bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kv7 Channel Opener Retigabine Reduces Self-Administration of Cocaine but Not Sucrose in Rats
Authors: Urena Esteban S. , Diezel Cody C. , Serna Mauricio , Hala’ufia Grace , Majuta Lisa , Barber Kara R. , Vanderah Todd W. , Riegel Arthur C. 
Published: May 2023

ABSTRACTThe increasing rates of drug misuse highlight the urgency of identifying improved therapeutics for treatment. Most drug-seeking behaviors that can be modeled in rodents utilize the repeated intravenous self-administration (SA) of drugs. Recent studies examining the mesolimbic pathway suggest that Kv7/KCNQ channels may contribute in the transition from recreational to chronic drug use. However, to date, all such studies used noncontingent, experimenter-delivered drug model systems, and the extent to which this effect generalizes to rats trained to self-administer drug is not known. Here, we tested the ability of retigabine (ezogabine), a Kv7 channel opener, to regulate instrumental behavior in male Sprague Dawley rats. We first validated the ability of retigabine to target experimenter-delivered cocaine in a CPP assay and found that retigabine reduced the acquisition of place preference. Next, we trained rats for cocaine-SA under a fixed-ratio or progressive-ratio reinforcement schedule and found that retigabine-pretreatment attenuated the self-administration of low to moderate doses of cocaine. This was not observed in parallel experiments, with rats self-administering sucrose, a natural reward. Compared to sucrose-SA, cocaine-SA was associated with reductions in the expression of the Kv7.5 subunit in the nucleus accumbens, without alterations in Kv7.2 and Kv7.3. Therefore, these studies reveal a reward specific reduction in SA behavior considered relevant for the study of long-term compulsive-like behavior and supports the notion that Kv7 is a potential therapeutic target for human psychiatric diseases with dysfunctional reward circuitry.
PlantC2U: Deep learning of cross-species sequence landscapes predicts plastid C-to-U RNA editing in plants
Authors: Xu Chaoqun , Li Jing , Song Ling-Yu , Guo Ze-Jun , Song Shi-Wei , Zhang Lu-Dan , Zheng Hai-Lei 
Published: May 2023

AbstractIn plants, C-to-U RNA editing is mainly occurred in the plastids and mitochondria transcripts, which contributes to complex transcriptional regulatory network. More evidences reveal that RNA editing plays critical roles in plant growth and development. However, RNA editing sites accurately detected by transcriptome sequencing data alone are still challenging. In the present study, we developed PlantC2U, which is a convolutional neural network to predict plastid C-to-U RNA editing based on the genomic sequence. PlantC2U achieves over 95% sensitivity and 99% specificity, which outperforms random forest and support vector machine. PlantC2U not only further checks RNA editing sites from transcriptome data to reduce the possible false positives, but also assesses the effect of different mutations on C-to-U RNA editing status based on the flanking sequences. Moreover, we found the patterns of tissue-specific RNA editing in mangrove plantKandelia obovata, and observed reduced C-to-U RNA editing rates in cold stress response ofK. obovata, suggesting their potential regulatory roles in the plants stress adaption. In addition, we present RNAeditDB, available online athttps://jasonxu.shinyapps.io/RNAeditDB/. Together, PlantC2U and RNAeditDB would help researchers explore the RNA editing events in plants and thus would be of broad utility for the plant research community.HighlightWe develop a convolutional neural network based deep learning, PlantC2U program, which help researchers explore the plastids C-to-U RNA editing events in plants and thus would be of broad utility for the plant research community.
A complete morphological characterization of all life stages of the phorid flyM. scalaris
Authors: Pallavi Jayakumar , Snehal Harshita , Salazar Daniela , Hanbar Mrunal , Chiramel Larina Bejoy , Jha Khushi Alok , Kolipakala Rakshita Sukruth , Lakshmi Venkatesh Sai Bhumica , Shetty Tanishka Dayanand , Madhusudan Navya , Mohan Amrutha , John Amulia , D’souza Naomi Deep , Sheet Priyanka , Nagarajan Deepesh 
Published: May 2023

