bluuebunny/crossref_metadata_2025_split huggingface dataset:
Landscape genomics reveals adaptive genetic differentiation driven by multiple environmental variables in naked barley on the Qinghai-Tibetan Plateau
Authors: Chen Tongrui , Xu Jinqing , Wang Lei , Wang Handong , You En , Deng Chao , Bian Haiyan , Shen Yuhu 
Published: November 2023

AbstractUnderstanding the local adaptation of crops has long been a concern of evolutionary biologists and molecular ecologists. Identifying the adaptive genetic variability in the genome is crucial not only to provide insights into the genetic mechanism of local adaptation but also to explore the adaptation potential of crops. This study aimed to identify the climatic drivers of naked barley landraces and putative adaptive loci driving local adaptation on the Qinghai-Tibetan Plateau (QTP). To this end, a total of 157 diverse naked barley accessions were genotyped using the genotyping-by-sequencing approach, which yielded 3123 high-quality SNPs for population structure analysis and partial redundancy analysis, and 37,636 SNPs for outlier analysis. The population structure analysis indicated that naked barley landraces could be divided into four groups. We found that the genomic diversity of naked barley landraces could be partly traced back to the geographical and environmental diversity of the landscape. In total, 136 signatures associated with temperature, precipitation, and ultraviolet radiation were identified, of which 13 had pleiotropic effects. We mapped 447 genes, including a known gene HvSs1. Some genes involved in cold stress and regulation of flowering time were detected near eight signatures. Taken together, these results highlight the existence of putative adaptive loci in naked barley on QTP and thus improve our current understanding of the genetic basis of local adaptation.
Neural circuit selective for fast but not slow dopamine increases in drug reward
Authors: Manza Peter , Tomasi Dardo , Shokri-Kojori Ehsan , Zhang Rui , Kroll Danielle , Feldman Dana , McPherson Katherine , Biesecker Catherine , Dennis Evan , Johnson Allison , Yuan Kai , Wang Wen-Tung , Yonga Michele-Vera , Wang Gene-Jack , Volkow Nora D. 
Published: November 2023

AbstractThe faster a drug enters the brain, the greater its addictive potential, yet the brain circuits underlying the rate dependency to drug reward remain unresolved. With simultaneous PET-fMRI we linked dynamics of dopamine signaling, brain activity/connectivity, and self-reported ‘high’ in 20 adults receiving methylphenidate orally (results in slow delivery) and intravenously (results in fast delivery) (trial NCT03326245). We estimated speed of striatal dopamine increases to oral and IV methylphenidate and then tested where brain activity was associated with slow and fast dopamine dynamics (primary endpoint). We then tested whether these brain circuits were temporally associated with individual ‘high’ ratings to methylphenidate (secondary endpoint). A corticostriatal circuit comprising the dorsal anterior cingulate cortex and insula and their connections with dorsal caudate was activated by fast (but not slow) dopamine increases and paralleled ‘high’ ratings. These data provide evidence in humans for a link between dACC/insula activation and fast but not slow dopamine increases and document a critical role of the salience network in drug reward.
Single cell spatial analysis reveals inflammatory foci of immature neutrophil and CD8 T cells in COVID-19 lungs
Authors: Weeratunga Praveen , Denney Laura , Bull Joshua A. , Repapi Emmanouela , Sergeant Martin , Etherington Rachel , Vuppussetty Chaitanya , Turner Gareth D. H. , Clelland Colin , Woo Jeongmin , Cross Amy , Issa Fadi , de Andrea Carlos Eduardo , Melero Bermejo Ignacio , Sims David , McGowan Simon , Zurke Yasemin-Xiomara , Ahern David J. , Gamez Eddie C. , Whalley Justin , Richards Duncan , Klenerman Paul , Monaco Claudia , Udalova Irina A. , Dong Tao , Antanaviciute Agne , Ogg Graham , Knight Julian C. , Byrne Helen M. , Taylor Stephen , Ho Ling-Pei 
Published: November 2023

