bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maresin 1 promotes nerve regeneration and alleviates neuropathic pain after nerve injury
Authors: Wei Jinhuan , Chen Gang , Su Wenfeng , Zhao Yayu , Wei Zhongya , Hua Yuchen , Xue Peng , Zhu Xiang , Chen Ying 
Published: May 2021

Abstract
Background: Peripheral nerve injury (PNI) is a public health concern that results in sensory and motor disorders as well as neuropathic pain and secondary lesions. Currently, effective treatments for PNI are still limited. For example, while nerve growth factor (NGF) is widely used in the treatment of PNI to promote nerve regeneration, it also induces pain. Maresin 1 (MaR1) is an anti-inflammatory and proresolving mediator that has the potential to regenerate tissue. We determined whether MaR1 is able to promote nerve regeneration as well as alleviating neuropathic pain, and to be considered as a putative therapeutic agent for treating PNI.Methods: PNI models were constructed with eight-week-old adult male ICR mice and treated with NGF, MaR1 or saline by local application, intrathecal injection or intraplantar injection. Behavioral analysis and muscle atrophy test were assessed after treatment. Immunofluorescence assay was performed to examine the expression of ATF-3, GFAP, IBA1, and NF200. The expression transcript levels of inflammatory factors IL1β, IL-6, and TNF-α were detected by quantitative real-time RT-PCR. AKT, ERK, mTOR, PI3K, phosphorylated AKT, phosphorylated ERK, phosphorylated mTOR, and phosphorylated PI3K levels were examined by western blot analysis. Whole-cell patch-clamp recordings were executed to detect transient receptor potential vanilloid 1 (TRPV1) currents.Results: MaR1 demonstrated a more robust ability to promote sensory and motor function recovery in mice after sciatic nerve crush injury than NGF. Immunohistochemistry analyses showed that the administration of MaR1 to mice with nerve crush injury reduced the number of damaged DRG neurons, promoted injured nerve regeneration and inhibited gastrocnemius muscle atrophy. Western blot analysis of ND7/23 cells cultured with MaR1 revealed that MaR1 regulated neurite outgrowth through the PI3K-AKT-mTOR signaling pathway. Moreover, MaR1 dose-dependently attenuated the mechanical allodynia and thermal hyperalgesia induced by nerve injury. Consistent with the analgesic effect, MaR1 inhibited capsaicin-elicited TRPV1 currents, repressed the nerve injury-induced activation of spinal microglia and astrocytes and reduced the production of proinflammatory cytokines in the spinal cord dorsal horn in PNI mice.Conclusions: Application of MaR1 to PNI mice significantly promoted nerve regeneration and alleviated neuropathic pain, suggesting that MaR1 is a promising therapeutic agent for PNI.
Performance Enhancement Method for Multiple License Plate Recognition in Challenging Environment
Authors: khan khurram , Imran Abid , Rehman Hafiz Zia Ur , Fazil adnan , Zakwan Muhammad , Mehmood Zahid 
Published: May 2021

Abstract
Multiple-license plate recognition is gaining popularity in the Intelligent Transport System (ITS) applications for security monitoring and surveillance. Advancements in acquisition devices have increased the availability of High definition (HD) images, which also can capture images of multiple vehicles. Since License Plate (LP) occupies a relatively small portion of an image, therefore, detection of LP in an image is considered a challenging task. Moreover, the overall performance deteriorates when the low-resolution factor combines with an unconstrained environment, such as night, dusk, and rainy, etc. As it is difficult to locate a small object with varying conditions in an entire image, this paper proposes a two-step approach for plate localization in challenging conditions. In the first step, the Faster-Region-based Convolutional Neural Network algorithm (Faster R-CNN) is used to detect all the vehicles in an image, which results in scaled information to locate plates. In the second step, morphological operations are employed to reduce non-plate regions. Meanwhile, geometric properties are used to localize plates in the HSI color space. This approach increases accuracy and reduces processing time. For character recognition, the Look-Up Table (LUT) classifier using adaptive boosting with Modified Census transform (MCT) as a feature extractor is used. Both proposed plate detection and character recognition methods have significantly outperformed conventional approaches in terms of precision and recall for multiple plate recognition.
First-principles study on methane storage properties of porous graphene modified with Mn
Authors: Zhao Yingjie , Chen Yuhong , Xu Wenhui , Zhang Meiling , Sang Cuicui , Zhang Cairong 
Published: May 2021

