bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification and characterization of a silent mutation in RNA binding domain of N protein coding gene from SARS-CoV-2
Authors: Zolfaghari Emameh Reza , Eftekhari Mahyar , Nosrati Hassan , Heshmatnia Jalal , Falak Reza
Published: January 2021

Objective

This study describes the occurrence of a silent mutation in the RNA binding domain of nucleocapsid phosphoprotein (N protein) coding gene from SARS-CoV-2 that may consequence to a missense mutation by onset of another single nucleotide mutation.

Results

In the DNA sequence isolated from severe acute respiratory syndrome (SARS-CoV-2) in Iran, a coding sequence for the RNA binding domain of N protein was detected. The comparison of Chinese and Iranian DNA sequences displayed that a thymine (T) was mutated to cytosine (C), so “TTG” from China was changed to “CTG” in Iran. Both DNA sequences from Iran and China have been encoded for leucine. In addition, the second T in “CTG” in the DNA or uracil (U) in “CUG” in the RNA sequences from Iran can be mutated to another C by a missense mutation resulting from thymine DNA glycosylase (TDG) of human and base excision repair mechanism to produce “CCG” encoding for proline, which consequently may increase the affinity of the RNA binding domain of N protein to viral RNA and improve the transcription rate, pathogenicity, evasion from human immunity system, spreading in the human body, and risk of human-to-human transmission rate of SARS-CoV-2.
Collaborative offloading for UAV-enabled time-sensitive MEC networks
Authors: Li Wen-Tao , Zhao Mingxiong , Wu Yu-Hui , Yu Jun-Jie , Bao Ling-Yan , Yang Huan , Liu Di
Published: January 2021

Recently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV are rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($$\mathbf {P}_{\mathbf {T}}$$

P
T

), resource allocation at UAV ($$\mathbf {P}_{\mathbf {R}}$$

P
R

) and offloading decisions at IoT devices ($$\mathbf {P}_{\mathbf {O}}$$

P
O

) and then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.
A QoS-based joint user association and resource allocation scheme in ultra-dense networks
Authors: Si Zhiwei , Chuai Gang , Gao Weidong , Zhang Jinxi , Chen Xiangyu , Zhang Kaisa
Published: January 2021

Ultra-dense networks (UDNs) have become an important architecture for the fifth generation (5G) networks. A large number of small base stations (SBSs) are deployed to provide high-speed and seamless connections for users in the network. However, the advantage of increasing the system capacity brought by the dense distribution of SBSs comes at the cost of severe inter-cell interference. Although the user-centric virtual cell method has been proposed to solve the interference problem, some challenges have been encountered in practical applications. For example, inter-cell interference still exists to a certain extent, and the cell load may be imbalance. Hence, under the virtual cell architecture, we propose a quality of service (QoS)-based joint user association and resource allocation scheme in UDNs. In order to mitigate the interference, balance cell load and improve the system throughput, a non-convex NP-hard problem is formulated. To effectively solve this problem, we decouple the formulated problem into three sub-problems: user association, physical resource block (PRB) allocation and power allocation. First, we consider the QoS requirements of user equipment (UE) and perform user association based on the PRB estimation method. Then, based on the overlapped virtual cells constructed, we propose a graph-based PRB allocation scheme for reducing virtual inter-cell interference. Moreover, we solve power allocation sub-problem by using the difference of concave (DC) programing method. The simulation results show that our proposed scheme is superior to other schemes in terms of user rates, cell load and system throughput.
Hopf bifurcation in a delayed reaction–diffusion–advection equation with ideal free dispersal
Authors: Liu Yunfeng , Hui Yuanxian
Published: January 2021

In this paper, we investigate a delay reaction–diffusion–advection model with ideal free dispersal. The stability of positive steady-state solutions and the existence of the associated Hopf bifurcation are obtained by analyzing the principal eigenvalue of an elliptic operator. By the normal form theory and the center manifold reduction, the stability and bifurcation direction of Hopf bifurcating periodic solutions are obtained. Moreover, numerical simulations and a brief discussion are presented to illustrate our theoretical results.
Detecting recurrent prostate Cancer using multiparametric MRI, influence of PSA and Gleason grade
Authors: Venkatesan Aradhana M. , Mudairu-Dawodu Eniola , Duran Cihan , Stafford R. Jason , Yan Yuanqing , Wei Wei , Kundra Vikas
Published: January 2021

Background

The utility of multiparametric MRI (mpMRI) in detecting suspected local recurrence post radical prostatectomy (RP) may be associated with PSA and Gleason grade. The purpose of the study was to evaluate the likelihood of detecting locally recurrent prostate cancer utilizing mpMRI in patients with suspected recurrence following radical prostatectomy (RP) parsed by PSA and Gleason grade.

Methods

One hundred ninety five patients with suspected local recurrence were imaged on a 1.5 T MRI with torso array and endorectal coil in this retrospective study. mpMRI interpretations were stratified by PSA and lower (Gleason < 7) vs. higher grade tumors (Gleason 8–10). Recursive partitioning was used to determine whether mpMRI interpretations could be classified as positive or negative.

