bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dopamine-methacrylated hyaluronic acid hydrogel as an effective carrier for stem cells in skin regeneration therapy
Authors: Gong Meihua , Yan Fei , Yu Li , Li Furong 
Published: August 2022

AbstractAdipose-derived stem cells (ADSCs) show potential in skin regeneration research. A previous study reported the failure of full-thickness skin self-repair in an injury area exceeding 4 cm in diameter. Stem cell therapies have shown promise in accelerating skin regeneration; however, the low survival rate of transplanted cells due to the lack of protection during and after transplantation leads to low efficacy. Hence, effective biomaterials for the delivery and retention of ADSCs are urgently needed for skin regeneration purposes. Here, we covalently crosslinked hyaluronic acid with methacrylic anhydride and then covalently crosslinked the product with dopamine to engineer dopamine-methacrylated hyaluronic acid (DA-MeHA). Our experiments suggested that the DA-MeHA hydrogel firmly adhered to the skin wound defect and promoted cell proliferation in vitro and skin defect regeneration in vivo. Mechanistic analyses revealed that the beneficial effect of the DA-MeHA hydrogel combined with ADSCs on skin defect repair may be closely related to the Notch signaling pathway. The ADSCs from the DA-MeHA hydrogel secrete high levels of growth factors and are thus highly efficacious for promoting skin wound healing. This DA-MeHA hydrogel may be used as an effective potential carrier for stem cells as it enhances the efficacy of ADSCs in skin regeneration.
CircKIF4A promotes glioma growth and temozolomide resistance by accelerating glycolysis
Authors: Luo Kui , Liu Aiqun , Wu Hao , Liu Qiang , Dai Jin , Liu Yu , Wang Zhifei 
Published: August 2022

AbstractCircular RNAs (circRNAs) are a kind of noncoding RNAs that have different biological functions. CircRNAs play very important parts in the progression of cancers. Nevertheless, the exact mechanism and function of many circRNAs in glioma are not clear. In our study, circKIF4A was identified as a remarkably upregulated circRNA expressed in glioma tissues and cell lines. We performed loss-off function and gain-of-function experiments to inquire into the biological function of circKIF4A in the progression of glioma. We discovered that knockdown of circKIF4A remarkably decreased the proliferation and invasion ability of glioma cells. Moreover, subcutaneous tumorigenesis model and intracranial injection of orthotopic glioma model were established to investigate the functions of circKIF4A in vivo. Suppression of circKIF4A remarkably enhanced the sensitivity of glioma to temozolomide treatment. The glycolysis rate was accelerated by circKIF4A overexpression, which promoted glioma growth and temozolomide resistance. The glycolysis regulating enzyme ALDOA was regulated by circKIF4A through the mechanism of interactivity with miR-335-5p in glioma cells. In a word, our data showed that the upregulation of circKIF4A facilitates glioma progression by means of binding miR-335-5p and upregulating ALDOA expression.
Reversal of the renal hyperglycemic memory in diabetic kidney disease by targeting sustained tubular p21 expression
Authors: Al-Dabet Moh’d Mohanad , Shahzad Khurrum , Elwakiel Ahmed , Sulaj Alba , Kopf Stefan , Bock Fabian , Gadi Ihsan , Zimmermann Silke , Rana Rajiv , Krishnan Shruthi , Gupta Dheerendra , Manoharan Jayakumar , Fatima Sameen , Nazir Sumra , Schwab Constantin , Baber Ronny , Scholz Markus , Geffers Robert , Mertens Peter Rene , Nawroth Peter P. , Griffin John H. , Keller Maria , Dockendorff Chris , Kohli Shrey , Isermann Berend 
Published: August 2022