Abstract
Porous graphene (PG) has a promising future in gas storage due to its unique pore characteristics and large specific surface area. The adsorption properties of PG and PG modified by Mn atoms (Mn-PG) for CH4 molecules have been studied based on first-principles density functional theory. It was found that the optimal adsorption position of CH4 on PG was the carbon annulus pore, and the adsorption energy was − 0.174 eV. The optimal position of the PG system modified by a single Mn atom is the central hole of the carbon ring, and the optimal position of the two Mn atoms is that Mn atoms are respectively located at different carbon ring holes on the opposite side of PG, with an average binding energy of -4.101 eV. The modification of Mn atom enhances the electronegativity of PG substrate and forms a negative charge center at the carbon ring, which is beneficial to enhance the adsorption performance of CH4 molecules with positive charge on the surface. The CH4 molecules are adsorbed on the PG surface through the electrostatic interaction with Mn atoms and PG substrates as well as the intermolecular force of CH4 molecules. Mn-PG system can adsorb 6 CH4 molecules on one side, and the average adsorption energy is -0.345 eV. When PG was modified with two Mn atoms, 12 CH4 molecules could be adsorbed on both sides, and the average adsorption energy was − 0.338 eV, the adsorption capacity can reach 38.43 wt.%.
WITHDRAWN: Subclinical Sequelae of acute Kidney Injury Predispose To Acute Kidney Injury In Rats: Diagnostic Biomarkers
Authors: Fuentes-Calvo Isabel , Cuesta Cristina , Sancho-Martinez Sandra M. , Hidalgo-Thomas Omar A. , Paniagua-Sancho Maria , Lopez-Hernandez Francisco J. , Martinez-Salgado Carlos 
Published: May 2021

Abstract
Background. Acute kidney injury (AKI) is a risk factor for new AKI episodes and progression to chronic kidney disease, cardiovascular events and death, as under certain circumstances renal repair is maladaptive leading to proinflammatory and profibrotic signals. The definition for AKI recovery is based on increases in plasma creatinine, but it only happens when 50-70 % of nephrons have been lost. There are no studies monitoring the real state of structural and functional recovery after an AKI episode. We analysed the functional and structural sequelae after an episode of AKI in rats, whether and for how long animals retain enhanced sensibility to AKI and whether such a condition may be detected by known biomarkers of subclinical renal damage.Methods. We performed a cisplatin (5mg/kg body weight)-induced AKI in rats and, after recovery, we studied the renal susceptibility to new AKI episodes after treatment with subtoxic doses of gentamicin (50 mg/kg).Results. One week after the recuperation of a cisplatin-induced AKI, the kidneys show histological alterations (cast formation, necrosis and tubular dilatation), and predisposition to new AKI episodes after subtoxic gentamicin treatment. Tubular function (urine output and urinary excretion of K+, assessed by the furosemide tubular function test) remains affected despite the recovery of renal filtration after the AKI episode. Several urinary biomarkers detect this subclinical damage: albumin, transferrin, insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases-2 (TIMP-2). The increased [TIMP-2]*[IGFBP7] urinary excretion predicts new AKI episodes before gentamicin subtoxic treatment.Conclusions. After a cisplatin-induced AKI, the kidneys are in functional risk for new AKI episodes, which can be prevented by monitoring IGFBP7 and TIMP-2 urinary excretion. Our findings require subsequent clinical validation to verify the potential of these biomarkers in predicting future episodes of kidney damage.
A semi-synthetic red light photoswitch for optogenetic control of protein activity
Authors: Kuwasaki Yuto , Suzuki Kazushi , Yu Gaigai , Kakihara Yuki , Nishiwaki Michiru , Fushimi Keiji , Bekdash Ramsey , Shimizu Yoshihiro , Narikawa Rei , Nakajima Takahiro , Yazawa Masayuki , Sato Moritoshi 
Published: May 2021