Results

The majority of mpMRI interpretations in patients with lower Gleason grade tumors and PSA < 0.5 ng/mL were negative (68/78, 87.2%, p = 0.004). The majority of mpMRI interpretations in patients with higher Gleason grade tumors and PSA > 1.5 ng/mL were positive (8/9, 88.9%, p = 0.003). Findings were corroborated by recursive partitioning, which identified a PSA = 0.5 ng/ml in patients with lower grade tumors and a PSA = 1.5 ng/mL in patients with higher grade tumors as differentiating negative and positive mpMRIs.

Conclusion

In the setting of suspected recurrence after RP, mpMRI results are associated with PSA and Gleason grade, both of which can help guide when mpMRI may find utility. mpMRI is likely to be low diagnostic yield and negative for recurrence (87%) in the setting of lower Gleason grade tumors and PSA < 0.5 ng/mL. mpMRI is likely to be of low diagnostic value and positive for recurrence (89%) in the setting of PSA > 1.5 ng/mL and higher grade tumors; in this case, mpMRI findings may be more useful for directing biopsy and local therapy. Between these extremes, PSA > 0.5 ng/mL and lower grade tumors or PSA < 1.5 ng/mL and higher grade tumors, mpMRI results are less predictable, suggesting greater diagnostic value for detecting recurrence post prostatectomy.
Validation of the brief scale for the evaluation of acculturation stress in migrant population (EBEA)
Authors: Urzúa Alfonso , Henríquez Diego , Caqueo-Urízar Alejandra , Smith-Castro Vanessa
Published: January 2021

Background

Acculturation stress is associated with poorer physical and mental health and a lower level of psychological well-being. The causes of acculturation stress are diverse, but most are similar in the migrant population. Despite the importance of evaluating this variable, few studies have reported culturally adapted and validated instruments for specific populations. Based on this, the aim of this study was to evaluate the psychometric properties of a short scale for the evaluation of acculturation stress (EBEA).

Methods

Two studies were conducted, involving 1725 first-generation Colombian and Peruvian migrants living in Chile, between the ages of 18 and 60 years. In addition to the EBEA and as evidence of validity, the Beck Anxiety Scale and the WHOQOL-BREF psychological health domain were applied. A confirmatory factor analysis was carried out, and the reliability and nomological validity were evaluated.

Results

The results in both studies indicated that the scale presents a factorial structure of three dimensions: (a) the stress derived from the preparation and departure from the country of origin, (b) the stress produced by socioeconomic concerns in the host country, and (c) the tensions typical of adaptation to sociocultural changes or Chilean society. The reliability coefficients and the analysis of their nomological validity were very good.

Conclusions

The EBEA is a measure that offers quick, useful screening for researchers who need a short measure for research among migrants. This tool contributes to the work of education, prevention, and intervention in the field of general health and migrants’ mental health.
Outcomes by Clinical and Molecular Features in Children With Medulloblastoma Treated With Risk-Adapted Therapy: Results of an International Phase III Trial (SJMB03)
Authors: Gajjar Amar , Robinson Giles W. , Smith Kyle S. , Lin Tong , Merchant Thomas E. , Chintagumpala Murali , Mahajan Anita , Su Jack , Bouffet Eric , Bartels Ute , Schechter Tal , Hassall Tim , Robertson Thomas , Nicholls Wayne , Gururangan Sridharan , Schroeder Kristin , Sullivan Michael , Wheeler Greg , Hansford Jordan R. , Kellie Stewart J. , McCowage Geoffrey , Cohn Richard , Fisher Michael J. , Krasin Matthew J. , Stewart Clinton F. , Broniscer Alberto , Buchhalter Ivo , Tatevossian Ruth G. , Orr Brent A. , Neale Geoff , Klimo Paul , Boop Frederick , Srinivasan Ashok , Pfister Stefan M. , Gilbertson Richard J. , Onar-Thomas Arzu , Ellison David W. , Northcott Paul A.
Published: January 2021

PURPOSE

SJMB03 (ClinicalTrials.gov identifier: NCT00085202 ) was a phase III risk-adapted trial that aimed to determine the frequency and clinical significance of biological variants and genetic alterations in medulloblastoma.

PATIENTS AND METHODS

Patients 3-21 years old were stratified into average-risk and high-risk treatment groups based on metastatic status and extent of resection. Medulloblastomas were molecularly classified into subgroups (Wingless [WNT], Sonic Hedgehog [SHH], group 3, and group 4) and subtypes based on DNA methylation profiles and overlaid with gene mutations from next-generation sequencing. Coprimary study end points were (1) to assess the relationship between ERBB2 protein expression in tumors and progression-free survival (PFS), and (2) to estimate the frequency of mutations associated with WNT and SHH tumors. Clinical and molecular risk factors were evaluated, and the most robust were used to model new risk-classification categories.