AbstractSingle cell spatial interrogation of the immune-structural interactions in COVID −19 lungs is challenging, mainly because of the marked cellular infiltrate and architecturally distorted microstructure. To address this, we develop a suite of mathematical tools to search for statistically significant co-locations amongst immune and structural cells identified using 37-plex imaging mass cytometry. This unbiased method reveals a cellular map interleaved with an inflammatory network of immature neutrophils, cytotoxic CD8 T cells, megakaryocytes and monocytes co-located with regenerating alveolar progenitors and endothelium. Of note, a highly active cluster of immature neutrophils and CD8 T cells, is found spatially linked with alveolar progenitor cells, and temporally with the diffuse alveolar damage stage. These findings offer further insights into how immune cells interact in the lungs of severe COVID-19 disease. We provide our pipeline [Spatial Omics Oxford Pipeline (SpOOx)] and visual-analytical tool, Multi-Dimensional Viewer (MDV) software, as a resource for spatial analysis.
High-speed mapping of surface charge dynamics using sparse scanning Kelvin probe force microscopy
Authors: Checa Marti , Fuhr Addis S. , Sun Changhyo , Vasudevan Rama , Ziatdinov Maxim , Ivanov Ilia , Yun Seok Joon , Xiao Kai , Sehirlioglu Alp , Kim Yunseok , Sharma Pankaj , Kelley Kyle P. , Domingo Neus , Jesse Stephen , Collins Liam 
Published: November 2023

AbstractUnraveling local dynamic charge processes is vital for progress in diverse fields, from microelectronics to energy storage. This relies on the ability to map charge carrier motion across multiple length- and timescales and understanding how these processes interact with the inherent material heterogeneities. Towards addressing this challenge, we introduce high-speed sparse scanning Kelvin probe force microscopy, which combines sparse scanning and image reconstruction. This approach is shown to enable sub-second imaging (>3 frames per second) of nanoscale charge dynamics, representing several orders of magnitude improvement over traditional Kelvin probe force microscopy imaging rates. Bridging this improved spatiotemporal resolution with macroscale device measurements, we successfully visualize electrochemically mediated diffusion of mobile surface ions on a LaAlO3/SrTiO3planar device. Such processes are known to impact band-alignment and charge-transfer dynamics at these heterointerfaces. Furthermore, we monitor the diffusion of oxygen vacancies at the single grain level in polycrystalline TiO2. Through temperature-dependent measurements, we identify a charge diffusion activation energy of 0.18 eV, in good agreement with previously reported values and confirmed by DFT calculations. Together, these findings highlight the effectiveness and versatility of our method in understanding ionic charge carrier motion in microelectronics or nanoscale material systems.
Cryo-EM structures of human magnesium channel MRS2 reveal gating and regulatory mechanisms
Authors: Lai Louis Tung Faat , Balaraman Jayashree , Zhou Fei , Matthies Doreen 
Published: November 2023

AbstractMagnesium ions (Mg2+) play an essential role in cellular physiology. In mitochondria, protein and ATP synthesis and various metabolic pathways are directly regulated by Mg2+. MRS2, a magnesium channel located in the inner mitochondrial membrane, mediates the influx of Mg2+ into the mitochondrial matrix and regulates Mg2+ homeostasis. Knockdown of MRS2 in human cells leads to reduced uptake of Mg2+ into mitochondria and disruption of the mitochondrial metabolism. Despite the importance of MRS2, the Mg2+ translocation and regulation mechanisms of MRS2 are still unclear. Here, using cryo-EM we report the structures of human MRS2 in the presence and absence of Mg2+ at 2.8 Å and 3.3 Å, respectively. From the homo-pentameric structures, we identify R332 and M336 as major gating residues, which are then tested using mutagenesis and two cellular divalent ion uptake assays. A network of hydrogen bonds is found connecting the gating residue R332 to the soluble domain, potentially regulating the gate. Two Mg2+-binding sites are identified in the MRS2 soluble domain, distinct from the two sites previously reported in CorA, a homolog of MRS2 in prokaryotes. Altogether, this study provides the molecular basis for understanding the Mg2+ translocation and regulatory mechanisms of MRS2.
Signature of quantum criticality in cuprates by charge density fluctuations
Authors: Arpaia Riccardo , Martinelli Leonardo , Sala Marco Moretti , Caprara Sergio , Nag Abhishek , Brookes Nicholas B. , Camisa Pietro , Li Qizhi , Gao Qiang , Zhou Xingjiang , Garcia-Fernandez Mirian , Zhou Ke-Jin , Schierle Enrico , Bauch Thilo , Peng Ying Ying , Di Castro Carlo , Grilli Marco , Lombardi Floriana , Braicovich Lucio , Ghiringhelli Giacomo 
Published: November 2023

