bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of pancreatic adenocarcinoma patient risk status using alternative splicing events
Authors: Kumar Rajesh , Lathwal Anjali , Raghava Gajendra Pal 
Published: June 2021

Abstract
In literature, several mRNA, miRNA, lncRNA based biomarkers are identified by genomic analysis to stratify the patients into high and low risk groups of pancreatic adenocarcinoma (PAAD). The identified biomarkers are of limited use in terms of sensitivity and prediction ability. Thus, we aimed to identify the prognostic alternative splicing events and their related mutations in the PAAD. PAAD splicing data of 174 samples (17874 AS events in 6209 genes) and corresponding clinical information was obtained from the SpliceSeq and The Cancer Genome Atlas (TCGA), respectively. Prognostic-index based modeling was used to obtain the best predictive models for the seven AS types. However, model based on multiple spliced events genes (APP; LATS1; MRPL4; LAS1L; STARD10; PHF21A; NMRAL1) outperformed the single event models with a remarkable HR of 9.13 (p-value = 6.42e-10) as well as other existing models. Results from g:Profiler suggest that transcription factors ZF5, ER81, E2F-1/2/3, ER81, Erg, and PEA3 are most related to the prognostic spliced genes. We also identified 565 mutations across 160 spliced genes that have a strong association with the prognostic AS events. The analysis revealed that around 560 of these mutations were not reported before in context to splice event/region. Overall, we conclude that altered AS events may serve as strong indicators for overall survival in pancreatic cancer patients, and novel linkage of the known mutations to the survival-related AS events may provide a new dimension to the advancement of diagnostic and therapeutic interventions in these patients.
Network Pharmacology of Triptolide in Cancer Cells: Implications for Transcription Factor Binding
Authors: Seo Ean-Jeong , Dawood Mona , Hult Annika K. , Olsson Martin L. , Efferth Thomas 
Published: June 2021

Abstract
Background: Triptolide is an active natural product, which inhibits cell proliferation, induces cell apoptosis, suppresses tumor metastasis and improves the effect of other therapeutic treatments in several cancer cell lines by affecting multiple molecules and signaling pathways, such as caspases, heat-shock proteins, DNA damage and NF-ĸB.Purpose: We investigated the effect of triptolide towards NF-ĸB and GATA1.Methods: We used cell viability assay, compare and cluster analyses of microarray-based mRNA transcriptome-wide expression data, gene promoter binding motif analysis, molecular docking, Ingenuity pathway analysis, NF-ĸB reporter cell assay, and electrophoretic mobility shift assay (EMSA) of GATA1. Results: Triptolide inhibited the growth of drug-sensitive (CCRF-CEM, U87.MG) and drug-resistant cell lines (CEM/ADR5000, U87.MGΔEGFR). Hierarchical cluster analysis showed six major clusters in dendrogram. The sensitive and resistant cell lines were statistically significant (p = 0.65 × 10-2) distributed. The binding motifs of NF-κB (Rel) and of GATA1 protein were significantly enriched in regions of 25 kb upstream promoter of all genes. IPA showed the networks, biological functions, and canonical pathways influencing the activity of triptolide towards tumor cells. Interestingly, upstream analysis for the 40 genes identified by compare analysis revealed ZFPM1 (friend of GATA protein 1) as top transcription regulator. However, we did not observe any effect of triptolide to the binding of GATA1 in vitro. We confirmed that triptolide inhibited NF-κB activity, and it strongly bound to the pharmacophores of IκB kinase β and NF-κB in silico. Conclusion: Triptolide showed promising inhibitory effect toward NF-κB, making it a potential candidate for targeting NF-κB.
Listening to ultrasound from plants reveals xylem vessel anatomy. Ultrasound characterization of plant vessels.
Authors: Dutta Satadal , Kaiser Elias , Matamoros Priscila Malcolm , Steeneken Peter , Verbiest Gerard 
Published: June 2021

Abstract
Although it is well known that plants emit ultrasound bursts under drought stress, the exact origin of the acoustic waveform of these pulses has remained elusive. Here we present evidence for a correlation between the ultrasound spectrum of these pulses and the dimensions of the plant’s xylem vessels. Using a model that relates the vibrational excitations of the vessels to their geometric and viscoelastic properties, we develop a methodology to extract the internal xylem vessel dimensions from recorded ultrasound waveforms. We apply the method to ultrasound pulses from drying shoots of three vascular dicot plant species, and validate it by comparison with destructive measurements via microscopy. Our method demonstrates the potential for continuous monitoring of the vascular anatomy of plants. The ultrasonic, non-invasive characterization of internal vessel dimensions can lead to breakthroughs in speed and accuracy in plant phenotyping and disease detection in agriculture.
Disinfection Effect of Hexadecyl Pyridinium Chloride on SARS-CoV-2 in vitro.
Authors: Chen Keda , Ma Feike , Wang Ying , Zhuang Xinyi , Zhang Xuning , Mao Haiyan , Zhang Yanjun 
Published: June 2021