RESULTS

Three hundred thirty eligible patients with medulloblastoma were enrolled. Five-year PFS was 83.2% (95% CI, 78.4 to 88.2) for average-risk patients (n = 227) and 58.7% (95% CI, 49.8 to 69.1) for high-risk patients (n = 103). No association was found between ERBB2 status and PFS in the overall cohort ( P = .74) or when patients were stratified by clinical risk ( P = .71). Mutations in CTNNB1 (96%), DDX3X (37%), and SMARCA4 (24%) were most common in WNT tumors and PTCH1 (38%), TP53 (21%), and DDX3X (19%) in SHH tumors. Methylome profiling classified 53 WNT (17.4%), 48 SHH (15.7%), 65 group 3 (21.3%), and 139 group 4 (45.6%) tumors. A comprehensive clinicomolecular risk factor analysis identified three low-risk groups (WNT, low-risk SHH, and low-risk combined groups 3 and 4) with excellent (5-year PFS > 90%) and two very high-risk groups (high-risk SHH and high-risk combined groups 3 and 4) with poor survival (5-year PFS < 60%).

CONCLUSION

These results establish a new risk stratification for future medulloblastoma trials.
Dust surface potential for the dusty plasma with negative ions and with a three-parameter non-Maxwell velocity distribution
Authors: Yao Guoxue , Du Jiulin
Published: January 2021

We study the dust surface potential for the complex dusty plasma with negative ions and with a three-parameter non-Maxwell velocity distribution. The plasma contains electrons, positive ions, negative ions, and negatively charged dust particles. By using the current equilibrium condition, we derive the relationship between the normalized dust surface potential and the dusty plasma parameters such as the normalized dust number density, the temperature ratio of negative ions to electrons, the density ratio of negative ions to positive ions, and the charge number of negative ions. The numerical analyses show that the relationship depends evidently on the three parameters in the non-Maxwell distribution when the dust surface potential is relatively smaller, but with the increase of the potential, such dependence will weaken soon. The dust surface potential is negative and increases monotonously with the increase of the dust density, and for the complex dusty plasma with the three-parameter non-Maxwell distribution, it is generally greater than that in the same plasma with the kappa-distribution and the Maxwellian distribution.
Variability in atlas registration of optical intrinsic signal imaging and its effect on functional connectivity analysis
Authors: Padawer-Curry Jonah A. , Jahnavi Jharna , Breimann Jake S. , Licht Daniel J. , Yodh Arjun G. , Cohen Akiva S. , White Brian R.
Published: January 2021

To compare neuroimaging data between subjects, images from individual sessions need to be aligned to a common reference or “atlas.” Atlas registration of optical intrinsic signal imaging of mice, for example, is commonly performed using affine transforms with parameters determined by manual selection of canonical skull landmarks. Errors introduced by such procedures have not previously been investigated. We quantify the variability that arises from this process and consequent errors from misalignment that affect interpretation of functional neuroimaging data. We propose an improved method, using separately acquired high-resolution images and demonstrate improvements in variability and alignment using this method.
Dual-band multi-bit programmable reflective metasurface unit cell: design and experiment
Authors: Saifullah Yasir , Chen Qinzhuo , Yang Guo-Min , Waqas Abu Bakar , Xu Feng
Published: January 2021

Programmable reflective metasurfaces that combine the features of reconfigurable phased array antennas and reflectors are an effective solution for radar and modern communication systems. However, most of the demonstrated active metasurfaces support tunable responses for a specific frequency band. Thus, we propose a programmable metasurface that combines the advantages of multi-bit phase quantization and dual-band operations. To actively control the diverse functions, two PIN diodes are integrated on the radiating element, and these diodes are controlled by the biasing voltage. The unit cell is fabricated, and experimental characterization is performed in the waveguide measurement setup. The proposed design can be applied for imaging and high-capacity wireless communications.
Microwave photonic notch filter with integrated phase-to-intensity modulation transformation and optical carrier suppression
Authors: Daulay Okky , Liu Gaojian , Marpaung David
Published: January 2021

We demonstrate for the first time, to the best of our knowledge, an on-chip microwave photonic (MWP) notch filter with high stopband rejection and integrated optical carrier suppression in a phase modulator-based system. The notch filter was achieved through phase modulation to intensity modulation (PM-to-IM) transformation and dual-sideband-processing using a network of three ring resonators (RRs) in a low-loss silicon nitride (

S
i

3

N

4

) platform. We show simultaneous PM-to-IM conversion and optical carrier processing for enhancing the filter performance using a single RR. We achieve filtering with a high stopband rejection of

>

55

d
B

, an optical carrier suppression up to 3 dB, a radio frequency link gain of 3 dB, a noise figure of 31 dB, and a spurious-free dynamic range of

100

d
B

⋅

H
z

2

/

3

. These experiments point to the importance of vectorial spectral shaping of an MWP spectrum for advanced functionalities.
Development of an orally-administrable tumor vasculature-targeting therapeutic using annexin A1-binding D-peptides
Authors: Nonaka Motohiro , Mabashi-Asazuma Hideaki , Jarvis Donald L. , Yamasaki Kazuhiko , Akama Tomoya O. , Nagaoka Masato , Sasai Toshio , Kimura-Takagi Itsuko , Suwa Yoichi , Yaegashi Takashi , Huang Chun-Teng , Nishizawa-Harada Chizuko , Fukuda Michiko N.
Published: January 2021