ABSTRACTMegaselia scalaris, commonly known as the scuttle fly, is a cosmopolitan species in the family Phoridae. It is an easily cultured fly species that is an emerging model organism in the fields of genetics and developmental biology. Its affinity for carrion and its predictable life cycle makes it useful in the field of forensic science for estimating the post-mortem interval (PMI) of human remains. Cases of human myasis caused byM. scalarishave also been reported in the medical literature. Despite its ubiquitous prevalence and its relevance across multiple fields, its morphology has not been adequately characterized. Here, we report the complete morphological characterization of all lifestages ofM. scalaris, ranging from egg to adult. Scanning electron microscopy has enabled us to uncover morphological features and developmental processes that have previously not been reported in the literature. Our data lays the groundwork for future genetic studies: a morphological characterization of the wild type must be performed before mutants displaying different phenotypes can be identified. In this vein, we also report the observation of a acephalic, or ‘headless’, adult phenotype whose study could yield insights into the process of cephalogenesis.
GPX4-VIM equates a proliferating DTP state in TNBC subtypes with converged vulnerabilities to autophagy and glutathione inhibition
Authors: Chaudhary Nazia , Choudhary Bhagya Shree , Patra Sushmita , Malvankar Shivani , Shivashankar Anusha , Jog Eeshrita , Kailje Vaishali V. , Khanna Sonal , Manna Subhakankha , Sahoo Sarthak , R Soundharya , Jolly Mohit Kumar , Dalal Sorab N. , Verma Nandini 
Published: May 2023

ABSTRACTFrequent metastatic relapses in Triple-Negative Breast Cancer (TNBC) patients with residual disease is a clinical challenge, largely due to tumor heterogeneity and absence of strategies that target proliferating chemo-tolerant cells. Here, we longitudinally modeled cellular state transitions from dormant drug-tolerant persister (DTP) into proliferating drug-tolerant persister (PDTP) in cells representing all TNBC subtypes. Combining subcellular imaging with phenotypic and biochemical assays, we identified distinct and converged spectrums of alterations in TNBC-PDTPs. We show that PDTPs retain acquired resistance with increased invasion potential. Moreover, Basal-Like DTPs enter into a non-reversible mesenchymal state while luminal androgen receptor-positive gain partial-Epithelial-to-Mesenchymal Transition (EMT) with vimentin upregulation. PDTP state dwells on high autophagy with reduced glutathione and GPX4 levels, rendering it vulnerable to autophagy suppression and ferroptosis. Interestingly, we find that GPX4 negatively regulates EMT and autophagy in TNBC, and an inverse correlation of GPX4-VIM expression along with autophagy genes predicts survival in TNBC patients undergoing chemotherapy.
Multiple p38/JNK Mitogen-activated protein kinase (MAPK) signaling pathways mediate salt chemotaxis learning inC. elegans
Authors: Huang Taoruo , Suzuki Kota , Kunitomo Hirofumi , Tomioka Masahiro , Iino Yuichi 
Published: May 2023