Abstract
The novel coronavirus (COVID-19 or 2019-nCoV) is a respiratory virus that can exist in the mouth and saliva of patients and spreads through aerosol dispersion. Therefore, stomatological hospitals and departments have become high-infection-risk environments. Accordingly, the search for oral disinfectants that can effectively inactivate the virus has become a highly active area of research. Hexadecyl pyridinium chloride, povidone-iodine, and other common oral disinfectants are the natural primary choices for stomatological hospitals. Therefore, this study investigated the inhibitory effect of hexadecyl pyridinium chloride on SARS-CoV-2 in vitro. Vero cells infected with SARS-CoV-2 were used to determine disinfection effect; the CCK-8 method was used to determine cytotoxicity; and viral load was determined by real-time PCR. The results showed that hexadecyl pyridinium chloride has no obvious cytotoxic effect on Vero cells in the concentration range 0.0125–0.05 mg/mL. The in vitro experiments showed that hexadecyl pyridinium chloride significantly inhibits the virus at concentrations of 0.1 mg/mL or above at 2 min of action. Thus, the results provide experimental support for the use of hexadecyl pyridinium chloride in stomatological hospitals.
Investigation of The Relationships Between Image Spatial Resolution And Landscape Metrics
Authors: Sertel Elif , Topaloglu Raziye Hale , Varol Beril , Aksu Asli Gul , Bahsi Kubra 
Published: June 2021

Abstract
Land Use and Land Cover (LULC) maps derived from satellite images are a significant source of geo-information to better understand the current status of landscapes, to analyze the landscape changes, and to develop sustainable decisions for landscape and urban planning. Since the spectral and spatial resolution of satellite images directly impact the LULC classes to be identified and the accuracy of the classification, these will also affect the values of calculated landscape metrics. This research aims to propose the most appropriate functions and features to obtain highly accurate thematically extensive LULC classification results from multi-resolution satellite images and to investigate how the change in spatial resolution of satellite images would affect the landscape metrics values and landscape pattern analysis Sentinel-2, SPOT-7, Pleaides, and Worldview-4 images with respective 10 m, 1.5 m, 0.5 m, and 0.3 m spatial resolution were classified using Geographic Object-Based Image Analysis techniques to create multi-scale LULC maps with the overall classification accuracy values of 66.05%, 85.00%, 91.79%, and 95.71%, respectively. Patch Density, Total Area, Largest Patch Index, Shape Index, Euclidian Nearest Neighbor distance, Aggregation Index, and Shannon's Diversity Index metrics were found to be most appropriate metrics to analyze the impact of spatial resolution on landscape metrics calculations considering the ability of these metrics to capture the spatial details, spatial arrangement, spatial distribution and complexity of shapes of landscape and classes.Landscape metrics results obtained from different LULC maps were compared to analyze the effects of image spatial resolution on different landscape metrics.
Field Verification of Low-Level Biochar Applications as Effective Ameliorants to Mitigate Cadmium Accumulation into Brassica Campestris L from Polluted Farmland Soil
Authors: Zhang Youchi , Hou Yanwei , Fan Jiajun , Lin Shanna , Reid Brian J. , Coulon Frédéric , Cai Chao 
Published: June 2021

Abstract
Farmland soils in China have been reported to be diffusely contaminated, Cd has been recognized as a significant contributor to this issue and biochars have been reported to be effective in mitigating soil Cd pollution. However, previous studies have shown contradictory outcomes. Furthermore, in general, laboratory experiments and unrealistically large amounts of biochar (>10 t/ha) have been used. In this study, three biochars: rice straw biochar (RS), pig manure biochar (PM) and rice husk biochar (RH) were produced from readily available farm residues and characterized. These were used in a field experiment, at low applications rates of 1.8 and 3.6 t/ha, with rape (Brassica campestris L.). Batch adsorption experiments indicated Cd adsorption in the order RS biochar > PM biochar > RH biochar. Field experiment indicated biochar amendments to slightly changes in soil pH and CEC; yet led to considerable and significant decreases in extractable Cd concentrations (reductions of: 43%-51% (PM), 29%-35% (RS) and 17%-19% (RH)). Reduced extractable Cd correlated with lower Cd concentrations in rape plants. PM and RS biochars were the most effective in decreasing Cd phytoaccumulation into edible parts of rape (>68% reduction). It is highlighted that biochars were produced using a pyrolysis unit with an output of 20 ton/yr. Thus, assuming a working application rate of 2 ton/ha, the pyrolysis unit could service 10 ha/yr. While at a modest scale, this research demonstrates the genuine reality of biochar-based remediation solutions to contribute to the mitigation of diffuse Cd contamination in some of China’s impaired farmland.
A New Design of Custom Optimized Cnn-Lstm Assists to Detect Network Anomaly Using Categorical Data
Authors: R Kanmani , Malar A.Christy Jeba , V Roopa , D Ranjani , R Suganya 
Published: June 2021