We previously reported that IF7 peptide, which binds to the annexin A1 (ANXA1) N-terminus, functions as a tumor vasculature-targeted drug delivery vehicle after intravenous injection. To enhance IF7 stabilityin vivo, we undertook mirror-image peptide phage display using a synthetic D-peptide representing the ANXA1 N-terminus as target. We then identified peptide sequences, synthesized them as D-amino acids, and designated the resulting peptide dTIT7, which we showed bound to the ANXA1 N-terminus. Whole body imaging of mouse brain tumor models injected with near infrared fluorescent IRDye-conjugated dTIT7 showed fluorescent signals in brain and kidney. Furthermore, orally-administered dTIT7/geldanamycin (GA) conjugates suppressed brain tumor growth. Ours is a proof-of-concept experiment showing that ANXA1-binding D-peptide can be developed as an orally-administrable tumor vasculature-targeted therapeutic.
Assessment of two DNA extraction kits for profiling poultry respiratory microbiota from multiple sample types
Authors: Abundo Michael E. C. , Ngunjiri John M. , Taylor Kara J. M. , Ji Hana , Ghorbani Amir , K. C. Mahesh , Weber Bonnie P. , Johnson Timothy J. , Lee Chang-Won
Published: January 2021

Characterization of poultry microbiota is becoming increasingly important due to the growing need for microbiome-based interventions to improve poultry health and production performance. However, the lack of standardized protocols for sampling, sample processing, DNA extraction, sequencing, and bioinformatic analysis can hinder data comparison between studies. Here, we investigated how the DNA extraction process affects microbial community compositions and diversity metrics in different chicken respiratory sample types including choanal and tracheal swabs, nasal cavity and tracheal washes, and lower respiratory lavage. We did a side-by-side comparison of the performances of Qiagen DNeasy blood and tissue (BT) and ZymoBIOMICS DNA Miniprep (ZB) kits. In general, samples extracted with the BT kit yielded higher concentrations of total DNA while those extracted with the ZB kit contained higher numbers of bacterial 16S rRNA gene copies per unit volume. Therefore, the samples were normalized to equal amounts of 16S rRNA gene copies prior to sequencing. For each sample type, all predominant bacterial taxa detected in samples extracted with one kit were present in replicate samples extracted with the other kit and did not show significant differences at the class level. However, a few differentially abundant shared taxa were observed at family and genus levels. Furthermore, between-kit differences in alpha and beta diversity metrics at the amplicon sequence variant level were statistically indistinguishable. Therefore, both kits perform similarly in terms of 16S rRNA gene-based poultry microbiome analysis for the sample types analyzed in this study.
Personizing the prediction of future susceptibility to a specific disease
Authors: Taha Kamal , Davuluri Ramana , Yoo Paul , Spencer Jesse
Published: January 2021

A traceable biomarker is a member of a disease’s molecular pathway. A disease may be associated with several molecular pathways. Each different combination of these molecular pathways, to which detected traceable biomarkers belong, may serve as an indicative of the elicitation of the disease at a different time frame in the future. Based on this notion, we introduce a novel methodology for personalizing an individual’s degree of future susceptibility to a specific disease. We implemented the methodology in a working system calledSusceptibilityDegree to aDiseasePredictor (SDDP). For a specific diseased, letSbe the set of molecular pathways, to which traceable biomarkers detected from most patients ofdbelong. For the same diseased, letS′ be the set of molecular pathways, to which traceable biomarkers detected from a certain individual belong. SDDP is able toinferthe subsetS′′ ⊆{S-S′} of undetected molecular pathways for the individual. Thus, SDDP can infer undetected molecular pathways of a disease for an individual based on few molecular pathways detected from the individual. SDDP can also help in inferring thecombinationof molecular pathways in the set {S′+S′′}, whose traceable biomarkerscollectivelyis an indicative of the disease. SDDP is composed of the following four components: information extractor, interrelationship between molecular pathways modeler, logic inferencer, and risk indicator. The information extractor takes advantage of the exponential increase of biomedical literature to automatically extract the common traceable biomarkers for a specific disease. The interrelationship between molecular pathways modeler models the hierarchical interrelationships between the molecular pathways of the traceable biomarkers. The logic inferencer transforms the hierarchical interrelationships between the molecular pathways into rule-based specifications. It employs the specification rules and the inference rules for predicate logic to infer as many as possible undetected molecular pathways of a disease for an individual. The risk indicator outputs a risk indicator value that reflects the individual’s degree of future susceptibility to the disease. We evaluated SDDP by comparing it experimentally with other methods. Results revealed marked improvement.
Prediction of neonatal morbidity and very preterm delivery using maternal steroid biomarkers in early gestation
Authors: Patil Avinash S. , Grotegut Chad A. , Gaikwad Nilesh W. , Dowden Shelley D. , Haas David M.
Published: January 2021

Background

Preterm delivery is a common pregnancy complication that can result in significant neonatal morbidity and mortality. Limited tools exist to predict preterm birth, and none to predict neonatal morbidity, from early in pregnancy. The objective of this study was to determine if the progesterone metabolites 11-deoxycorticosterone (DOC) and 16-alpha hydroxyprogesterone (16α-OHP), when combined with patient demographic and obstetric history known during the pregnancy, are predictive of preterm delivery-associated neonatal morbidity, neonatal length of stay, and risk for spontaneous preterm delivery prior to 32 weeks’ gestation.