AbstractA major obstacle in diabetes is the metabolic or hyperglycemic memory, which lacks specific therapies. Here we show that glucose-mediated changes in gene expression largely persist in diabetic kidney disease (DKD) despite reversing hyperglycemia. The senescence-associated cyclin-dependent kinase inhibitor p21 (Cdkn1a) was the top hit among genes persistently induced by hyperglycemia and was associated with induction of the p53-p21 pathway. Persistent p21 induction was confirmed in various animal models, human samples and in vitro models. Tubular and urinary p21-levels were associated with DKD severity and remained elevated despite improved blood glucose levels in humans. Mechanistically, sustained tubular p21 expression in DKD is linked to demethylation of its promoter and reduced DNMT1 expression. Two disease resolving agents, protease activated protein C (3K3A-aPC) and parmodulin-2, reversed sustained tubular p21 expression, tubular senescence, and DKD. Thus, p21-dependent tubular senescence is a pathway contributing to the hyperglycemic memory, which can be therapeutically targeted.
Fast DNA-PAINT imaging using a deep neural network
Authors: Narayanasamy Kaarjel K. , Rahm Johanna V. , Tourani Siddharth , Heilemann Mike 
Published: August 2022

AbstractDNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.
Visualizing the failure of solid electrolyte under GPa-level interface stress induced by lithium eruption
Authors: Gao Haowen , Ai Xin , Wang Hongchun , Li Wangqin , Wei Ping , Cheng Yong , Gui Siwei , Yang Hui , Yang Yong , Wang Ming-Sheng 
Published: August 2022

AbstractSolid electrolytes hold the promise for enabling high-performance lithium (Li) metal batteries, but suffer from Li-filament penetration issues. The mechanism of this rate-dependent failure, especially the impact of the electrochemo-mechanical attack from Li deposition, remains elusive. Herein, we reveal the Li deposition dynamics and associated failure mechanism of solid electrolyte by visualizing the Li|Li7La3Zr2O12 (LLZO) interface evolution via in situ transmission electron microscopy (TEM). Under a strong mechanical constraint and low charging rate, the Li-deposition-induced stress enables the single-crystal Li to laterally expand on LLZO. However, upon Li “eruption”, the rapidly built-up local stress, reaching at least GPa level, can even crack single-crystal LLZO particles without apparent defects. In comparison, Li vertical growth by weakening the mechanical constraint can boost the local current density up to A·cm−2 level without damaging LLZO. Our results demonstrate that the crack initiation at the Li|LLZO interface depends strongly on not only the local current density but also the way and efficiency of mass/stress release. Finally, potential strategies enabling fast Li transport and stress relaxation at the interface are proposed for promoting the rate capability of solid electrolytes.
Integrated biosensor platform based on graphene transistor arrays for real-time high-accuracy ion sensing
Authors: Xue Mantian , Mackin Charles , Weng Wei-Hung , Zhu Jiadi , Luo Yiyue , Luo Shao-Xiong Lennon , Lu Ang-Yu , Hempel Marek , McVay Elaine , Kong Jing , Palacios Tomás 
Published: August 2022

AbstractTwo-dimensional materials such as graphene have shown great promise as biosensors, but suffer from large device-to-device variation due to non-uniform material synthesis and device fabrication technologies. Here, we develop a robust bioelectronic sensing platform composed of more than 200 integrated sensing units, custom-built high-speed readout electronics, and machine learning inference that overcomes these challenges to achieve rapid, portable, and reliable measurements. The platform demonstrates reconfigurable multi-ion electrolyte sensing capability and provides highly sensitive, reversible, and real-time response for potassium, sodium, and calcium ions in complex solutions despite variations in device performance. A calibration method leveraging the sensor redundancy and device-to-device variation is also proposed, while a machine learning model trained with multi-dimensional information collected through the multiplexed sensor array is used to enhance the sensing system’s functionality and accuracy in ion classification.
Electron-phonon coupling and vibrational properties of size-selected linear carbon chains by resonance Raman scattering
Authors: Marabotti P. , Tommasini M. , Castiglioni C. , Serafini P. , Peggiani S. , Tortora M. , Rossi B. , Li Bassi A. , Russo V. , Casari C. S. 
Published: August 2022

AbstractUV resonance Raman spectroscopy of size-selected linear sp-carbon chains unveils vibrational overtones and combinations up to the fifth order. Thanks to the tunability of the synchrotron source, we excited each H-terminated polyyne (HCnH withn = 8,10,12) to the maxima of its vibronic absorption spectrum allowing us to precisely determine the electronic and vibrational structure of the ground and excited states for the main observed vibrational mode. Selected transitions are shown to enhance specific overtone orders in the Raman spectrum in a specific way that can be explained by a simple analytical model based on Albrecht’s theory of resonance Raman scattering. The determined Huang–Rhys factors indicate a strong and size-dependent electron-phonon coupling increasing with the sp-carbon chain length.
Organization of the gravity-sensing system in zebrafish
Authors: Liu Zhikai , Hildebrand David G. C. , Morgan Joshua L. , Jia Yizhen , Slimmon Nicholas , Bagnall Martha W. 
Published: August 2022