Abstract
For traditional intrusion detection model, the system effectiveness is fully based on training dataset and feature selection. During feature selection, it needs more labour charge and trusted mainly on expert’s knowledge. Moreover, the training dataset contains more imbalanced data which in terms model tends to be biased. Here, an automatic approach is introduced to correct deficiency in the system. In this paper, the author proposes novel network anomaly detection (NID) build using categorical data. A model has to be designed with modified form of deep neural network primarily utilized for detecting anomaly within the network. Custom CNN-LSTM with Harris Hawks Optimization (named as custom optimized CNN-LSTM) is designed as a new classifier majorly used to detect the anomaly from word cloud to distinguish the data with effective performance. The experimental result shows that the proposed method achieves a promising output for network anomaly detection.
Who Makes It All The Way? Participants Vs. Decliners, And Completers Vs. Drop-Outs, In A 6-Month Exercise Trial During Cancer Treatment. Results From The Phys-Can RCT
Authors: Strandberg Emelie , Bean Christopher , Vassbakk-Svindland Karianne , Brooke Hannah L , Sjövall Katarina , Börjeson Sussanne , Berntsen Sveinung , Nordin Karin , Demmelmaier Ingrid 
Published: June 2021

Abstract
Purpose: To compare sociodemographic, health- and exercise-related characteristics of participants vs decliners, and completers vs drop-outs, in an exercise intervention during cancer treatment. Methods: Patients with newly diagnosed breast, prostate or colorectal cancer were invited to participate in a 6-month exercise intervention. Questionnaire, medical record and physical testing data were analyzed for between-group differences using independent t-tests and Chi2-tests. Results: Trial participants (n=577) were younger (59±12 yrs vs 64±11 yrs, p<.001), included more women (80% vs 75%, p=.012) and were scheduled for chemotherapy treatment (54% vs 34%, p<.001) compared to decliners (n=1391). A greater proportion had university education (60% vs 40%, p<.001), reported more anxiety (5.5±4.4 vs 4.3±3.7, p<.001), cancer-related fatigue, exercise self-efficacy (49.9±16.2 vs 45.0±20.1, p<.001), higher outcome expectations and less kinesiophobia (23.5±5.1 vs 24.5±5.0, p=.001) compared to decliners who completed baseline questionnaires (n=436). A greater proportion of participants were classified as ‘not physically active’, however, within the group who participated, more intervention completers were classified as ‘physically active’ at baseline compared to drop-outs. Completers also reported less kinesiophobia than drop-outs. Conclusion: Participants in a comprehensive exercise oncology trial differ in several sociodemographic, health and exercise-related aspects from those declining to participate, while differences between completers and drop-outs are less pronounced. A lack of health-enhancing exercise habits at baseline may be an incentive for accepting participation, while having such habits at baseline may increase the chances of completing exercise intervention trials. The findings provide useful insight for translating research results and planning future exercise interventions for cancer survivors.
Delta Ruled First Order Iterative Deep Neural Learning for Sybil and Wormhole Attacks Detection in Healthcare Wireless Sensor Network
Authors: A John Clement Sunder , KP K.P. Sampoornam , R R.Vinodkumar 
Published: June 2021

Abstract
Detection and isolation of Sybil and wormhole attack nodes in healthcare WSN is a significant problem to be resolved. Few research works have been designed to identify Sybil and wormhole attack nodes in the network. However, the detection performance of Sybil and wormhole attack nodes was not effectual as the false alarm rate was higher. In order to overcome such limitations, Delta Ruled First Order Iterative Deep Learning based Intrusion Detection (DRFOIDL-ID) Technique is proposed. The DRFOIDL-ID Technique includes two main phase namely attack detection and isolation. The DRFOIDL-ID Technique constructs Delta Ruled First Order Iterative Deep Learning in attack detection phase with aim of detecting the occurrence of Sybil and wormhole attacks in healthcare WSN. After detecting the attack nodes, DRFOIDL-ID Technique carried outs isolation process with the objective of increasing the routing performance. During the isolation phase, DRFOIDL-ID Technique keep always the identified Sybil and wormhole attack nodes through transmitting the isolation messages to all sensor nodes in healthcare WSN. Hence, DRFOIDL-ID Technique improves the routing performance with lower packet loss rate. The DRFOIDL-ID Technique conducts the simulation process using factors such as attack detection rate, attack detection time, false alarm rate and packet loss rate with respect to a diverse number of sensor nodes and data packets. The simulation result proves that the DRFOIDL-ID Technique is able to improve the attack detection rate and also reduces the attack detection time as compared to state-of-the-art works.
Multiple Classification Algorithm Based on Graph Convolutional Neural Network for Intrusion Detection
Authors: Liu Fulai , Hu Zhongyi , Zhang Aiyi , Du Ruiyan , Qin Dongbao , Xu Jialiang 
Published: June 2021