Methods and findings

We conducted a cohort study of pregnant women with plasma samples collected as part of Building Blocks of Pregnancy Biobank at the Indiana University School of Medicine. The progesterone metabolites, DOC and 16α-OHP, were quantified by mass spectroscopy from the plasma of 58 pregnant women collected in the late first trimester/early second trimester. Steroid levels were combined with patient demographic and obstetric history data in multivariable logistic regression models. The primary outcome was composite neonatal morbidity as measured by the Hassan scale. Secondary outcomes included neonatal length of stay and spontaneous preterm delivery prior to 32 weeks’ gestation. The final neonatal morbidity model, which incorporated antenatal corticosteroid exposure and fetal sex, was able to predict high morbidity (Hassan score ≥ 2) with an area under the ROC curve (AUROC) of 0.975 (95% CI 0.932, 1.00), while the model without corticosteroid and fetal sex predictors demonstrated an AUROC of 0.927 (95% CI 0.824, 1.00). The Hassan score was highly correlated with neonatal length of stay (p<0.001), allowing the neonatal morbidity model to also predict increased neonatal length of stay (53 [IQR 22, 76] days vs. 4.5 [2, 31] days, above and below the model cut point, respectively; p = 0.0017). Spontaneous preterm delivery prior to 32 weeks’ gestation was also predicted with an AUROC of 0.94 (95% CI 0.869, 1.00).

Conclusions

Plasma levels of DOC and 16α-OHP in early gestation can be combined with patient demographic and clinical data to predict significant neonatal morbidity, neonatal length of stay, and risk for very preterm delivery, though validation studies are needed to verify these findings. Early identification of pregnancies at risk for preterm delivery and neonatal morbidity allows for timely implementation of multidisciplinary care to improve perinatal outcomes.
Single prolonged stress blocks sleep homeostasis and pre-trauma sleep deprivation does not exacerbate the severity of trauma-induced fear-associated memory impairments
Authors: Davis Christopher J. , Gerstner Jason R. , Vanderheyden William M.
Published: January 2021

Sleep is intimately linked to cognitive performance and exposure to traumatic stress that leads to post-traumatic stress disorder (PTSD) impairs both sleep and cognitive function. However, the contribution of pre-trauma sleep loss to subsequent trauma-dependent fear-associated memory impairment remains unstudied. We hypothesized that sleep deprivation (SD) prior to trauma exposure may increase the severity of a PTSD-like phenotype in rats exposed to single prolonged stress (SPS), a rodent model of PTSD. Rats were exposed to SPS alone, SD alone, or a combination of SPS+SD and measures of fear-associated memory impairments and vigilance state changes were compared to a group of control animals not exposed to SPS or SD. We found that SPS, and SPS+SD animals showed impaired fear-associated memory processing and that the addition of SD to SPS did not further exaggerate the effect of SPS alone. Additionally, the combination of SPS with SD results in a unique homeostatic sleep duration phenotype when compared to SD, SPS, or control animals. SPS exposure following SD represses homeostatic rebound and eliminates sleep-deprivation-induced increases in NREM sleep delta power. This work identifies a unique time frame where trauma exposure and sleep interact and identifies this window of time as a potential therapeutic treatment window for staving off the negative consequences of trauma exposure.
Neuroprotection mediated by ST266 requires full complement of proteins secreted by amnion-derived multipotent progenitor cells
Authors: Willett Keirnan , Khan Reas S. , Dine Kimberly , Wessel Howard , Kirshner Ziv Z. , Sauer Jodie L. , Ellis Ashley , Brown Larry R. , Shindler Kenneth S.
Published: January 2021

ST266 is the biological secretome of cultured Amnion-derived Multipotent Progenitor cells containing multiple growth factors and cytokines. While intranasally-administered ST266 improves the phenotype in experimental optic neuritis, specific ST266 components mediating these effects are not known. We compared the effects of ST266 with and without removal of large molecular weight proteins both in vitro and in the multiple sclerosis model experimental autoimmune encephalomyelitis (EAE) in C57BL/6J mice. Mice were treated daily with intranasal vehicle, ST266 or lower molecular weight fraction of ST266. Retinal ganglion cells were counted in isolated retinas, and optic nerves were assessed for inflammation and demyelination. ST266 treatment significantly improved retinal ganglion cell survival and reduced optic nerve demyelination in EAE mice. The lower molecular weight ST266 fraction significantly improved optic nerve demyelination, but only showed a trend towards improved retinal ganglion cell survival. ST266 fractions below 50kDa increased Schwann cell proliferation in vitro, but were less effective than non-fractionated ST266. Demyelination attenuation was partially associated with the lower molecular weight ST266 fraction, but removal of higher molecular weight biomolecules from ST266 diminishes its neuroprotective effects, suggesting at least some high molecular weight proteins play a role in ST266-mediated neuroprotection.
An approach to the permeation mechanism of learning transfer and teaching strategy in physical education based on complex network
Authors: Feng Xin , Li Jiapei , Hu Shuhui , Zhao Yi , Chen Long , Wang Nan
Published: January 2021

