bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Future Increases in Tidal Flooding on Salinity and Groundwater Dynamics in Coastal Aquifers
Authors: Heiss James W. , Mase Bryce , Shen Chengji 
Published: December 2022

AbstractFuture increases in the frequency of tidal flooding due to sea level rise (SLR) are likely to affect pore water salinities in coastal aquifers. In this study, we investigate the impact of increased tidal flooding frequency on salinity and flow dynamics in coastal aquifers using numerical variable‐density variably‐saturated groundwater flow and salt transport models. Short (sub‐daily) and long (decadal) period tides are combined with SLR projections to drive continuous 80‐year models of flow and salt transport. Results show that encroaching intertidal zones lead to both periodic and long‐term vertical salinization of the upper aquifer. Salinization of the upper aquifer due to tidal flooding forces the lower interface seaward, even under SLR. System dynamics are controlled by the interplay between SLR and long period tidal forcing associated with perigean spring tides and the 18.6‐year lunar nodal cycle. Periodic tidal flooding substantially enhances intertidal saltwater‐freshwater mixing, resulting in a 6‐ to 10‐fold expansion of the intertidal saltwater‐freshwater mixing area across SLR scenarios. The onset of the expansion coincides with extreme high water levels resulting from lunar nodal cycling of tidal constituent amplitudes. The findings are the first to demonstrate the combined effects of gradual SLR and short and long period tides on aquifer salinity distributions, and reveal competing influences of SLR on saltwater intrusion. The results are likely to have important implications for coastal ocean chemical fluxes and groundwater resources as tidal flooding intensifies worldwide.
Representing Indian Agricultural Practices and Paddy Cultivation in the Variable Infiltration Capacity Model
Authors: Joseph Jisha , Ghosh Subimal 
Published: December 2022

AbstractIncreased irrigation due to agricultural intensification has profound impacts on the surface water and energy balance at regional to local scales. Recent updates of the state‐of‐the‐art Land Surface Models (LSMs) include the impacts of irrigation on surface hydrology. The Indo‐Gangetic Plain (IGP) is one of the global hotspots of irrigation water applications. However, the direct application of these models to Indian basins has certain limitations. The commonly employed flood irrigation technique is often indiscriminate and unmanaged, unlike the state‐of‐the‐art models' estimation of crop water use based on soil moisture (SM) conditions. The primary crop in the IGP is paddy, cultivated in inundated fields with quite distinct water and energy partitioning mechanisms represented in very few models. Here, we developed an improved irrigation module to simulate the Indian agricultural practices for the widely used Variable Infiltration Capacity model. We incorporated the crop‐specific water use for flood irrigation, calculated based on previously reported field studies. The water and energy balance processes are modified by incorporating the ponded paddy fields with proper parameterization. We achieved moderate improvement in the simulated evapotranspiration (ET) and SM of the IGP, particularly in the non‐monsoon seasons with the updated model. We found that ET and SM are more sensitive to the irrigation techniques than the interval of irrigation application. Runoff strongly responded to irrigation technique as well as the interval of application. We emphasize accurate representation of irrigation practices in the LSMs, specifically when applied to the human‐natural hydrological system.
Matrix protein Tenascin-C promotes kidney fibrosis via STAT3 activation in response to tubular injury
Authors: Xie Qionghong , Zhang Min , Mao Xiaoyi , Xu Mingyue , Liu Shaojun , Shang Da , Xu Yunyu , Chen Ruiying , Guan Yi , Huang Xinzhong , Zent Roy , Pozzi Ambra , Hao Chuan-Ming 
Published: December 2022