AbstractThe universality of the strange metal phase in many quantum materials is often attributed to the presence of a quantum critical point (QCP), a zero-temperature phase transition ruled by quantum fluctuations. In cuprates, where superconductivity hinders direct QCP observation, indirect evidence comes from the identification of fluctuations compatible with the strange metal phase. Here we show that the recently discovered charge density fluctuations (CDF) possess the right properties to be associated to a quantum phase transition. Using resonant x-ray scattering, we studied the CDF in two families of cuprate superconductors across a wide doping range (up to p = 0.22). At p* ≈ 0.19, the putative QCP, the CDF intensity peaks, and the characteristic energy Δ is minimum, marking a wedge-shaped region in the phase diagram indicative of a quantum critical behavior, albeit with anomalies. These findings strengthen the role of charge order in explaining strange metal phenomenology and provide insights into high-temperature superconductivity.
Aryl hydrocarbon receptor regulates IL-22 receptor expression on thymic epithelial cell and accelerates thymus regeneration
Authors: Shen Jingyi , Wang Ying , Zheng Fei , Cao Shuo , Lan Qiu , Xu Kailin , Pan Bin 
Published: November 2023

AbstractImproving regeneration of damaged thymus is important for reconstituting T-cell immunity. Interleukin-22 (IL-22) was proved to improve thymus regeneration through recovering thymic epithelial cells (TECs). The IL-22 receptor IL-22RA1 is crucial for mediating IL-22 functions. Mechanism that regulates IL-22RA1 expression is unknown. Through using TECs-conditional knockout mice, we found aryl hydrocarbon receptor (AHR) is important for thymus regeneration, because Foxn1-cre-mediated AHR knockout (AhrKO) significantly blocks recovery of thymus cells. Giving mice the AHR inhibitor CH-223191 or the AHR agonist FICZ blocks or accelerates thymus regeneration, respectively. AhrKO-mediated blockade of thymus regeneration could not be rescued by giving exogenous IL-22. Mechanistically, AhrKO mice shows decreased IL-22RA1 expression. In the murine TECs cell line mTEC1 cells, targeting AHR shows an impact on IL-22RA1 mRNA levels. Using chromatin immunoprecipitation and luciferase reporter assays, we find AHR co-operates with STAT3, binds the promotor region of IL-22RA1 gene and transcriptionally increases IL-22RA1 expression in mTEC1 cells. Foxn1-cre-mediated IL-22RA1 knockout (Il22ra1KO) blocks thymus regeneration after irradiation. Furthermore, targeting AHR or IL-22RA1 has significant impacts on severity of murine chronic graft-versus-host disease (cGVHD), which is an autoimmune-like complication following allogeneic hematopoietic cell transplantation. Giving FICZ decreases cGVHD, whereas Il22ra1KO exacerbates cGVHD. The impacts on cGVHD are associated with thymus regeneration and T-cell immune reconstitution. In conclusion, we report an unrecognized function of TECs-expressed AHR in thymus regeneration and AHR transcriptionally regulates IL-22RA1 expression, which have implications for improving thymus regeneration and controlling cGVHD.
Predicting crystal form stability under real-world conditions
Authors: Firaha Dzmitry , Liu Yifei Michelle , van de Streek Jacco , Sasikumar Kiran , Dietrich Hanno , Helfferich Julian , Aerts Luc , Braun Doris E. , Broo Anders , DiPasquale Antonio G. , Lee Alfred Y. , Le Meur Sarah , Nilsson Lill Sten O. , Lunsmann Walter J. , Mattei Alessandra , Muglia Pierandrea , Putra Okky Dwichandra , Raoui Mohamed , Reutzel-Edens Susan M. , Rome Sandrine , Sheikh Ahmad Y. , Tkatchenko Alexandre , Woollam Grahame R. , Neumann Marcus A. 
Published: November 2023