AbstractAnimals are able to adapt their behaviors to their environment. In order to achieve this, the nervous system plays integrative roles, such as perception of external signals, sensory processing, and behavioral regulations via various signal transduction pathways. Here genetic analyses ofC. elegansfound that mutants of components of JNK and p38 Mitogen-activated protein kinase (MAPK) signaling pathways, also known as stress-activated protein kinase (SAPK) signaling pathways, exhibit various types of defects in the learning of salt chemotaxis.C. eleganshomologues of JNK MAPKKK and MAPKK, MLK-1 and MEK-1, respectively, are required to avoid salt concentrations experienced during starvation. In contrast, homologues of p38 MAPKKK and MAPKK, NSY-1 and SEK-1, respectively, are required for high-salt chemotaxis after conditioning. Genetic interaction analyses suggest that a JNK family MAPK, KGB-1, functions downstream of both signaling pathways to regulate salt chemotaxis learning. Furthermore, we found that the NSY-1/SEK-1 pathway functions in sensory neurons, ASH, ADF, and ASER, to regulate the learned high-salt chemotaxis. A neuropeptide, NLP-3, expressed in ASH, ADF, and ASER neurons, and a neuropeptide receptor, NPR-15, expressed in AIA interneurons that receive synaptic input from these sensory neurons, function in the same genetic pathway as NSY-1 / SEK-1 signaling. These findings suggest that this MAPK pathway may affect neuropeptide signaling between sensory neurons and interneurons, thus promoting high-salt chemotaxis after conditioning.
Multiscale imaging of corneal endothelium damage and effects of Rho Kinase inhibitor application in mouse models of acute ocular hypertension
Authors: Cai Zhen , Zhang Yang , Fang Raymond S. , Brenner Benjamin , Kweon Junghun , Sun Cheng , Goldberg Jeffery , Zhang Hao F. 
Published: May 2023

AbstractWe developed a multiscale optical imaging workflow, integrating and correlating visible-light optical coherence tomography, confocal laser scanning microscopy, and single-molecule localization microscopy to investigate the mouse cornea damages from thein-vivotissue level to the nanoscopic single-molecule level. We used electron microscopy to validate the imaged nanoscopic structures. We imaged wild-type mice and mice with acute ocular hypertension and examined the effects of Rho Kinase inhibitor application. We defined four types of intercellular tight junction structures as healthy, compact, partially-distorted, and fully-distorted types by labeling the Zonula occludens-1 protein in the corneal endothelial cell layer. We correlated the statistics of the four types of tight junction structures with cornea thickness and intraocular pressure. We found that the population of fully-distorted tight junctions correlated well with the level of cornea edema, and applying Rho Kinase inhibitor reduced the population of fully-distorted tight junctions under acute ocular hypertension.
Foveated metamers of the early visual system
Authors: Broderick William F. , Rufo Gizem , Winawer Jonathan , Simoncelli Eero P. 
Published: May 2023

AbstractHuman ability to discriminate and identify visual attributes varies across the visual field, and is generally worse in the periphery than in the fovea. This decline in performance is revealed in many kinds of tasks, from detection to recognition. A parsimonious hypothesis is that the representation of any visual feature is blurred (spatially averaged) by an amount that differs for each feature, but that in all cases increases with eccentricity. Here, we examine models for two such features: local luminance and spectral energy. Each model averages the corresponding feature in pooling windows whose diameters scale linearly with eccentricity. We performed psychophysical experiments with synthetic stimuli to determine the window scaling for which human and model discrimination abilities match, called the critical scaling. We used much larger stimuli than those of previous studies, subtending 53.6 by 42.2 degrees of visual angle. We found the critical scaling for the luminance model was approximately one-fourth that of the energy model, and consistent with earlier studies, that a smaller critical scaling value was required when discriminating a synthesized image from a natural image than when discriminating two synthesized images. We offer a coherent explanation for these results in terms of alignments and misalignments of the models with human perceptual representations.
Adaptive therapy in cancer: the role of restrictions in the accumulation of mutations
Authors: Fontaneda David , Diaz-Uriarte Ramon 
Published: May 2023