Abstract
Red light is useful for optogenetic control of various protein activities in mammalian deep tissues due to its high tissue penetration, low invasiveness, and low light scattering. However, technology that enables for the optogenetic manipulation using red light remains elusive. Here we develop a red light-activatable, semi-synthetic photoswitch, named MagRed. MagRed is composed of a red light-absorbing bacterial phytochrome incorporating a mammalian endogenous chromophore, biliverdin, and its photo-state-specific de novo synthetic binder. MagRed allows us to reassemble split-proteins using red light and thereby develop a red light-activatable Cre recombinase, which is applicable for mammalian deep tissues. Additionally, we take advantage of MagRed to develop red light-inducible transcription system based on the CRISPR-Cas9 system, enabling for high induction (up to 378-fold) of multiple user-defined endogenous target genes. With high versatility and regulatability, MagRed provides a powerful technology that easily facilitates optogenetics applications for a variety of biological research areas.
Learning Needs Assessment for Multi-Stakeholder Implementation Science Training in LMIC Settings: Findings and Recommendations
Authors: Turner Mallory Wolfe , Bogdewic Stephanie , Agha Erum , Blanchard Carrie , Sturke Rachel , Pettifor Audrey , Salisbury Kathryn , Marques Andrea Horvath , Excellent Marie Lina , Rajagopal Nitya , Ramaswamy Rohit 
Published: May 2021

Abstract
BackgroundDespite significant progress in the field of implementation science (IS), current training programs are inadequate to meet the global need, especially in low-and middle-income countries (LMICs). Even when training opportunities exist, there is a “knowledge-practice gap,” where implementation research findings are not useful to practitioners in a field designed to bridge that gap. This is a critical challenge in LMICs where complex public health issues must be addressed. This paper describes results from a formal assessment of learning needs, priority topics, and delivery methods for LMIC stakeholders.MethodsWe first reviewed a sample of articles published recently in Implementation Science to identify IS stakeholders and assigned labels and definitions for groups with similar roles. We then employed a multi-step sampling approach and a random sampling strategy to recruit participants (n=39) for a semi-structured interview that lasted 30-60 minutes. Stakeholders with inputs critical to developing training curricula were prioritized and selected for interviews. We created memos from audio recorded interviews and used a deductively created codebook to conduct thematic analysis. We calculated kappa coefficients for each memo and used validation techniques to establish rigor including incorporating feedback from reviewers and member checking.ResultsParticipants included program managers, researchers, and physicians working in over 20 countries, primarily LMICs. The majority had over ten years of implementation experience but fewer than five years of IS experience. Three main themes emerged from the data, pertaining to past experience with IS, future IS training needs, and contextual issues. Most respondents (even with formal training) described their IS knowledge as basic or minimal. Preferences for future training were heterogeneous, but findings suggest that curricula must encompass a broader set of competencies than just IS, include mentorship/apprenticeship, and center the LMIC context.ConclusionThis work is the first to explicitly explore and highlight the need for fundamental, widespread, and context specific training in IS and capacity building in basic operational research for key stakeholders in LMICs. Therefore, we propose the novel approach of intelligent swarming as a solution to help build IS capacity in LMICs through the lens of sustainability and equity.
ACCV: Automatic Classification algorithm of Cataract Video based on Deep learning
Authors: Hu Shenming , Luan Xinze , Wu Hong , Wang Xiaoting , Yan Chunhong , Wang Jingying , Liu Guantong , He Wei 
Published: May 2021

Abstract
Purpose: A real-time automatic cataract grading algorithm based on cataract video is proposed.Materials and Methods: In this retrospective study, we set the video of the eye lens section as the research target. A method is proposed to use YOLO-V3 to assist in positioning, to automatically identify the position of the lens and classify the cataract after color space conversion. The data set is a cataract video file of 38 people's 76 eyes collected by a slit lamp. Data collected using five random manner, the method aims to reduce the influence on the collection algorithm accuracy. The video length is within 10s, and the classified picture data is extracted from the video file. A total of 1520 images are extracted from the image data set, and the data set is divided into training set, validation set and test set according to the ratio of 7:2:1.Results: We verified it on the 76-segment clinical data test set and achieved the accuracy of 0.9400, with the AUC of 0.9880. And the F1 of 0.9388. In addition, because of the color space recognition method, the detection per frame can be completed within 29 microseconds and thus the detection efficiency has been improved significantly.Conclusion: With the efficiency and effectiveness of this algorithm, the lens scan video is used as the research object, which improves the accuracy of the screening. It is closer to the actual cataract diagnosis and treatment process, and can effectively improve the cataract inspection ability of non-ophthalmologists. For cataract screening in poor areas, the accessibility of ophthalmology medical care is also increased.
AC Breakdown Analysis of Synthesized Nanofluids for Transformer Insulation
Authors: OPARANTI SAMSON , Khaleed A.A. , Abdelmalik A.A. 
Published: May 2021

