bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immune classification of clear cell renal cell carcinoma
Authors: Su Sumeyye , Akbarinejad Shaya , Shahriyari Leili 
Published: February 2021

AbstractSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value $$<0.01$$

<
0.01

). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value $$<0.01$$

<
0.01

), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value $$<0.01$$

<
0.01

). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value $$<0.01$$

<
0.01

) compared to the patients with tumors for all groups of tumors except group 3.
Genetically predicted education attainment in relation to somatic and mental health
Authors: Yuan Shuai , Xiong Ying , Michaëlsson Madeleine , Michaëlsson Karl , Larsson Susanna C. 
Published: February 2021

AbstractA deeper understanding of the causal links from education level to health outcomes may shed a light for disease prevention. In the present Mendelian randomization study, we found that genetically higher education level was associated with lower risk of major mental disorders and most somatic diseases, independent of intelligence. Higher education level adjusted for intelligence was associated with lower risk of suicide attempts, insomnia, major depressive disorder, heart failure, stroke, coronary artery disease, lung cancer, breast cancer, type 2 diabetes and rheumatoid arthritis but with higher risk of obsessive–compulsive disorder, anorexia nervosa, anxiety, bipolar disorder and prostate cancer. Higher education level was associated with reduced obesity and smoking, which mediated quite an extent of the associations between education level and health outcomes. These findings emphasize the importance of education to reduce the burden of common diseases.
Asymptomatic secondary hyperparathyroidism can mimic sacroiliitis on computed tomography
Authors: Kreutzinger Virginie , Diekhoff Torsten , Liefeldt Lutz , Poddubnyy Denis , Hermann Kay Geert A. , Ziegeler Katharina 
Published: February 2021

AbstractSecondary hyperparathyroidism (sHPT) as a result of chronic kidney disease (CKD) is a common health problem and has been reported to manifest at the sacroiliac joints (SIJ). The aim of this investigation was to systematically assess sacroiliac joint changes in asymptomatic sHPT as detected by high-resolution CT. Included in this IRB-approved retrospective case–control study were 56 patients with asymptomatic sHPT as well as 259 matched controls without SIJ disease. Demographic data were retrieved from electronic patient records. High-resolution computed tomography datasets of all patients were subjected to a structured scoring, including erosions, sclerosis, osteophytes, joint space alterations and intraarticular calcifications. Chi2 tests were used to compare frequencies of lesions. Erosions were significantly more prevalent in patients with sHPT, and were found mainly in the ventral (28.6% vs. 13.9%; p = 0.016) and middle (17.9% vs. 7.7%; p = 0.040) iliac portions of the SIJ. Partial ankylosis was rare in both cohorts (3.6% vs. 5.0%; p > 0.999); complete ankylosis was not observed. Neither extent not prevalence of sclerosis or calcifications differed significantly between groups. Joint lesions reminiscent of sacroiliitis can be found in a substantial portion of asymptomatic patients with secondary hyperparathyroidism. Further investigations into the clinical significance of these findings are warranted.
The impacts of the atmospheric boundary layer on regional haze in North China
Authors: Li Qianhui , Zhang Hongsheng , Cai Xuhui , Song Yu , Zhu Tong 
Published: February 2021

AbstractAn intensive atmospheric boundary layer (ABL) experiment was conducted simultaneously at six stations arranged in a cross shape on the North China Plain (NCP) from 26 November to 26 December 2019. The impacts of the regional ABL structure on heavy haze pollution and the relationship between the ABL height and aerosol accumulation layer (AAL) depth were discussed. Bouts of downdrafts generate a persistent descending elevated inversion layer, helping the maintenance and exacerbation of haze pollution. Continuous weak wind layers contribute to the pollutants accumulation, and low-level jets promote the removal of air pollutants. The unique landform conditions of the NCP are reflected in its regional ABL structure and further affect the spatial distribution of haze pollution. Due to the drainage flow and strong downdrafts, the western stations near the mountains have a colder surface and warmer upper air masses, resulting in a more stable stratification and worse diffusion conditions; these stations also experience a thicker weak wind layer caused by increased friction. Thus, the spatial distribution of haze is heavier in the west and lighter in the east. The convective boundary layer (CBL) height declines evidently during haze episodes, usually lower than 560 m. Furthermore, as the vertical distribution of aerosols is mainly influenced by daytime thermal turbulence and maintained at night, it is appropriate to determine the CBL height using the AAL depth. However, the AAL depth is not consistent with the stable boundary layer height due to the influence of the residual layer at night.
Multiplexed neurochemical transmission emulated using a dual-excitatory synaptic transistor
Authors: Ma Mingxue , Ni Yao , Chi Zirong , Meng Wanqing , Yu Haiyang , Gong Jiangdong , Wei Huanhuan , Han Hong , Wang Xinran , Xu Wentao 
Published: February 2021