AbstractMotor circuits develop in sequence from those governing fast movements to those governing slow. Here we examine whether upstream sensory circuits are organized by similar principles. Using serial-section electron microscopy in larval zebrafish, we generated a complete map of the gravity-sensing (utricular) system spanning from the inner ear to the brainstem. We find that both sensory tuning and developmental sequence are organizing principles of vestibular topography. Patterned rostrocaudal innervation from hair cells to afferents creates an anatomically inferred directional tuning map in the utricular ganglion, forming segregated pathways for rostral and caudal tilt. Furthermore, the mediolateral axis of the ganglion is linked to both developmental sequence and neuronal temporal dynamics. Early-born pathways carrying phasic information preferentially excite fast escape circuits, whereas later-born pathways carrying tonic signals excite slower postural and oculomotor circuits. These results demonstrate that vestibular circuits are organized by tuning direction and dynamics, aligning them with downstream motor circuits and behaviors.
A hybrid triboelectric nanogenerator for enhancing corrosion prevention of metal in marine environment
Authors: Wu Menzhen , Guo Wenxi , Dong Shigang , Liu Andeng , Cao Yanhui , Xu Zijie , Lin Changjian , Zhang Jian 
Published: August 2022

AbstractA hybrid spherical triboelectric nanogenerator (S-TENG) with both solid-solid and solid-liquid contact modes is successfully constructed to collect wave energy for highly efficient cathodic protection of metals in marine. To maximize collection of wave energy, the S-TENG is designed to simultaneously capture friction energy from inside and outside the device with different working modes, achieving a short circuit current density of 186 mA m−3 and open circuit voltage of 88.9 V, respectively. It indicates that the potential drop of stainless steel (304SS) and organically coated carbon steel (Q235CS) coupled with the S-TENG are about 410 mV and 930 mV, respectively, which is suitable for their cathodic protection in marine environment. It is demonstrated that our S-TENG as a low-cost and environmentally friendly self-powered approach is promising to effectively converts wave energy for electrochemical cathodic protection in marine.
Stigmasterol attenuates hepatic steatosis in rats by strengthening the intestinal barrier and improving bile acid metabolism
Authors: Zhang Yaxin , Gu Yuyan , Jiang Jing , Cui Xiaobing , Cheng Saibo , Liu Linling , Huang Zhiyong , Liao Rongxin , Zhao Peng , Yu Jieying , Wang Jing , Jia Yuhua , Jin Wen , Zhou Fenghua 
Published: August 2022

AbstractStigmasterol (ST) has been shown to improve both lipid and bile acid (BA) metabolism. However, the mechanism(s) by which ST prevents dyslipidemia via BA metabolism, and the potential involvement of other regulatory mechanisms, remains unclear. Here, we found that ST treatment effectively alleviates lipid metabolism disorder induced by a high-fat diet (HFD). Moreover, we also show that fecal microbiota transplantation from ST-treated rats displays similar protective effects in rats fed on an HFD. Our data confirm that the gut microbiota plays a key role in attenuating HFD-induced fat deposition and metabolic disorders. In particular, ST reverses HFD-induced gut microbiota dysbiosis in rats by reducing the relative abundance of Erysipelotrichaceae and Allobaculum bacteria in the gut. In addition, ST treatment also modifies the serum and fecal BA metabolome profiles in rats, especially in CYP7A1 mediated BA metabolic pathways. Furthermore, chenodeoxycholic acid combined with ST improves the therapeutic effects in HFD-induced dyslipidemia and hepatic steatosis. In addition, this treatment strategy also alters BA metabolism profiles via the CYP7A1 pathway and gut microbiota. Taken together, ST exerts beneficial effects against HFD-induced hyperlipidemia and obesity with the underlying mechanism being partially related to both the reprogramming of the intestinal microbiota and metabolism of BAs in enterohepatic circulation. This study provides a theoretical basis for further study of the anti-obesity effects of ST and consideration of the gut microbiota as a potential target for the treatment of HFD-induced dyslipidemia.
Harmonized nitrogen and phosphorus concentrations in the Mississippi/Atchafalaya River Basin from 1980 to 2018
Authors: Krasovich Emma , Lau Peiley , Tseng Jeanette , Longmate Julia , Bell Kendon , Hsiang Solomon 
Published: August 2022