Abstract
This work presents the effect of nanoparticles (Al2O3 and TiO2) on methyl ester synthesized from palm kernel oil for oil-filled power equipment. It investigates the loss tangent, AC conductivity and AC breakdown strength of the methyl ester-based nanofluid. The surface of the nanoparticles was functionalized with oleic acid before dispersing it into methyl ester to modify the stability of the mixture. Scanning electron microscopy coupled with electron dispersive x-ray was done on the two nanoparticles to know the morphology and elemental composition of the nanoparticles. The preparation of nanofluids was achieved through the dispersion of 0.2, 0.4, 0.6, 0.8 and 1wt. % of nanoparticles into the ester. It was observed that the loading of the two nanoparticles reduces the loss tangent and the AC conductivity of methyl ester but with a pronounced enhancement in Al2O3 nanofluid. The Weibull statistical analysis of the breakdown data shows that the dispersion of the nanoparticles in the base fluid increases the characteristic breakdown strength of the ester with an optimum performance at 0.6 wt. %. The characteristic breakdown strength for TiO2 and Al2O3 nanofluid is 60.6 kV and 64.1 kV respectively. The result revealed that Al2O3 nanofluid possesses the highest dielectric properties with low loss, low conductivity and high characteristic breakdown strength which makes it a better replacement for mineral insulating oil.
Quantum state tomography of molecules by ultrafast diffraction
Authors: Zhang Ming , Zhang Shuqiao , Xiong Yanwei , Zhang Hankai , Ischenko Anatoli , Vendrell Oriol , Dong Xiaolong , Mu Xiangxu , Centurion Martin , Xu Haitan , Miller R. J. Dwayne , Li Zheng 
Published: May 2021

Abstract
Ultrafast electron diffraction and time-resolved serial crystallography are the basis of the ongoing revolution in capturing at the atomic level of detail the structural dynamics of molecules. However, most experiments employ the classical “ball-and-stick” depictions, and the information of molecular quantum states, such as the density matrix, is missing. Here, we introduce a framework for the preparation and ultrafast coherent diffraction from rotational wave packets of molecules, and we establish a new variant of quantum state tomography for ultrafast electron diffraction to characterize the molecular quantum states. The ability to reconstruct the density matrix of molecules of arbitrary degrees of freedom will provide us with an unprecedentedly clear view of the quantum states of molecules, and enable the visualization of effects dictated by the quantum dynamics of molecules.
Design of Agricultural Credit Guarantee Risk Prediction Model Based on PSO-SVM in Wireless Network
Authors: Chao ZHANG , Wang Zhenyu , Jie LV 
Published: May 2021

Abstract
In recent years, big data and deep learning technology have been extensively applied in the field of financial risk identification. Many scholars have used deep learning technology to provide early warning of the time series of the risk in agricultural credit guarantee. The traditional model training mainly relies on the evaluation of the financial and non-financial situation of new agricultural business entities to identify the risk in agricultural credit guarantee. Therefore, the selection of influencing factors, model construction and the optimization algorithm are usually highly subjective. And the model is built on the basis of wired network to analyze the risk data, the risk data can not be long-distance transmission. Improving these influencing factors can help to provide more scientific suggestions on the training of the model for the identification of risk in agricultural credit guarantee, and it can also significantly enhance the risk identification accuracy of the model. In this paper, under the wireless network, PSO-SVM was used to model the real data of 510 types of new agricultural operating entities in the agricultural credit guarantee system of L province from 2017 to 2019, and to identify the risks. Finally, a high precision risk identification model of agricultural credit guarantee based on PSO-SVM under wireless network was established, and its accuracy of the identification results was compared with that of the unimproved SVM model. With 14 influencing factors in the test set as input, and a test ratio of 0.3, the following conclusions were obtained: first, after improving the parameter selection and algorithm of the model for the identification of the risk in agricultural credit guarantee based on the traditional SVM, the accuracy of the improved model is higher than that of the traditional model. Second, after adding the influencing factor, namely the cognitive bias of the new agricultural business entities in agricultural product market forecasting, the accuracy of agricultural credit guarantee risk identification model based on PSO-SVM under wireless network reached 92.2%, indicating that the model is well trained and can accurately identify the risk of agricultural credit guarantee in practice.
FAM49B Promotes Breast Cancer Proliferation, Metastasis , and Chemoresistance by Stabilizing ELAVL1 Protein and Regulating Downstream Rab10/TLR4 Pathway
Authors: Li Yanhui , Xiong Yue , Wang Zhen , Han Jianjun , Shi Sufang , He Jinglan , Shen Na , Wu Wenjuan , Wang Rui , Lv Weiwei , Deng Yajun , Liu Weiguang 
Published: May 2021