AbstractAccumulating evidence indicates that the extracellular matrix (ECM) is not only a consequence of fibrosis, but also contributes to the progression of fibrosis, by creating a profibrotic microenvironment. Tenascin-C (TNC) is an ECM glycoprotein that contains multiple functional domains. We showed that following kidney injury, TNC was markedly induced in fibrotic areas in the kidney from both mouse models and humans with kidney diseases. Genetically deletion of TNC in mice significantly attenuated unilateral ureteral obstruction-induced kidney fibrosis. Further studies showed that TNC promoted the proliferation of kidney interstitial cells via STAT3 activation. TNC-expressing cells in fibrotic kidney were activated fibroblast 2 (Act.Fib2) subpopulation, according to a previously generated single nucleus RNA-seq dataset profiling kidney of mouse UUO model at day 14. To identify and characterize TNC-expressing cells, we generated a TNC-promoter-driven CreER2-IRES-eGFP knock-in mouse line and found that the TNC reporter eGFP was markedly induced in cells around injured tubules that had lost epithelial markers, suggesting TNC was induced in response to epithelium injury. Most of the eGFP-positive cells were both NG2 and PDGFRβ positive. These cells did not carry markers of progenitor cells or macrophages. In conclusion, this study provides strong evidence that matrix protein TNC contributes to kidney fibrosis. TNC pathway may serve as a potential therapeutic target for interstitial fibrosis and the progression of chronic kidney disease.
AKAP8L enhances the stemness and chemoresistance of gastric cancer cells by stabilizing SCD1 mRNA
Authors: Zhang Ruihong , Liu Luguang , Wang Fengqin , Zhao Weizhu , Liu Kai , Yu Hang , Zhao Siwei , Xu Botao , Zhang Xiaoli , Chai Jie , Hao Jing 
Published: December 2022

AbstractGastric cancer (GC) remains the third leading cause of cancer-related deaths. Chemoresistance is the major determinant of GC treatment failure. To explore the molecular mechanisms of GC chemoresistance, mass spectrometry was performed to detect the genes altered in expression between chemoresistant and chemosensitive GC. PRKA kinase anchor protein 8L (AKAP-8L) was identified as one of the top upregulated genes in chemoresistant GC tissues. Moreover, the higher AKAP-8L expression was associated with the lower survival rate in GC patients. Overexpression of AKAP-8L enhanced the GC cell stemness and chemoresistance of oxaliplatin in vivo and in vitro. AKAP-8L deficiency obtained the opposite results. Mechanistically, AKAP-8L interacted with Stearoyl-CoA desaturase 1 (SCD1) mRNA and IGF2BP1 protein, and regulated SCD1 mRNA stability via IGF2BP1-dependent manner. SCD1 played a critical role in mediating the function of AKAP-8L in GC cell stemness and chemoresistance. Clinically, AKAP-8L and SCD1 protein levels was positively associated with human GC chemoresistance. Taken together, our results demonstrated that AKAP-8L facilitates GC chemoresistance via regulating SCD1-mediated stemness of GC cells. AKAP8L may represent a novel therapeutic target to overcome GC chemoresistance.
Weighted kernels improve multi-environment genomic prediction
Authors: Hu Xiaowei , Carver Brett F. , El-Kassaby Yousry A. , Zhu Lan , Chen Charles 
Published: December 2022

AbstractCrucial to variety improvement programs is the reliable and accurate prediction of genotype’s performance across environments. However, due to the impactful presence of genotype by environment (G×E) interaction that dictates how changes in expression and function of genes influence target traits in different environments, prediction performance of genomic selection (GS) using single-environment models often falls short. Furthermore, despite the successes of genome-wide association studies (GWAS), the genetic insights derived from genome-to-phenome mapping have not yet been incorporated in predictive analytics, making GS models that use Gaussian kernel primarily an estimator of genomic similarity, instead of the underlying genetics characteristics of the populations. Here, we developed a GS framework that, in addition to capturing the overall genomic relationship, can capitalize on the signal of genetic associations of the phenotypic variation as well as the genetic characteristics of the populations. The capacity of predicting the performance of populations across environments was demonstrated by an overall gain in predictability up to 31% for the winter wheat DH population. Compared to Gaussian kernels, we showed that our multi-environment weighted kernels could better leverage the significance of genetic associations and yielded a marked improvement of 4–33% in prediction accuracy for half-sib families. Furthermore, the flexibility incorporated in our Bayesian implementation provides the generalizable capacity required for predicting multiple highly genetic heterogeneous populations across environments, allowing reliable GS for genetic improvement programs that have no access to genetically uniform material.
Sleep-like unsupervised replay reduces catastrophic forgetting in artificial neural networks
Authors: Tadros Timothy , Krishnan Giri P. , Ramyaa Ramyaa , Bazhenov Maxim 
Published: December 2022