AbstractThe ability to emulate multiplexed neurochemical transmission is an important step toward mimicking complex brain activities. Glutamate and dopamine are neurotransmitters that regulate thinking and impulse signals independently or synergistically. However, emulation of such simultaneous neurotransmission is still challenging. Here we report design and fabrication of synaptic transistor that emulates multiplexed neurochemical transmission of glutamate and dopamine. The device can perform glutamate-induced long-term potentiation, dopamine-induced short-term potentiation, or co-release-induced depression under particular stimulus patterns. More importantly, a balanced ternary system that uses our ambipolar synaptic device backtrack input ‘true’, ‘false’ and ‘unknown’ logic signals; this process is more similar to the information processing in human brains than a traditional binary neural network. This work provides new insight for neuromorphic systems to establish new principles to reproduce the complexity of a mammalian central nervous system from simple basic units.
Gut microbiome diversity is an independent predictor of survival in cervical cancer patients receiving chemoradiation
Authors: Sims Travis T. , El Alam Molly B. , Karpinets Tatiana V. , Dorta-Estremera Stephanie , Hegde Venkatesh L. , Nookala Sita , Yoshida-Court Kyoko , Wu Xiaogang , Biegert Greyson W. G. , Delgado Medrano Andrea Y. , Solley Travis , Ahmed-Kaddar Mustapha , Chapman Bhavana V. , Sastry K. Jagannadha , Mezzari Melissa P. , Petrosino Joseph F. , Lin Lilie L. , Ramondetta Lois , Jhingran Anuja , Schmeler Kathleen M. , Ajami Nadim J. , Wargo Jennifer , Colbert Lauren E. , Klopp Ann H. 
Published: February 2021

AbstractDiversity of the gut microbiome is associated with higher response rates for cancer patients receiving immunotherapy but has not been investigated in patients receiving radiation therapy. Additionally, current studies investigating the gut microbiome and outcomes in cancer patients may not have adjusted for established risk factors. Here, we sought to determine if diversity and composition of the gut microbiome was independently associated with survival in cervical cancer patients receiving chemoradiation. Our study demonstrates that the diversity of gut microbiota is associated with a favorable response to chemoradiation. Additionally, compositional variation among patients correlated with short term and long-term survival. Short term survivor fecal samples were significantly enriched in Porphyromonas, Porphyromonadaceae, and Dialister, whereas long term survivor samples were significantly enriched in Escherichia Shigella, Enterobacteriaceae, and Enterobacteriales. Moreover, analysis of immune cells from cervical tumor brush samples by flow cytometry revealed that patients with a high microbiome diversity had increased tumor infiltration of CD4+ lymphocytes as well as activated subsets of CD4 cells expressing ki67+ and CD69+ over the course of radiation therapy. Modulation of the gut microbiota before chemoradiation might provide an alternative way to enhance treatment efficacy and improve treatment outcomes in cervical cancer patients.
High-throughput screening and validation of antibodies against synaptic proteins to explore opioid signaling dynamics
Authors: Lemos Duarte Mariana , Trimbake Nikita A. , Gupta Achla , Tumanut Christine , Fan Xiaomin , Woods Catherine , Ram Akila , Gomes Ivone , Bobeck Erin N. , Schechtman Deborah , Devi Lakshmi A. 
Published: February 2021

AbstractAntibodies represent powerful tools to examine signal transduction pathways. Here, we present a strategy integrating multiple state-of-the-art methods to produce, validate, and utilize antibodies. Focusing on understudied synaptic proteins, we generated 137 recombinant antibodies. We used yeast display antibody libraries from the B cells of immunized rabbits, followed by FACS sorting under stringent conditions to identify high affinity antibodies. The antibodies were validated by high-throughput functional screening, and genome editing. Next, we explored the temporal dynamics of signaling in single cells. A subset of antibodies targeting opioid receptors were used to examine the effect of treatment with opiates that have played central roles in the worsening of the ‘opioid epidemic.’ We show that morphine and fentanyl exhibit differential temporal dynamics of receptor phosphorylation. In summary, high-throughput approaches can lead to the identification of antibody-based tools required for an in-depth understanding of the temporal dynamics of opioid signaling.
Passive eDNA collection enhances aquatic biodiversity analysis
Authors: Bessey Cindy , Neil Jarman Simon , Simpson Tiffany , Miller Haylea , Stewart Todd , Kenneth Keesing John , Berry Oliver 
Published: February 2021