Abstract
Background: Breast cancer (BC) is one of the most common cancers and the leading cause of death in women. Analysis of online databases revealed that FAM49B is highly expressed in BC and is associated with reduced disease-free survival (DFS) and overall survival (OS). However, the role of FAM49B in BC has not been elucidated yet. Therefore, in this study, we aimed to systematically study the role of FAM49B in the proliferation, metastasis, and chemoresistance of BC, as well as the corresponding mechanisms, and to provide new predictors and targets for BC treatment.Methods: We used western blotting and immunohistochemistry to quantify FAM49B expression levels in human BC samples. A combination of shRNA, co-immunoprecipitation, MTT, migration/invasion, and apoptosis assays, in addition to microarray detection and data analysis and a nude mouse xenograft tumor model, was used for further mechanistic studies.Results: In BC, the results showed that the expression level of FAM49B was significantly higher than that in normal breast tissue, and highly expression of FAM49B was significantly positively correlated with tumor volume, histological grade, lymph node metastasis rate, and poor prognosis. Knockdown or overexpression of FAM49B inhibited or promoted, respectively, the proliferation and migration of BC cells in vitro and in vivo. Microarray analysis revealed that the Toll-like receptor signaling pathway was inhibited upon FAM49B knockdown. In addition, the gene interaction network and downstream protein validation of FAM49B revealed that FAM49B positively regulates BC cell proliferation and migration by promoting the Rab10/TLR4 pathway. Furthermore, endogenous FAM49B interacted with ELAVL1 and positively regulated Rab10 and TLR4 expression by stabilizing ELAVL1. Moreover, mechanistic studies indicated that the lack of FAM49B expression in BC cells conferred more sensitivity to anthracycline and increased cell apoptosis by downregulating the ELAVL1/Rab10/TLR4/NF-κB signaling pathway.Conclusion: FAM49B may be a novel prognostic marker and therapeutic target for BC.
Can we predict which patients with plantar heel pain are more likely to benefit from insoles? a secondary exploratory analysis of a randomized controlled trial
Authors: Rasenberg N. , Dijkgraaf L.J.M. , Bindels P.J. , Bierma-Zeinstra S.M.A. , Middelkoop Marienke van 
Published: May 2021

Abstract
Background Plantar heel pain (PHP) is a common cause of foot complaints, for which treatment with custom-made insoles is frequently applied. So far few studies have investigated patient characteristics that predict response to these treatments. The aim of this secondary exploratory analysis was twofold; firstly, to identify patient characteristics that predict prognosis in patients with PHP treated with insoles, and secondly to identify characteristics that might interact with treatment with insoles. Methods Data from a randomized trial in which participants received either custom insoles (N=70), sham insoles (N=69) or GP-led usual care (N=46) were used. At baseline, information was collected on demographics, foot symptoms, foot and ankle range of motion, navicular drop, presence of neuropathic pain, physical activity and other illnesses in the last 12 months. The primary outcome of this study was the Foot Function Index score(FFI) at 26 weeks. Multivariable linear regression models were generated to identify patients characteristics that predict the outcome for each type of intervention (i.e. insoles and GP-led usual care). Results We found two variables associated with a better function score at 26 weeks in patients treated with insoles, female sex (β -9.59 95%CI -17.87; -1.31) and a lower FFI score at baseline (β 0.56 95%CI 0.30; 0.82). Conclusion When communicating about prognosis of PHP clinicians should take sex and the amount of disability at first presentation into account. Women and people with better function scores at baseline (according to FFI) might respond better to treatment with insoles in terms of foot function. Trial registration: NTR5346