations that would make health monitoring more convenient, while at the same time emphasizing improved mental well-being in daily situations, all without having to continuously wear a gadget to obtain precise insights about multiple health metrics.
A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis
Authors: Chen Xupeng , Wang Ran , Khalilian-Gourtani Amirhossein , Yu Leyao , Dugan Patricia , Friedman Daniel , Doyle Werner , Devinsky Orrin , Wang Yao , Flinker Adeen 
Published: September 2023

AbstractDecoding human speech from neural signals is essential for brain-computer interface (BCI) technologies restoring speech function in populations with neurological deficits. However, it remains a highly challenging task, compounded by the scarce availability of neural signals with corresponding speech, data complexity, and high dimensionality, and the limited publicly available source code. Here, we present a novel deep learning-based neural speech decoding framework that includes an ECoG Decoder that translates electrocorticographic (ECoG) signals from the cortex into interpretable speech parameters and a novel differentiable Speech Synthesizer that maps speech parameters to spectrograms. We develop a companion audio-to-audio auto-encoder consisting of a Speech Encoder and the same Speech Synthesizer to generate reference speech parameters to facilitate the ECoG Decoder training. This framework generates natural-sounding speech and is highly reproducible across a cohort of 48 participants. Among three neural network architectures for the ECoG Decoder, the 3D ResNet model has the best decoding performance (PCC=0.804) in predicting the original speech spectrogram, closely followed by the SWIN model (PCC=0.796). Our experimental results show that our models can decode speech with high correlation even when limited to only causal operations, which is necessary for adoption by real-time neural prostheses. We successfully decode speech in participants with either left or right hemisphere coverage, which could lead to speech prostheses in patients with speech deficits resulting from left hemisphere damage. Further, we use an occlusion analysis to identify cortical regions contributing to speech decoding across our models. Finally, we provide open-source code for our two-stage training pipeline along with associated preprocessing and visualization tools to enable reproducible research and drive research across the speech science and prostheses communities.
Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids using low-coherence holotomography
Authors: Lee Mahn Jae , Lee Jaehyeok , Ha Jeongmin , Kim Geon , Kim Hye-Jin , Lee Sumin , Koo Bon-Kyoung , Park YongKeun 
Published: September 2023

AbstractThe prevailing challenges in live unlabeled high-resolution imaging of native organoids stem from technical issues like complex sample handling and optical scattering in three-dimensional architectures. In this study, we introduce low-coherence holotomography as an advanced, label-free, quantitative imaging modality, designed to overcome related technical obstacles for long-term live imaging of 3D organoids. We successfully captured high-resolution morphological intricacies and dynamic events within mouse small intestinal organoids at a subcellular resolution. Furthermore, this method provides a unique advantage in differentiating between viable and non-viable organoids, thereby expanding its potential applications in organoid-based research.
U6 snRNA m6A modification is required for accurate and efficient cis- and trans-splicing ofC. elegansmRNAs
Authors: Shen Aykut , Hencel Katarzyna , Parker Matthew T. , Scott Robyn , Skukan Roberta , Adesina Aduragbemi S. , Metheringham Carey L. , Miska Eric A. , Nam Yunsun , Haerty Wilfried , Simpson Gordon G. , Akay Alper 
Published: September 2023

Abstractpre-mRNA splicing is a critical feature of eukaryotic gene expression. Many eukaryotes use cis-splicing to remove intronic sequences from pre-mRNAs. In addition to cis-splicing, many organisms use trans-splicing to replace the 5′ ends of mRNAs with a non-coding spliced-leader RNA. Both cis- and trans-splicing rely on accurately recognising splice site sequences by spliceosomal U snRNAs and associated proteins. Spliceosomal snRNAs carry multiple RNA modifications with the potential to affect different stages of pre-mRNA splicing. Here, we show that m6A modification of U6 snRNA A43 by the RNA methyltransferase METT-10 is required for accurate and efficient cis- and trans-splicing ofC. eleganspre-mRNAs. The absence of U6 snRNA m6A modification primarily leads to alternative splicing at 5′ splice sites. Furthermore, weaker 5′ splice site recognition by the unmodified U6 snRNA A43 affects splicing at 3′ splice sites. U6 snRNA m6A43 and the splicing factor SNRNP27K function to recognise an overlapping set of 5′ splice sites with an adenosine at +4 position. Finally, we show that U6 snRNA m6A43 is required for efficient SL trans-splicing at weak 3′ trans-splice sites. We conclude that the U6 snRNA m6A modification is important for accurate and efficient cis- and trans-splicing inC. elegans.
MERRA-based trend analysis identifies complex, multidecadal patterns of changing climatic suitability for Cassin’s Sparrow (Peucaea cassinii)
Authors: Schnase John L. , Carroll Mark L. , Montesano Paul M. , Seamster Virginia A. 
Published: September 2023