AbstractEnvironmental DNA (eDNA) metabarcoding is a sensitive and widely used approach for species detection and biodiversity assessment. The most common eDNA collection method in aquatic systems is actively filtering water through a membrane, which is time consuming and requires specialized equipment. Ecological studies investigating species abundance or distribution often require more samples than can be practically collected with current filtration methods. Here we demonstrate how eDNA can be passively collected in both tropical and temperate marine systems by directly submerging filter membranes (positively charged nylon and non-charged cellulose ester) in the water column. Using a universal fish metabarcoding assay, we show that passive eDNA collection can detect fish as effectively as active eDNA filtration methods in temperate systems and can also provide similar estimates of total fish biodiversity. Furthermore, passive eDNA collection enables greater levels of biological sampling, which increases the range of ecological questions that eDNA metabarcoding can address.
Size-control in the synthesis of oxo-bridged phosphazane macrocycles via a modular addition approach
Authors: Shi Xiaoyan , León Felix , Ong How Chee , Ganguly Rakesh , Díaz Jesús , García Felipe 
Published: February 2021

AbstractInorganic macrocycles remain largely underdeveloped compared with their organic counterparts due to the challenges involved in their synthesis. Among them, cyclodiphosphazane macrocycles have shown to be promising candidates for supramolecular chemistry applications due to their ability to encapsulate small molecules or ions within their cavities. However, further developments have been handicapped by the lack of synthetic routes to high-order cyclodiphosphazane macrocycles. Moreover, current approaches allow little control over the size of the macrocycles formed. Here we report the synthesis of high-order oxygen-bridged phosphazane macrocycles via a “3 + n cyclisation” (n = 1 and 3). Using this method, an all-PIII high-order hexameric cyclodiphosphazane macrocycle was isolated, displaying a larger macrocyclic cavity than comparable organic crown-ethers. Our approach demonstrates that increasing building block complexity enables precise control over macrocycle size, which will not only generate future developments in both the phosphazane and main group chemistry but also in the fields of supramolecular chemistry.
Influence of interaction between surface-modified magnetic nanoparticles with infectious biofilm components in artificial channel digging and biofilm eradication by antibiotics in vitro and in vivo
Authors: Quan Kecheng , Jiang Guimei , Liu Jian , Zhang Zexin , Ren Yijin , Busscher Henk J. , van der Mei Henny C. , Peterson Brandon W. 
Published: February 2021

Artificial channels dug by non-interacting nanoparticles in infectious biofilms enhance antibiotic penetration and bacterial killing in vitro and in vivo.
A novel protection scheme for VSC‐HVDC transmission lines based on current integral autocorrelation
Authors: Wu Chuanjian , Zhang Dahai , Luo Guomin , Li Meng , He Jinghan 
Published: February 2021

AbstractVoltage source converter‐based high voltage direct current (VSC‐HVDC) transmission system has become the mainstream of power construction and plays an increasingly important role in the power system. However, the DC line fault results in shutting down of the converters, which can greatly endanger the security of the power grid. So it is essential to find a fast fault identification strategy for DC line protection technology. In addition, the existing backup protection scheme has the problems of long delay and strict communication synchronisation requirements. Therefore, this study proposes a novel protection scheme for VSC‐HVDC transmission lines based on the fault current integral autocorrelation coefficient. The fault current and fault current frequency characteristics of VSC‐HVDC transmission lines are analysed first. Second, this study proposes a method to filter out distributed capacitance current by current integration and eliminate the oscillation of fault current. Finally, the difference of the current integral during different faults (internal or external fault) is analysed, and the autocorrelation coefficient is introduced to express the difference. Hence, this study proposes a new principle for identifying faults using the autocorrelation coefficient of the fault current integral. Simulation results show that the protection principle is not affected by the distributed capacitive current and does not require strict communication synchronisation. It has an excellent performance in intolerance to fault resistance and noise interference and can be used as backup protection for VSC‐HVDC transmission system.
Regulating dielectric performances of Poly(vinylidene fluoride) nanocomposites by individually controlling shell thickness of Core@Double‐Shells structured nanowires
Authors: Yang Minhao , Xue Zhi‐Yong , Dang Zhi‐Min , Shen Yang , Haghi‐Ashtiani Paul , He Delong , Xu Jian , Bai Jinbo 
Published: February 2021