Learning transfer is widely present in the learning of all kinds of knowledge, skills and social norms, and is one of the important phenomena of learning, and the reasonable use of transfer is conducive to improving the learning effect of students and the quality of teaching. This study starts from the data of college students' academic performance, takes real students' academic performance as a sample, measures the relevance of courses through students' academic performance, constructs various networks of learning transfer, and studies the topology and evolution of the networks to clarify the essential laws of learning transfer and put forward suggestions for the optimization of teaching strategies. Finally, using complex network analysis to analyze and mine the data on college students' academic performance, the article quantifies the overall structure of the courses and their hidden connections in a global and dynamic manner, and discovers the inheritance relationship between the courses, the clustering characteristics and the basic pattern of learning transfer. It also provides a platform for exploring the differences in the course structure of different majors and the learning transfer of male and female students.
Prediction of implementing ISO 14031 guidelines using a multilayer perceptron neural network approach
Authors: Mansour Mohamed , Alsulamy Saleh , Dawood Shaik
Published: January 2021

The purpose of this study was to model the link between the implementation of ISO 14031 and ISO 14001. This study connects ISO 14031’s guidelines as independent variables to a dependent variable expressed by the ISO 14001 certification situation of industrial organizations based on the judgments of environmental managers in Saudi Arabia. Applying the quantitative approach using a survey with 596 responses from organizations functioning in 30 economic activities, a multi-layered neural network was trained to examine the relationship between standards and predict whether the organization is ISO 14001 certified in addition to testing the developed network on a group of collected cases. The results demonstrated the ability of the network to classify the organization’s certification status by 94.00% according to the training sample and its ability to predict 91.00% of the test sample, with an overall prediction efficiency of 91.30%. This work provides insights and adds to the environmental performance evaluation literature providing a neural network model based on ISO 14031 guidelines that can be extended to include other international standards such as ISO 9001. This study supports the merging of ISO 14001 with ISO 14031 into a binding standard.
Development and validation of a food and nutrition literacy questionnaire for Chinese school-age children
Authors: Liu Tan , Su Xiao , Li Niuniu , Sun Jing , Ma Guansheng , Zhu Wenli
Published: January 2021

Background

This study aimed to develop and validate the Food and Nutrition Literacy Questionnaire for Chinese School-age Children (FNLQ-SC).

Methods

A comprehensive literature review and qualitative study were initially performed to identify the dimensions and core components of food and nutrition literacy. A cross-sectional survey of 4359 school-age children was conducted, and junior middle school students were used to analyze the reliability and validity of the questionnaire (n = 2452). The reliability of the questionnaire was determined by internal consistency, the construct validity was assessed by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), and the content validity was assessed by the Pearson correlation coefficient.

Results

From the literature review and qualitative methods, 19 core components of the FNLQ-SC were developed, including one dimension of food and nutrition knowledge and understanding, and four skill dimensions (ability of access, selection, preparing food and healthy eating). The overall FNLQ-SC questionnaire had acceptable internal consistency (Cronbach’s α = 0.698). The EFA of skill components extracted 5 factors that were included in the conceptual framework in a slightly different model, and the cumulative contribution of variance accounted for 50.60% of the overall variance. The CFA of skill components showed an acceptable fit in general and the root mean square error of approximation (RMSEA) was 0.070 (between 0.50 to 0.80). The communality was greater than 0.20 for all components. The Pearson correlation coefficients between each dimension and the overall questionnaire ranged from 0.370 to 0.877. The average FNLQ-SC score of all 4395 participants was 61.91 ± 9.22, and the score for the knowledge and understanding dimension was higher than that for the skill dimensions. Multiple linear regression analysis indicated that not only social demographic characteristics (being a girl, being an only child, living someplace other than at school, having an urban registered permanent residence status, being from an affluent family, and being cared for by parents/grandparents with a higher education level) but also the home food environment were predictors of food and nutrition literacy in school-age children (R2= 0.226,F= 81.401,P<0.05).

Conclusion

The Food and Nutrition Literacy Questionnaire (FNLQ-SC) developed here had good reliability, and it can potentially be a useful instrument for assessing food and nutrition literacy among Chinese school-age children.
Opioid use as a potential risk factor for pancreatic cancer in the United States: An analysis of state and national level databases
Authors: Barlass Usman , Deshmukh Ameya , Beck Todd , Bishehsari Faraz
Published: January 2021