AbstractCassin’s Sparrow (Peucaea cassinii) is a grassland resident of the American Southwest. Despite decades of study, there remains uncertainty regarding the conservation status of the species. The species’ past response to a changing climate may help explain this uncertainty, especially if patterns vary across the species’ range. In this study, we combine data from NASA’s Modern-Era Reanalysis for Research and Applications, Version 2 (MERRA-2; M2) with field observations spanning the past 40 years to examine historical changes in climatic suitability for Cassin’s Sparrow across its full annual range within the continental United States. We examine two time- and variable-specific time series using MaxEnt. The M2 times series uses a mix of 30 microclimatic variables and ecosystem functional attributes related to energy and water fluxes for predictors; the MERRAclim (MC) time series uses 19 MERRA-2-derived bioclimatic variables for predictors. Trend analysis reveals complex patterns of slowly increasing climatic suitability over 69.5% of the study area in the MC time series accompanied by decreases over 24.4% of the area. Shifts in the study area-wide, weighted centroid for climatic suitability show a northwesterly, 40-year displacement of 1.85 km/yr. The M2 time series points to a less favorable history with increasing and decreasing trends over 54.9% and 40.1% of the study area, respectively, and a westerly weighted centroid shift of 2.60 km/yr. A clear subset of seven M2 and MC variables emerged as the most important determinants of suitability over the past 40 years. These variables also demonstrated complex patterns of non-constant trends across the study area. Suitability trends in both time series appear to have little in common with current, state-level, abundance-derived conservation status assessments. Increasing winds, drying land surface conditions, and variability in North American Monsoon rainfall appear to be dominating, climate-related influences on the species. We thus see complex patterns of historical change in climatic suitability depending on whether time series models are driven by bioclimatic variables alone or by variables more aligned with ecological function. This leads us to conclude that modeled estimates of climatic suitability for Cassin’s Sparrow can vary widely depending on the temporal frame, spatial extent, and environmental drivers considered, and that this variability mirrors the uncertainty in the literature regarding the species’ conservation status. Furthermore, these factors should be taken into account in future conservation assessments for the species, and retrospective ecological niche modeling, as applied here, offers a promising approach to addressing these issues.
Biological motion perception in the theoretical framework of perceptual decision-making: An event-related potential study
Authors: Oğuz Osman Çağrı , Aydın Berfin , Urgen Burcu A. 
Published: September 2023

ABSTRACTBiological motion perception plays a critical role in various decisions in daily life for humans. Failure to decide accordingly in such a perceptual task could have life-threatening consequences. Neurophysiological studies on non-human primates and computational modeling studies suggest two processes that mediate perceptual decision-making. One of these signals is associated with the accumulation of sensory evidence and the other with response selection. Recent EEG studies with human participants have introduced an event-related potential called Centroparietal Positive Potential (CPP) as a neural marker aligned with the sensory evidence accumulation while effectively distinguishing it from motor-related event-related potential, namely lateralized readiness potential (LRP). The present study aims to investigate the neural mechanisms of biological motion perception in the theoretical framework of perceptual decision-making, which has been overlooked before. More specifically, we examine whether CPP would track the coherence of the biological motion stimuli and could be distinguished from the LRP signal. We recorded EEG from human participants while they were engaged in a direction discrimination task of a point-light walker whose coherence was manipulated by embedding it in various levels of noise. Our behavioral findings revealed shorter reaction times and reduced miss rates as the coherence of the target stimuli increased. In addition, CPP tracked the coherence of the biological motion stimuli with a tendency to reach a common level during the response, albeit with a later onset than the previously reported results in random-dot motion paradigms. Furthermore, CPP was distinguished from the LRP signal based on its temporal profile. Overall, our results suggest that the mechanisms underlying perceptual decision-making generalize to more complex and socially significant stimuli like biological motion. We discuss the implications of these findings for advancing computational models of biological motion perception and perceptual decision-making.
Regularized partial correlation provides reliable functional connectivity estimates while correcting for widespread confounding
Authors: Peterson Kirsten L. , Sanchez-Romero Ruben , Mill Ravi D. , Cole Michael W. 
Published: September 2023

AbstractFunctional connectivity (FC) has been invaluable for understanding the brain’s communication network, with strong potential for enhanced FC approaches to yield additional insights. Unlike with the fMRI field-standard method of pairwise correlation, theory suggests that partial correlation can estimate FC without confounded and indirect connections. However, partial correlation FC can also display low repeat reliability, impairing the accuracy of individual estimates. We hypothesized that reliability would be increased by adding regularization, which can reduce overfitting to noise in regression-based approaches like partial correlation. We therefore tested several regularized alternatives – graphical lasso, graphical ridge, and principal component regression – against unregularized partial and pairwise correlation, applying them to empirical resting-state fMRI and simulated data. As hypothesized, regularization vastly improved reliability, quantified using between-session similarity and intraclass correlation. This enhanced reliability then granted substantially more accurate individual FC estimates when validated against structural connectivity (empirical data) and ground truth networks (simulations). Graphical lasso showed especially high accuracy among regularized approaches, seemingly by maintaining more valid underlying network structures. We additionally found graphical lasso to be robust to noise levels, data quantity, and subject motion – common fMRI error sources. Lastly, we demonstrated that resting-state graphical lasso FC can effectively predict fMRI task activations and individual differences in behavior, further establishing its reliability, external validity, and ability to characterize task-related functionality. We recommend graphical lasso or similar regularized methods for calculating FC, as they can yield more valid estimates of unconfounded connectivity than field-standard pairwise correlation, while overcoming the poor reliability of unregularized partial correlation.