AbstractArtificial neural networks are known to suffer from catastrophic forgetting: when learning multiple tasks sequentially, they perform well on the most recent task at the expense of previously learned tasks. In the brain, sleep is known to play an important role in incremental learning by replaying recent and old conflicting memory traces. Here we tested the hypothesis that implementing a sleep-like phase in artificial neural networks can protect old memories during new training and alleviate catastrophic forgetting. Sleep was implemented as off-line training with local unsupervised Hebbian plasticity rules and noisy input. In an incremental learning framework, sleep was able to recover old tasks that were otherwise forgotten. Previously learned memories were replayed spontaneously during sleep, forming unique representations for each class of inputs. Representational sparseness and neuronal activity corresponding to the old tasks increased while new task related activity decreased. The study suggests that spontaneous replay simulating sleep-like dynamics can alleviate catastrophic forgetting in artificial neural networks.
Bond-selective intensity diffraction tomography
Authors: Zhao Jian , Matlock Alex , Zhu Hongbo , Song Ziqi , Zhu Jiabei , Wang Biao , Chen Fukai , Zhan Yuewei , Chen Zhicong , Xu Yihong , Lin Xingchen , Tian Lei , Cheng Ji-Xin 
Published: December 2022

AbstractRecovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 s per volume, with a lateral and axial resolution of ~350 nm and ~1.1 µm, respectively. BS-IDT’s application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 µm x 100 µm).
Sequence-specific capture and concentration of viral RNA by type III CRISPR system enhances diagnostic
Authors: Nemudraia Anna , Nemudryi Artem , Buyukyoruk Murat , Scherffius Andrew M. , Zahl Trevor , Wiegand Tanner , Pandey Shishir , Nichols Joseph E. , Hall Laina N. , McVey Aidan , Lee Helen H. , Wilkinson Royce A. , Snyder Laura R. , Jones Joshua D. , Koutmou Kristin S. , Santiago-Frangos Andrew , Wiedenheft Blake 
Published: December 2022

AbstractType-III CRISPR-Cas systems have recently been adopted for sequence-specific detection of SARS-CoV-2. Here, we repurpose the type III-A CRISPR complex from Thermus thermophilus (TtCsm) for programmable capture and concentration of specific RNAs from complex mixtures. The target bound TtCsm complex generates two cyclic oligoadenylates (i.e., cA3 and cA4) that allosterically activate ancillary nucleases. We show that both Can1 and Can2 nucleases cleave single-stranded RNA, single-stranded DNA, and double-stranded DNA in the presence of cA4. We integrate the Can2 nuclease with type III-A RNA capture and concentration for direct detection of SARS-CoV-2 RNA in nasopharyngeal swabs with 15 fM sensitivity. Collectively, this work demonstrates how type-III CRISPR-based RNA capture and concentration simultaneously increases sensitivity, limits time to result, lowers cost of the assay, eliminates solvents used for RNA extraction, and reduces sample handling.
A photoacoustic patch for three-dimensional imaging of hemoglobin and core temperature
Authors: Gao Xiaoxiang , Chen Xiangjun , Hu Hongjie , Wang Xinyu , Yue Wentong , Mu Jing , Lou Zhiyuan , Zhang Ruiqi , Shi Keren , Chen Xue , Lin Muyang , Qi Baiyan , Zhou Sai , Lu Chengchangfeng , Gu Yue , Yang Xinyi , Ding Hong , Zhu Yangzhi , Huang Hao , Ma Yuxiang , Li Mohan , Mishra Aditya , Wang Joseph , Xu Sheng 
Published: December 2022

AbstractElectronic patches, based on various mechanisms, allow continuous and noninvasive monitoring of biomolecules on the skin surface. However, to date, such devices are unable to sense biomolecules in deep tissues, which have a stronger and faster correlation with the human physiological status than those on the skin surface. Here, we demonstrate a photoacoustic patch for three-dimensional (3D) mapping of hemoglobin in deep tissues. This photoacoustic patch integrates an array of ultrasonic transducers and vertical-cavity surface-emitting laser (VCSEL) diodes on a common soft substrate. The high-power VCSEL diodes can generate laser pulses that penetrate >2 cm into biological tissues and activate hemoglobin molecules to generate acoustic waves, which can be collected by the transducers for 3D imaging of the hemoglobin with a high spatial resolution. Additionally, the photoacoustic signal amplitude and temperature have a linear relationship, which allows 3D mapping of core temperatures with high accuracy and fast response. With access to biomolecules in deep tissues, this technology adds unprecedented capabilities to wearable electronics and thus holds significant implications for various applications in both basic research and clinical practice.
Selective and rapid extraction of trace amount of gold from complex liquids with silver(I)-organic frameworks
Authors: Luo Jie , Luo Xiao , Xie Mo , Li Hao-Zhen , Duan Haiyan , Zhou Hou-Gan , Wei Rong-Jia , Ning Guo-Hong , Li Dan 
Published: December 2022