Pancreatic cancer (PC) rate is increasing in the U.S. The use of prescription and illicit opioids has continued to rise nationally in recent years as well. Opioids have been shown to have a deleterious effect on multiple types of cancer with recent data suggesting opium use as a risk factor for PC. Using national databases, we tested whether opioid usage pattern over time could explain the state and national-based variations in PC rates in the U.S. Opioid death rate (as a surrogate for prescription and illicit opioid use) was extracted from the CDCs Wonder online data through the Vital Statistics Cooperative Program. Incidence of pancreatic cancer was retrieved from the online CDCs data base gathered from the U.S. Cancer Statistics Working Group. Prevalence of obesity, tobacco and alcohol use was collected from Behavioral risk factor surveillance system. Mixed-effects regression models were used to test the association between levels of PC rate and opioid death/use rates during the years 1999–2016. A rise in PC was seen over time at the national and state levels. Similarly, the opioid death rates increased over time. Among other potential PC risk factors, only obesity prevalence showed an increase during the study period. A state’s opioid death rate at 4 years prior significantly predicted initial incidence of PC (β = 0.1848, p<0.0001) and had a significant effect on the estimated annual change in the rate of PC (β = -.0193,p<0.0001). Opioid use may be an un-identified risk factor contributing to the increasing incidence of PC in the U.S. These novel findings need to be verified by population-based studies.
Insights into elections: An ensemble bot detection coverage framework applied to the 2018 U.S. midterm elections
Authors: Schuchard Ross J. , Crooks Andrew T.
Published: January 2021

The participation of automated software agents known as social bots within online social network (OSN) engagements continues to grow at an immense pace. Choruses of concern speculate as to the impact social bots have within online communications as evidence shows that an increasing number of individuals are turning to OSNs as a primary source for information. This automated interaction proliferation within OSNs has led to the emergence of social bot detection efforts to better understand the extent and behavior of social bots. While rapidly evolving and continually improving, current social bot detection efforts are quite varied in their design and performance characteristics. Therefore, social bot research efforts that rely upon only a single bot detection source will produce very limited results. Our study expands beyond the limitation of current social bot detection research by introducing an ensemble bot detection coverage framework that harnesses the power of multiple detection sources to detect a wider variety of bots within a given OSN corpus of Twitter data. To test this framework, we focused on identifying social bot activity within OSN interactions taking place on Twitter related to the 2018 U.S. Midterm Election by using three available bot detection sources. This approach clearly showed that minimal overlap existed between the bot accounts detected within the same tweet corpus. Our findings suggest that social bot research efforts must incorporate multiple detection sources to account for the variety of social bots operating in OSNs, while incorporating improved or new detection methods to keep pace with the constant evolution of bot complexity.
Surname affinity in Santiago, Chile: A network-based approach that uncovers urban segregation
Authors: Bro Naim , Mendoza Marcelo
Published: January 2021

Based on a geocoded registry of more than four million residents of Santiago, Chile, we build two surname-based networks that reveal the city’s population structure. The first network is formed from paternal and maternal surname pairs. The second network is formed from the isonymic distances between the city’s neighborhoods. These networks uncover the city’s main ethnic groups and their spatial distribution. We match the networks to a socioeconomic index, and find that surnames of high socioeconomic status tend to cluster, be more diverse, and occupy a well-defined quarter of the city. The results are suggestive of a high degree of urban segregation in Santiago.
How the world’s collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter
Authors: Alshaabi Thayer , Arnold Michael V. , Minot Joshua R. , Adams Jane Lydia , Dewhurst David Rushing , Reagan Andrew J. , Muhamad Roby , Danforth Christopher M. , Dodds Peter Sheridan
Published: January 2021

In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucial. Fundamentally, and in the possible absence of a vaccine for 12 to 18 months, we need universal, well-documented testing for both the presence of the disease as well as confirmed recovery through serological tests for antibodies, and we need to track major socioeconomic indices. But we also need auxiliary data of all kinds, including data related to how populations are talking about the unfolding pandemic through news and stories. To in part help on the social media side, we curate a set of 2000 day-scale time series of 1- and 2-grams across 24 languages on Twitter that are most ‘important’ for April 2020 with respect to April 2019. We determine importance through our allotaxonometric instrument, rank-turbulence divergence. We make some basic observations about some of the time series, including a comparison to numbers of confirmed deaths due to COVID-19 over time. We broadly observe across all languages a peak for the language-specific word for ‘virus’ in January 2020 followed by a decline through February and then a surge through March and April. The world’s collective attention dropped away while the virus spread out from China. We host the time series on Gitlab, updating them on a daily basis while relevant. Our main intent is for other researchers to use these time series to enhance whatever analyses that may be of use during the pandemic as well as for retrospective investigations.
Impacts of land use at multiple buffer scales on seasonal water quality in a reticular river network area
Authors: Zhang Zhimin , Zhang Fei , Du Jinglong , Chen Dechao , Zhang Weiwei
Published: January 2021