AbstractBACKGROUNDCancer is currently one of the leading causes of premature death in the world, and is predicted to continue rising even despite the continuous discovery of novel treatments. New approaches, like adaptive therapy, try to minimize the problem of drug resistance, but there are still many open questions and unstudied phenomena that need to be tackled in order to make this approaches viable in real patients; among these, the possible effects that restrictions in the order of accumulation of mutations could have.RESULTSWe have developed a spatially explicit agent-based model capable of simulating tumor growth and adaptive therapy in a highly flexible way. We show that when we consider restrictions in the order of accumulation of mutations and their effect in tumor architecture, the predicted genotypes of the cells that are inhibiting the growth of resistant cells can be very different to the ones predicted by perfectly mixed models.CONCLUSIONWe identify a divergence between the expected and real genotypes of the cells inhibiting the growth of the resistant population that has not been previously documented. This effect, if not taken into account, could negatively affect our predictions of adaptive therapy success and could hinder our advances in the development of new approaches to improve adaptive therapy. This discovery suggests the need for more studies that take into account the spatial component of cancer, specially when dealing with tumors with high heterogeneity. Furthermore, our model is able to simulate scenarios of tumor development and adaptive therapy, making it useful both for research and for education.
Single cell transcriptomics reveals cell type specific features of developmentally regulated responses to lipopolysaccharide between birth and 5 years
Authors: Read James F. , Serralha Michael , Armitage Jesse , Iqbal Muhammad Munir , Cruickshank Mark N. , Saxena Alka , Strickland Deborah H. , Waithman Jason , Holt Patrick G. , Bosco Anthony 
Published: May 2023

AbstractHuman perinatal life is characterized by a period of extraordinary change during which newborns encounter abundant environmental stimuli and exposure to potential pathogens. To meet such challenges, the neonatal immune system is equipped with unique functional characteristics that adapt to changing conditions as development progresses across the early years of life, but the molecular characteristics of such adaptations remain poorly understood. The application of single cell genomics to birth cohorts provides an opportunity to investigate changes in gene expression programs elicited downstream of innate immune activation across early life at unprecedented resolution. In this study, we performed single cell RNA-sequencing of mononuclear cells collected from matched birth cord blood and 5-year peripheral blood samples following stimulation (18hrs) with two well-characterized innate stimuli; lipopolysaccharide (LPS) and Polyinosinic:polycytidylic acid (Poly(I:C)). We found that the transcriptional response to LPS was constrained at birth and predominantly partitioned into classical proinflammatory gene upregulation primarily by monocytes and IFN-signaling gene upregulation by lymphocytes. Moreover, these responses featured substantial cell-to-cell communication which appeared markedly strengthened between birth and 5 years. In contrast, stimulation with Poly(I:C) induced a robust IFN-signalling response across all cell types identified at birth and 5 years. Analysis of gene regulatory networks revealed IRF1 and STAT1 were key drivers of the LPS-induced IFN-signaling response in lymphocytes with a potential developmental role for IRF7 regulation. Additionally, we observed distinct activation trajectory endpoints for monocytes derived from LPS-treated cord and 5-year blood, which was not apparent among Poly(I:C)-induced monocytes. Taken together, our findings provide new insight into the gene regulatory landscape of immune cell function between birth and 5 years and point to regulatory mechanisms relevant to future investigation of infection susceptibility in early life.
Physically informed Monte Carlo simulation of dual-wedge prism-based spectroscopic single-molecule localization microscopy
Authors: Yeo Wei-Hong , Sun Cheng , Zhang Hao F. 
Published: May 2023

AbstractSignificanceThe dual-wedge prism (DWP)-based spectroscopic single-molecule localization microscopy (sSMLM) system offers improved localization precision and adjustable spectral or localization performance, but its nonlinear spectral dispersion presents a challenge. A systematic method can help understand the challenges and thereafter optimize the DWP system’s performance by customizing system parameters to maximize spectral or localization performance for various molecular labels.AimWe developed an MC-based model which predicts the imaging output of the DWP-based sSMLM system given different system parameters.ApproachWe assessed our MC model’s localization and spectral precisions by comparing our simulation against theoretical equations and fluorescent microspheres. Furthermore, we simulated the DWP-based system using beamsplitters of Reflectance (R):Transmittance (T) of R50:T50 and R30:T70 and their tradeoffs.ResultsOur MC simulation showed average deviations of 2.5 nm and 2.1 nm for localization and spectral precisions against theoretical equations; and 2.3 nm and 1.0 nm against fluorescent microspheres. An R30:T70 beamsplitter improved spectral precision by 8% but worsened localization precision by 35% on average compared to an R50:T50 beamsplitter.ConclusionsThe MC model accurately predicted localization precision, spectral precision, spectral peaks, and spectral widths of fluorescent microspheres, as validated by experimental data. Our work enhances the theoretical understanding of DWP-based sSMLM for multiplexed imaging, enabling performance optimization.
Preliminary Development of a Robotic Hip-Knee Exoskeleton with 3D-Printed Backdrivable Actuators
Authors: Sanchez Alyssia , Rossos Trent , Mihailidis Alex , Laschowski Brokoslaw 
Published: May 2023