AbstractThe physicochemical properties of molecular crystals, such as solubility, stability, compactability, melting behaviour and bioavailability, depend on their crystal form1. In silico crystal form selection has recently come much closer to realization because of the development of accurate and affordable free-energy calculations2–4. Here we redefine the state of the art, primarily by improving the accuracy of free-energy calculations, constructing a reliable experimental benchmark for solid–solid free-energy differences, quantifying statistical errors for the computed free energies and placing both hydrate crystal structures of different stoichiometries and anhydrate crystal structures on the same energy landscape, with defined error bars, as a function of temperature and relative humidity. The calculated free energies have standard errors of 1–2 kJ mol−1 for industrially relevant compounds, and the method to place crystal structures with different hydrate stoichiometries on the same energy landscape can be extended to other multi-component systems, including solvates. These contributions reduce the gap between the needs of the experimentalist and the capabilities of modern computational tools, transforming crystal structure prediction into a more reliable and actionable procedure that can be used in combination with experimental evidence to direct crystal form selection and establish control5.
Preserved neural dynamics across animals performing similar behaviour
Authors: Safaie Mostafa , Chang Joanna C. , Park Junchol , Miller Lee E. , Dudman Joshua T. , Perich Matthew G. , Gallego Juan A. 
Published: November 2023

AbstractAnimals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual. The overall organization of neural circuits is preserved across individuals1 because of their common evolutionarily specified developmental programme2–4. Such organization at the circuit level may constrain neural activity5–8, leading to low-dimensional latent dynamics across the neural population9–11. Accordingly, here we suggested that the shared circuit-level constraints within a species would lead to suitably preserved latent dynamics across individuals. We analysed recordings of neural populations from monkey and mouse motor cortex to demonstrate that neural dynamics in individuals from the same species are surprisingly preserved when they perform similar behaviour. Neural population dynamics were also preserved when animals consciously planned future movements without overt behaviour12 and enabled the decoding of planned and ongoing movement across different individuals. Furthermore, we found that preserved neural dynamics extend beyond cortical regions to the dorsal striatum, an evolutionarily older structure13,14. Finally, we used neural network models to demonstrate that behavioural similarity is necessary but not sufficient for this preservation. We posit that these emergent dynamics result from evolutionary constraints on brain development and thus reflect fundamental properties of the neural basis of behaviour.
Neural landscape diffusion resolves conflicts between needs across time
Authors: Richman Ethan B. , Ticea Nicole , Allen William E. , Deisseroth Karl , Luo Liqun 
Published: November 2023

AbstractAnimals perform flexible goal-directed behaviours to satisfy their basic physiological needs1–12. However, little is known about how unitary behaviours are chosen under conflicting needs. Here we reveal principles by which the brain resolves such conflicts between needs across time. We developed an experimental paradigm in which a hungry and thirsty mouse is given free choices between equidistant food and water. We found that mice collect need-appropriate rewards by structuring their choices into persistent bouts with stochastic transitions. High-density electrophysiological recordings during this behaviour revealed distributed single neuron and neuronal population correlates of a persistent internal goal state guiding future choices of the mouse. We captured these phenomena with a mathematical model describing a global need state that noisily diffuses across a shifting energy landscape. Model simulations successfully predicted behavioural and neural data, including population neural dynamics before choice transitions and in response to optogenetic thirst stimulation. These results provide a general framework for resolving conflicts between needs across time, rooted in the emergent properties of need-dependent state persistence and noise-driven shifts between behavioural goals.
Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States
Authors: Fujita K. Sydny , Ancona Zachary H. , Kramer Louisa A. , Straka Mary , Gautreau Tandie E. , Robson Dana , Garrity Chris , Hoen Ben , Diffendorfer Jay E. 
Published: November 2023

AbstractOver 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MWdc) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON.
A brain MRI dataset and baseline evaluations for tumor recurrence prediction after Gamma Knife radiotherapy
Authors: Wang Yibin , Duggar William Neil , Caballero David Michael , Thomas Toms Vengaloor , Adari Neha , Mundra Eswara Kumar , Wang Haifeng 
Published: November 2023