AbstractThe design of adsorbents for rapid, selective extraction of ultra-trace amounts of gold from complex liquids is desirable from both an environmental and economical point of view. However, the development of such materials remains challenging. Herein, we report the fabrication of two vinylene-linked two-dimensional silver(I)-organic frameworks prepared via Knoevenagel condensation. This material enables selective sensing of gold with a low limit of detection of 60 ppb, as well as selective uptake of ultra-trace gold from complex aqueous mixtures including distilled water with 15 competing metal ions, leaching solution of electronic waste (e-waste), wastewater, and seawater. The present adsorbent delivers a gold adsorption capacity of 954 mg g−1, excellent selectivity and reusability, and can rapidly and selectively extract ultra-trace gold from seawater down to ~20 ppb (94% removal in 10 minutes). In addition, the purity of recovered gold from e-waste reaches 23.8 Karat (99.17% pure).
A nigro–subthalamo–parabrachial pathway modulates pain-like behaviors
Authors: Jia Tao , Wang Ying-Di , Chen Jing , Zhang Xue , Cao Jun-Li , Xiao Cheng , Zhou Chunyi 
Published: December 2022

AbstractThe basal ganglia including the subthalamic nucleus (STN) and substantia nigra pars reticulata (SNr) are involved in pain-related responses, but how they regulate pain processing remains unknown. Here, we identify a pathway, consisting of GABAergic neurons in the SNr (SNrGABA) and glutamatergic neurons in the STN (STNGlu) and the lateral parabrachial nucleus (LPBGlu), that modulates acute and persistent pain states in both male and female mice. The activity of STN neurons was enhanced in acute and persistent pain states. This enhancement was accompanied by hypoactivity in SNrGABA neurons and strengthening of the STN–LPB glutamatergic projection. Reversing the dysfunction in the SNrGABA-STNGlu-LPBGlu pathway attenuated activity of LPBGlu neurons and mitigated pain-like behaviors. Therefore, the SNrGABA-STNGlu-LPBGlu pathway regulates pathological pain and is a potential target for pain management.
SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits
Authors: McJunkin Thomas , Harpt Benjamin , Feng Yi , Losert Merritt P. , Rahman Rajib , Dodson J. P. , Wolfe M. A. , Savage D. E. , Lagally M. G. , Coppersmith S. N. , Friesen Mark , Joynt Robert , Eriksson M. A. 
Published: December 2022

AbstractLarge-scale arrays of quantum-dot spin qubits in Si/SiGe quantum wells require large or tunable energy splittings of the valley states associated with degenerate conduction band minima. Existing proposals to deterministically enhance the valley splitting rely on sharp interfaces or modifications in the quantum well barriers that can be difficult to grow. Here, we propose and demonstrate a new heterostructure, the “Wiggle Well”, whose key feature is Ge concentration oscillations inside the quantum well. Experimentally, we show that placing Ge in the quantum well does not significantly impact our ability to form and manipulate single-electron quantum dots. We further observe large and widely tunable valley splittings, from 54 to 239 μeV. Tight-binding calculations, and the tunability of the valley splitting, indicate that these results can mainly be attributed to random concentration fluctuations that are amplified by the presence of Ge alloy in the heterostructure, as opposed to a deterministic enhancement due to the concentration oscillations. Quantitative predictions for several other heterostructures point to the Wiggle Well as a robust method for reliably enhancing the valley splitting in future qubit devices.
Dynamic chromatin accessibility deploys heterotypic cis/trans-acting factors driving stomatal cell-fate commitment
Authors: Kim Eun-Deok , Dorrity Michael W. , Fitzgerald Bridget A. , Seo Hyemin , Sepuru Krishna Mohan , Queitsch Christine , Mitsuda Nobutaka , Han Soon-Ki , Torii Keiko U. 
Published: December 2022