The assessment and prediction of regional water quality are fundamental inputs to environmental planning and watershed ecological management. This paper explored spatiotemporal changes in the correlation of water quality parameters (WQPs) and land-use types (LUTs) in a reticular river network area. Water samples of 44 sampling sites were collected every quarter from 2016 to 2018 and evaluated for dissolved oxygen (DO), total phosphorus (TP), ammonia nitrogen (NH3-N), and permanganate index (CODMn). A redundancy analysis (RDA) and stepwise multiple linear regression (SMLR) were applied to analyze the land-use type impacts on seasonal WQPs at five buffer scales (100, 200, 500, 800, and 1000 m). The Kruskal–Wallis test results revealed significant seasonal differences in NH3-N, TP, CODMn, and DO. The area percentages of farmland, water area and built-up land in the study area were 38.96%, 22.75% and16.20%, respectively, for a combined total area percentage of nearly 80%. Our study showed that orchard land had an especially favorable influence on WQPs. Land-use type impacts on WQPs were more significant during the dry season than the wet season. The total variation explained by LUTs regarding WQPs at the 1 km buffer scale was slightly stronger than at smaller buffer scales. Built-up land had a negative effect on WQPs, but orchard and forest-grassland had a positive effect on WQPs. The effects of water area and farmland on WQPs were complex on different buffer scales. These findings are helpful for improving regional water resource management and environmental planning.
Characterization of cerebrospinal fluid (CSF) microbiota from patients with CSF shunt infection and reinfection using high throughput sequencing of 16S ribosomal RNAgenes
Authors: Whitlock Kathryn B. , Pope Christopher E. , Hodor Paul , Hoffman Lucas R. , Limbrick David L. , McDonald Patrick J. , Hauptman Jason S. , Ojemann Jeffrey G. , Simon Tamara D. ,   on behalf of the Cerebrospinal FLuId MicroBiota in Shunts Study (CLIMB) Group
Published: January 2021

Background

Nearly 20% of patients with cerebrospinal fluid (CSF) shunt infection develop reinfection. It is unclear whether reinfections are caused by an organism previously present or are independent infection events.

Objective

We used bacterial culture and high throughput sequencing (HTS) of 16S ribosomal RNA (rRNA) genes to identify bacteria present in serial CSF samples obtained from children who failed CSF shunt infection treatment. We hypothesized that organisms that persist in CSF despite treatment would be detected upon reinfection.

Design/methods

Serial CSF samples were obtained from 6 patients, 5 with 2 infections and 1 with 3 infections; the study was limited to those for which CSF samples were available from the end of infection and beginning of reinfection. Amplicons of the 16S rRNA gene V4 region were sequenced. Taxonomic assignments of V4 sequences were compared with bacterial species identified in culture.

Results

Seven infection dyads averaging 13.5 samples per infection were analyzed. A median of 8 taxa [interquartile range (IQR) 5–10] were observed in the first samples from reinfection using HTS. Conventional culture correlated with high abundance of an organism by HTS in all but 1 infection. In 6 of 7 infection dyads, organisms identified by culture at reinfection were detected by HTS of culture-negative samples at the end of the previous infection. The median Chao-Jaccard abundance-based similarity index for matched infection pairs at end of infection and beginning of reinfection was 0.57 (IQR 0.07–0.87) compared to that for unmatched pairs of 0.40 (IQR 0.10–0.60) [p = 0.46].

Conclusion(s)

HTS results were generally consistent with culture-based methods in CSF shunt infection and reinfection, and may detect organisms missed by culture at the end of infection treatment but detected by culture at reinfection. However, the CSF microbiota did not correlate more closely within patients at the end of infection and beginning of reinfection than between any two unrelated infections. We cannot reject the hypothesis that sequential infections were independent.
Three Seinura species from Japan with a description of S. shigaensis n. sp. (Tylenchomorpha: Aphelenchoididae)
Authors: Kanzaki Natsumi , Ekino Taisuke , Hamaguchi Keiko , Takeuchi-Kaneko Yuko
Published: January 2021

A preliminary survey ofSeinuraspp. was conducted in the Kyoto area, Western Japan. The survey yielded four new strains ofSeinuraspp., including two strains ofS.caverna, a strain ofS.italiensis, and a strain of an undescribed species. Molecularly, the two strains ofS.cavernawere nearly identical to the type strain but showed some minor variations, particularly in the mitochondrial cytochrome oxidase subunit I gene. The small subunit and D2-D3 large subunit sequences of the Japanese strain ofS.italiensiswere nearly identical and identical to its original description, respectively, and the difference in the small subunit was due to mis-reading of the sequences. The new species,S.shigaensisn. sp., was phylogenetically close toS.cavernaandS.persica, although these three species were clearly different phylogenetically. The new species was typologically similar or nearly identical to several otherSeinuraspp., includingS.chertkovi,S.christiei,S.italiensis,S.steineri, andS.tenuicaudata, but it can be distinguished from those species by the morphometric values. Because the new species is phylogenetically very close toS.caverna, it could be a good comparative system forS.cavernaas a potential satellite model for the predatory nematode.
Extracting and modeling geographic information from scientific articles
Authors: Acheson Elise , Purves Ross S.
Published: January 2021

Scientific articles often contain relevant geographic information such as where field work was performed or where patients were treated. Most often, this information appears in the full-text article contents as a description in natural language including place names, with no accompanying machine-readable geographic metadata. Automatically extracting this geographic information could help conduct meta-analyses, find geographical research gaps, and retrieve articles using spatial search criteria. Research on this problem is still in its infancy, with many works manually processing corpora for locations and few cross-domain studies. In this paper, we develop a fully automatic pipeline to extract and represent relevant locations from scientific articles, applying it to two varied corpora. We obtain good performance, with full pipeline precision of 0.84 for an environmental corpus, and 0.78 for a biomedical corpus. Our results can be visualized as simple global maps, allowing human annotators to both explore corpus patterns in space and triage results for downstream analysis. Future work should not only focus on improving individual pipeline components, but also be informed by user needs derived from the potential spatial analysis and exploration of such corpora.