AbstractPrediction and identification of tumor recurrence are critical for brain cancer treatment design and planning. Stereotactic radiation therapy delivered with Gamma Knife has been developed as one of the common treatment approaches combined with others by delivering radiation that targets accurately on the tumor while not affecting nearby healthy tissues. In this paper, we release a fully publicly available brain cancer MRI dataset and the companion Gamma Knife treatment planning and follow-up data for the purpose of tumor recurrence prediction. The dataset contains original patient MRI images, radiation therapy data, and clinical information. Lesion annotations are provided, and inclusive preprocessing steps have been specified to simplify the usage of this dataset. A baseline framework based on a convolutional neural network is proposed companionably with basic evaluations. The release of this dataset will contribute to the future development of automated brain tumor recurrence prediction algorithms and promote the clinical implementations associated with the computer vision field. The dataset is made publicly available on The Cancer Imaging Archive (TCIA) (https://doi.org/10.7937/xb6d-py67).
Optimal reference genes for RNA tissue analysis in small animal models of hemorrhagic fever viruses
Authors: Davies Katherine A. , Welch Stephen R. , Sorvillo Teresa E. , Coleman-McCray JoAnn D. , Martin María Laura , Brignone Julia M. , Montgomery Joel M. , Spiropoulou Christina F. , Spengler Jessica R. 
Published: November 2023

AbstractReverse-transcription quantitative polymerase chain reaction assays are frequently used to evaluate gene expression in animal model studies. Data analyses depend on normalization using a suitable reference gene (RG) to minimize effects of variation due to sample collection, sample processing, or experimental set-up. Here, we investigated the suitability of nine potential RGs in laboratory animals commonly used to study viral hemorrhagic fever infection. Using tissues (liver, spleen, gonad [ovary or testis], kidney, heart, lung, eye, brain, and blood) collected from naïve animals and those infected with Crimean–Congo hemorrhagic fever (mice), Nipah (hamsters), or Lassa (guinea pigs) viruses, optimal species-specific RGs were identified based on five web-based algorithms to assess RG stability. Notably, the Ppia RG demonstrated stability across all rodent tissues tested. Optimal RG pairs that include Ppia were determined for each rodent species (Ppia and Gusb for mice; Ppia and Hrpt for hamsters; and Ppia and Gapdh for guinea pigs). These RG pair assays were multiplexed with viral targets to improve assay turnaround time and economize sample usage. Finally, a pan-rodent Ppia assay capable of detecting Ppia across multiple rodent species was developed and successfully used in ecological investigations of field-caught rodents, further supporting its pan-species utility.
Drought-responsive genes in tomato: meta-analysis of gene expression using machine learning
Authors: Chowdhury Rabiul Haq , Eti Fatiha Sultana , Ahmed Rayhan , Gupta Shipan Das , Jhan Pijush Kanti , Islam Tofazzal , Bhuiyan Md. Atiqur Rahman , Rubel Mehede Hassan , Khayer Abul 
Published: November 2023

AbstractPlants have diverse molecular mechanisms to protect themselves from biotic and abiotic stressors and adapt to changing environments. To uncover the genetic potential of plants, it is crucial to understand how they adapt to adverse conditions by analyzing their genomic data. We analyzed RNA-Seq data from different tomato genotypes, tissue types, and drought durations. We used a time series scale to identify early and late drought-responsive gene modules and applied a machine learning method to identify the best responsive genes to drought. We demonstrated six candidate genes of tomato viz. Fasciclin-like arabinogalactan protein 2 (FLA2), Amino acid transporter family protein (ASCT), Arginine decarboxylase 1 (ADC1), Protein NRT1/PTR family 7.3 (NPF7.3), BAG family molecular chaperone regulator 5 (BAG5) and Dicer-like 2b (DCL2b) were responsive to drought. We constructed gene association networks to identify their potential interactors and found them drought-responsive. The identified candidate genes can help to explore the adaptation of tomato plants to drought. Furthermore, these candidate genes can have far-reaching implications for molecular breeding and genome editing in tomatoes, providing insights into the molecular mechanisms that underlie drought adaptation. This research underscores the importance of the genetic basis of plant adaptation, particularly in changing climates and growing populations.