AbstractThe synthesis of core@double‐shells structured TiO2@C@SiO2 nanowires (NWs) with variable thickness of carbon inner shell and SiO2 outer shell was achieved by individually controlling the chemical vapour deposition time and amount of silicon precursor added in the sol–gel synthesis. The resultant TiO2@C@SiO2 NWs filled nanocomposites exhibited an excellent dielectric performance with simultaneously improved dielectric constant and suppressed dielectric loss, which could be further regulated by individually controlling the carbon inner shell and SiO2 outer shell thickness. More importantly, the influences of the conductive carbon inner shell and insulated SiO2 outer shell thickness on the dielectric performance of nanocomposites were clearly revealed. The increase of the conductive carbon inner shell thickness would lead to an increase in dielectric constant and loss of nanocomposites, while the insulated SiO2 outer shell exhibited a totally opposite law that the dielectric constant and loss of nanocomposites decrease with increasing SiO2 outer shell thickness. Numerical simulations were also carried out to theoretically verify the relationship between the dielectric loss and SiO2 outer shell thickness. This promising controllable multi‐shell structure could be extended to a variety of hybrids to develop high‐performance dielectric nanocomposites.
A novel classification model of collective user web behaviour based on network traffic contents
Authors: Liu Hongri , Wang Shuo , Wei Yuliang , Wang Bailing 
Published: February 2021

AbstractWeb behaviour analysis of a collective user has provided a powerful means for studying the collective user interests on the Internet. However, the existing research merely analyses the behaviour of a single user who accesses multiple applications or multiple users who access one application. The authors propose a web behaviour classification model for collective user, in which the title fields in HTTP flows are extracted from the mirrored network traffic that has been already captured for any given period of time. The title fields, considered as the short abstract of the whole web pages browsed by the users, are vectorized by natural language processing technologies. Specifically, the Latent Dirichlet allocation (LDA) algorithm is used to calculate the topic distribution probability matrix. Afterward, the multi‐class classifiers are trained and tested using the manually labelled probability distribution matrix from the output of the LDA algorithm to classify the user behaviour topics. The experiments demonstrate that the highest classification accuracy of the model reaches 81.2% by combing the LDA algorithm with Random Forest classifiers under the classification model.
Analysing digital predistortion technique for computation‐efficient power amplifier linearisation in the presence of measurement noise
Authors: Tripathi Girish Chandra , Rawat Meenakshi 
Published: February 2021

AbstractThe noise is an inherent part of a transceiver system, which becomes more severe on low‐cost systems. The power amplifier (PA) further enhances this noise and the signal to be propagated to the receiver. The conventional approach of digital predistortion (DPD) assumes an ideal transceiver system while extracting data for the predistortion function generation. As a result, performance limitation arises due to residual signal–noise interaction. This study presents the accuracy and implementation issues of DPD on a low‐cost transceiver having lower bit resolution in the presence of transceiver noise. Different model architectures, as well as processing algorithms, are compared in terms of numerical stability of the solution (condition number of observation matrix), efficient field‐programmable gate array (FPGA) implementation (dispersion of coefficients, in‐band model performance (normalised mean square error), and out‐of‐band model performance (adjacent channel power ratio). The simulation results are tested on FPGA and direct conversion transceiver‐based platform using PA. A long‐term evolution signal with 64 quadrature amplitude modulation is used for performance evaluation. The suitability of the various polynomial models for fixed‐point implementation and the required memory size for implementing the DPD model is further established.
Smooth particle filter‐based likelihood approximations for remaining useful life prediction of Lithium‐ion batteries
Authors: El‐Dalahmeh Mo'ath , Al‐Greer Maher , El‐Dalahmeh Ma'd , Short Michael 
Published: February 2021

AbstractAccurate prediction of the remaining useful life (RUL) in Lithium‐ion batteries (LiBs) is a key aspect of managing its health, in order to promote reliable and secure systems, and to reduce the need for unscheduled maintenance and costs. Recent work on RUL prediction has largely focused on refining the accuracy and reliability of the RUL prediction. The author introduces a new online RUL prediction for LiB using smooth particle filter (SPF)‐ based likelihood approximation method. The proposed algorithm can accurately estimate the unknown degradation model parameters and predict the degradation state by solving the optimisation problem at each iteration, rather than only taking a gradient step, that tends to lead to rapid convergence, avoids instability issues and improves predictive accuracy. From the experimental datasets published by Prognostics Centre of Excellence (PCoE) of NASA, a second order degradation model was created to explore the degradation of LiB, utilising non‐linear characteristics and non‐Gaussian capacity degradation. RUL prediction was tested with various predicted starting points to assess whether the amount of data and parameters' uncertainty influenced the accuracy of the prediction. Results show that the proposed prediction approach gives improved prediction accuracy and improves the convergence rate in comparison with the particle filter (PF) and other methods such as unscented particle filter (UPF). Since the maximum error of the SPF predicting approach is relatively small, RUL prediction in the best case at the prediction starting point consisting of 80 cycles is 127 cycles. The prediction relative error was approximately 0.024, and the absolute error of the proposed algorithm is around 2 cycles, which is lower than the PF (around 16 cycles). RUL prediction is close to 108 cycles and relative error is around 0.136, while the absolute error prediction is approximately 16.