AbstractWater quality monitoring can inform policies that address pollution; however, inconsistent measurement and reporting practices render many observations incomparable across bodies of water, thereby impeding efforts to characterize spatial patterns and long-term trends in pollution. Here, we harmonized 9.2 million publicly available monitor readings from 226 distinct water monitoring authorities spanning the entirety of the Mississippi/Atchafalaya River Basin (MARB) in the United States. We created the Standardized Nitrogen and Phosphorus Dataset (SNAPD), a novel dataset of 4.8 million standardized observations for nitrogen- and phosphorus-containing compounds from 107 thousand sites during 1980–2018. To the best of our knowledge, this dataset represents the largest record of these pollutants in a single river network where measurements can be compared across time and space. We addressed numerous well-documented issues associated with the reporting and interpretation of these water quality data, heretofore unaddressed at this scale, and our approach to water quality data processing can be applied to other nutrient compounds and regions.
Two multi-temporal datasets to track debris flow after the 2008 Wenchuan earthquake
Authors: Wang Lei , Chang Ming , Le Jian , Xiang Lanlan , Ni Zhang 
Published: August 2022

AbstractWe provide two datasets for tracking the debris flow induced by the 2008 Wenchuan Mw 7.9 earthquake on a section of the Longmen mountains on the eastern side of the Tibetan plateau (Sichuan, China). The database was obtained through a literature review and field survey reports in the epicenter area, combined with high-resolution remote sensing image and extensive data collection and processing. The first dataset covers an area of 892 km2, including debris flows from 2008 to 2020 (an updated version). 186 debris flows affecting 79 watersheds were identified. 89 rainfall stations were collected to determine the rainfall events for the post-earthquake debris flow outbreak. The second database is a list of mitigation measures for post-earthquake debris flows, including catchment name, check dam number, coordinates, construction time, and successful mitigation date. The datasets can aid different applications, including the early warning and engineering prevention of post-earthquake debris flow, as well as provide valuable data support for research in related disciplines.
Synthesis and characterization of biopolyurethane crosslinked with castor oil-based hyperbranched polyols as polymeric solid–solid phase change materials
Authors: Lee Joo Hyung , Kim Seong Hun 
Published: August 2022

AbstractNovel crosslinking bio polyurethane based polymeric solid–solid phase change materials (SSPCM) were synthesized using castor oil (CO) based hyperbranched polyols as crosslinkers. CO-based hyperbranched polyols were synthesized by grafting 1-mercaptoethanol or α–thioglycerol via a thiol-ene click reaction method (coded as COM and COT, respectively). Subsequently, the three SSPCMs were synthesized by a two-step prepolymer method. Polyethylene glycol was used as the phase change material in the SSPCMs, while the CO-based hyperbranched polyols and two types of diisocyanate (hexamethylene diisocyanate (HDI) and 4,4'-diphenylmethane diisocyanate) served as the molecular frameworks. Fourier transform infrared spectroscopy indicated the successful synthesis of the SSPCMs. The solid–solid transition of the prepared SSPCMs was confirmed by X-ray diffraction analysis and polarized optical microscopy. The thermal transition properties of the SSPCMs were analyzed by differential scanning microscopy. The isocyanate and crosslinker types had a significant influence on the phase transition properties. The SSPCM samples prepared using HDI and COT exhibited the highest phase transition enthalpy of 126.5 J/g. The thermal cycling test and thermogravimetric analysis revealed that SSPCMs exhibit outstanding thermal durability. Thus, the novel SSPCMs based on hyperbranched polyols have great potential for application as thermal energy storage materials.
Impact of 24-epibrassinolide, spermine, and silicon on plant growth, antioxidant defense systems, and osmolyte accumulation of maize under water stress
Authors: Ghasemi Azizolah , Farzaneh Salim , Moharramnejad Sajjad , Sharifi Raouf Seyed , Youesf Ahmed Fathy , Telesinski Arkadiusz , Kalaji Hazem M. , Mojski Jacek 
Published: August 2022