AbstractChromatin architecture and transcription factor (TF) binding underpin cell-fate specification during development, but their mutual regulatory relationships remain unclear. Here we report an atlas of dynamic chromatin landscapes during stomatal cell-lineage progression, in which sequential cell-state transitions are governed by lineage-specific bHLH TFs. Major reprogramming of chromatin accessibility occurs at the proliferation-to-differentiation transition. We discover novel co-cis regulatory elements (CREs) signifying the early precursor stage, BBR/BPC (GAGA) and bHLH (E-box) motifs, where master-regulatory bHLH TFs, SPEECHLESS and MUTE, consecutively bind to initiate and terminate the proliferative state, respectively. BPC TFs complex with MUTE to repress SPEECHLESS expression through a local deposition of repressive histone marks. We elucidate the mechanism by which cell-state-specific heterotypic TF complexes facilitate cell-fate commitment by recruiting chromatin modifiers via key co-CREs.
Adaptable physics-based super-resolution for electron backscatter diffraction maps
Authors: Jangid Devendra K. , Brodnik Neal R. , Goebel Michael G. , Khan Amil , Majeti SaiSidharth , Echlin McLean P. , Daly Samantha H. , Pollock Tresa M. , Manjunath B. S. 
Published: December 2022

AbstractIn computer vision, single-image super-resolution (SISR) has been extensively explored using convolutional neural networks (CNNs) on optical images, but images outside this domain, such as those from scientific experiments, are not well investigated. Experimental data is often gathered using non-optical methods, which alters the metrics for image quality. One such example is electron backscatter diffraction (EBSD), a materials characterization technique that maps crystal arrangement in solid materials, which provides insight into processing, structure, and property relationships. We present a broadly adaptable approach for applying state-of-art SISR networks to generate super-resolved EBSD orientation maps. This approach includes quaternion-based orientation recognition, loss functions that consider rotational effects and crystallographic symmetry, and an inference pipeline to convert network output into established visualization formats for EBSD maps. The ability to generate physically accurate, high-resolution EBSD maps with super-resolution enables high-throughput characterization and broadens the capture capabilities for three-dimensional experimental EBSD datasets.
Ultrastrong conductive in situ composite composed of nanodiamond incoherently embedded in disordered multilayer graphene
Authors: Li Zihe , Wang Yujia , Ma Mengdong , Ma Huachun , Hu Wentao , Zhang Xiang , Zhuge Zewen , Zhang Shuangshuang , Luo Kun , Gao Yufei , Sun Lei , Soldatov Alexander V. , Wu Yingju , Liu Bing , Li Baozhong , Ying Pan , Zhang Yang , Xu Bo , He Julong , Yu Dongli , Liu Zhongyuan , Zhao Zhisheng , Yue Yuanzheng , Tian Yongjun , Li Xiaoyan 
Published: December 2022

AbstractTraditional ceramics or metals cannot simultaneously achieve ultrahigh strength and high electrical conductivity. The elemental carbon can form a variety of allotropes with entirely different physical properties, providing versatility for tuning mechanical and electrical properties in a wide range. Here, by precisely controlling the extent of transformation of amorphous carbon into diamond within a narrow temperature–pressure range, we synthesize an in situ composite consisting of ultrafine nanodiamond homogeneously dispersed in disordered multilayer graphene with incoherent interfaces, which demonstrates a Knoop hardness of up to ~53 GPa, a compressive strength of up to ~54 GPa and an electrical conductivity of 670–1,240 S m–1 at room temperature. With atomically resolving interface structures and molecular dynamics simulations, we reveal that amorphous carbon transforms into diamond through a nucleation process via a local rearrangement of carbon atoms and diffusion-driven growth, different from the transformation of graphite into diamond. The complex bonding between the diamond-like and graphite-like components greatly improves the mechanical properties of the composite. This superhard, ultrastrong, conductive elemental carbon composite has comprehensive properties that are superior to those of the known conductive ceramics and C/C composites. The intermediate hybridization state at the interfaces also provides insights into the amorphous-to-crystalline phase transition of carbon.