ABSTRACTRobotic exoskeletons can provide powered locomotor assistance and rehabilitation to persons with mobility impairments due to aging and/or physical disabilities. Here we present the preliminary development and systems integration of T-BLUE - a modular, bilateral robotic hip-knee exoskeleton with 3D-printed backdriveable actuators. We retrofitted commercially available passive postoperative orthoses with open-source 3D-printed actuators to minimize cost and improve accessibility. The actuators are of quasi-direct drive design with high-torque density brushless DC motors and low gearing (15:1 transmission ratio) for low output impedance and high backdrivability, therein allowing for energy-efficient and dynamic human-robot physical interaction and legged locomotion. The modular design allows the exoskeleton to be customized and adapted to different users (e.g., persons with lateral vs. bilateral mobility impairments) and different hip-knee joint configurations. The goals of this preliminary study were to describe our experience with regards to the repeatability of the open-source 3D-printed actuators in engineering practice and the feasibility of integrating the actuators into wearable robotics hardware. This qualitative research serves as a first step towards using the robotic exoskeleton to support the development and testing of novel controller designs and rehabilitation protocols for different locomotor activities of daily living. We are especially interested in populations that could benefit from partial locomotor assistance such as older adults and/or persons with osteoarthritis. Future research will involve benchtop testing to quantitatively evaluate the actuator performance in terms of dynamics and energy-efficiency.
Discovering Biomarker Proteins and Peptides for Parkinson’s Disease Prognosis Prediction with Machine Learning and Interpretability Methods
Authors: Park Ho-min , Kabanga Espoir , Moon Dongin , Chung Minjae , Im Jiwon , Kim Yujin , Van Messem Arnout , De Neve Wesley 
Published: May 2023

ABSTRACTParkinson’s disease is a neurodegenerative disorder that affects millions of people worldwide, posing significant challenges for diagnosis and treatment. This study presents a machine learning pipeline for identifying candidate biomarker proteins and peptides from cerebrospinal fluid mass spectrometry (CSF-MS) tests in Parkinson’s disease patients. Our pipeline comprises two main stages: (1) model training using mutual information-based feature selection and five different machine learning regressors and (2) identification of candidate biomarkers by combining three types of interpretability methods. Our regression models demonstrated promising effectiveness in predicting the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) scores, with UPDRS-1 receiving the best predictions, followed by UPDRS-3 and UPDRS-2. Furthermore, our pipeline identified 11 proteins and peptides as potential biomarkers for Parkinson’s disease, excluding Levodopa usage which trivially has the most significant impact on the prognosis prediction. Comparisons with four additional pipelines confirmed the effectiveness of our approach in terms of both model performance and biomarker identification. In conclusion, our study presents a comprehensive machine learning pipeline that demonstrates effectiveness in predicting the severity of Parkinson’s disease using CSF-MS tests. Our approach also identifies potential biomarkers, which could aid in the development of new diagnostic tools and treatments for patients with Parkinson’s disease.
scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data
Authors: Lin Yingxin , Wu Tung-Yu , Chen Xi , Wan Sheng , Chao Brian , Xin Jingxue , Yang Jean Y.H. , Wong Wing H. , Wang Y. X. Rachel 
Published: May 2023

AbstractSingle-cell technologies offer unprecedented opportunities to dissect gene regulatory mecha-nisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal datasets, we demonstrate scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome dataset we generated from differentiating mouse embryonic stem cells over time, we demonstrate scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.