AbstractThe effect of triad application of the phytohormone 24-epibrassinolide (EBL), the polyamine spermine (Spm), and the element silicon (Si) has not yet been considered on plant growth and behavior in water-stressed conditions. We aimed to evaluate the impact of single/dual/triad application of 24-epibrassinolide (EBL), spermine (Spm), and silicon (Si) on the growth, photosynthetic metabolites, and antioxidant enzymes in the maize plant exposed to water stress. This study was conducted as a potential drought resistance system and plants' maintenance against oxidative damage. In this regard, one maize hybrid (Paya) was grown under well-watered and water-deficit conditions (interrupted irrigation at the flowering and the filling seed stages) with and without foliar spraying of EBL, Spm, and/or Si. Drought conditions remarkably reduced growth, productivity, water-related content (RWC), and chlorophyll content. However, the dual and triad applications of EBL (0.1 mg L−1), Spm (25 mg L−1), and Si (7 mg L−1) significantly improved the above parameters. Water stress considerably augmented the levels of H2O2 and MDA. Their content in stress-subjected plants was significantly reduced by triad application. In water-stressed circumstances and after foliar treatments, the activities of superoxide dismutase, catalase, and peroxidase as well as the amounts of total soluble proteins, phenolic compounds, proline, and glycine betaine all improved. Overall, triad application increased the plant's drought resistance and diminished ROS accumulation by raising the scavenging via the enhanced activity of the antioxidant enzymes.
Transfer learning strategies for solar power forecasting under data scarcity
Authors: Sarmas Elissaios , Dimitropoulos Nikos , Marinakis Vangelis , Mylona Zoi , Doukas Haris 
Published: August 2022

AbstractAccurately forecasting solar plants production is critical for balancing supply and demand and for scheduling distribution networks operation in the context of inclusive smart cities and energy communities. However, the problem becomes more demanding, when there is insufficient amount of data to adequately train forecasting models, due to plants being recently installed or because of lack of smart-meters. Transfer learning (TL) offers the capability of transferring knowledge from the source domain to different target domains to resolve related problems. This study uses the stacked Long Short-Term Memory (LSTM) model with three TL strategies to provide accurate solar plant production forecasts. TL is exploited both for weight initialization of the LSTM model and for feature extraction, using different freezing approaches. The presented TL strategies are compared to the conventional non-TL model, as well as to the smart persistence model, at forecasting the hourly production of 6 solar plants. Results indicate that TL models significantly outperform the conventional one, achieving 12.6% accuracy improvement in terms of RMSE and 16.3% in terms of forecast skill index with 1 year of training data. The gap between the two approaches becomes even bigger when fewer training data are available (especially in the case of a 3-month training set), breaking new ground in power production forecasting of newly installed solar plants and rendering TL a reliable tool in the hands of self-producers towards the ultimate goal of energy balancing and demand response management from an early stage.
A virtual evaluation of options for managing risk of hospital congestion with minimum intervention
Authors: Hou Wanxin , Qin Shaowen , Thompson Campbell Henry 
Published: August 2022

AbstractHospital congestion is a common problem for the healthcare sector. However, existing approaches including hospital resource optimization and process improvement might lead to huge cost of human and physical structure changes. This study evaluated less disruptive interventions based on a hospital simulation model and offer objective reasoning to support hospital management decisions. This study tested a congestion prevention method that estimates hospital congestion risk level (R), and activates minimum intervention when R is above certain threshold, using a virtual hospital created by simulation modelling. The results indicated that applying a less disruptive intervention is often enough, and more cost effective, to reduce the risk level of hospital congestion. Moreover, the virtual implementation approach enabled testing of the method at a more detailed level, thereby revealed interesting findings difficult to achieve theoretically, such as discharging extra two medical inpatients, rather than surgical inpatients, a day earlier on days when R is above the threshold, would bring more benefits in terms of congestion reduction for the hospital.