Abstract
In order to improve the recognition performance of intrusion detection, a graph convolutional neural network for multiple classification intrusion detection is proposed, named as GCNID. Firstly, the detection data are preprocessed by numerical and normalized, so that the disadvantage effect of numerical differences among various features can be reduced. Then, the adjacency matrix for intrusion data in GCIND is constructed by the k-nearest neighbor method, which utilizes the Euclide distance between different features as evaluation criterion. Besides, the adjacency matrix and the modified detection data are set as the input of GCNID framework. Furthermore, the neighbors information of each detection data are added into itself by the graph convolutional layer, such that more effective intrusion features can be extracted by GCNID. What s more, the parameters in the proposed method are optimized by back propagation until the network convergence. Finally, the Softmax logistic regression model is used to classify the types of intrusion. Simulation results show that the proposed method can not only improve the detection accuracy, but also classify the unknown attack types. The performance shows that the GCNID has a good ability of accuracy and generalization.
Extent, Type and Reasons for Adaptation and Modification When Scaling-Up an Effective Physical Activity Program: Physical Activity 4 Everyone (PA4E1)
Authors: Mclaughlin Matthew , Campbell Elizabeth , Sutherland Rachel , McKenzie Tom , Davies Lynda , Wiggers John , Wolfenden Luke 
Published: June 2021

Abstract
Background

Few studies have described the extent, type and reasons for making changes to a program prior to and during its delivery using a consistent taxonomy. Physical Activity 4 Everyone (PA4E1) is a secondary school physical activity program that was scaled-up for delivery to a greater number of schools. We aimed to describe the extent, type and reasons for changes to the PA4E1 program (the evidence-based physical activity practices, implementation support strategies and evaluation methods) made before its delivery at scale (adaptations) and during its delivery in a scale-up trial (modifications).
Methods

The Framework for Reporting Adaptations and Modifications-Enhanced (FRAME) was used to describe adaptations (planned and made prior to the scale-up trial) and modifications (made during the conduct of the trial). A list of adaptations was generated from a comparison of the efficacy and scale-up trials via published PA4E1 protocols, trial registrations and information provided by trial investigators. Monthly trial team meetings tracked and coded modifications in ‘real-time’ during the conduct of the scale-up trial. The extent, type and reasons for both adaptations and modifications were summarized descriptively.
Results

In total, 20 adaptations and 20 modifications were identified, these were to physical activity practices (n = 8; n = 3), implementation support strategies (n = 6; n = 16) and evaluation methods (n = 6, n = 1), respectively. Few adaptations were ‘fidelity inconsistent’ (n = 2), made ‘unsystematically’ (n = 1) and proposed to have a ‘negative’ impact on the effectiveness of the program (n = 1). Reasons for the adaptations varied. Of the 20 modifications, all were ‘fidelity consistent’ and the majority were made ‘proactively’ (n = 12), though most were ‘unsystematic’ (n = 18). Fifteen of the modifications were thought to have a ‘positive’ impact on program effectiveness. The most common decision-maker in the modification process was the ‘program manager’ (n = 17). The main reason for modification was the ‘available resources’ (n = 14) of the PA4E1 Implementation Team. For both adaptations and modifications respectively, the most common goal was to ‘improve fit with recipients’ (n = 8; n = 7).
Conclusions

A considerable number of adaptations and modifications were made for scale-up that could have important impacts on intervention effects and are important to the interpretation of trial findings.
Trial Registration

Australia New Zealand Clinical Trial Registry: ACTRN12617000681358
The Space-evolution Frame as Alternative to Space-time
Authors: Du Xiaonan 
Published: June 2021

Abstract
As an alternative to Minkowski spacetime frame, this paper propose a four-dimensional Euclidean space that combines three spatial dimension with proper time instead of time. We call it space-evolution, in which proper time is interpreted as evolutionary position, time is considered as world line length and is absolute. Space-evolution frame provide a new perspective for our understanding of time, space and special relativity. The new frame is self-consistent without losing compatibility to special relativity, the Lorentz transform and its predictions could be derived geometrically by simple coordinate rotation
Supporting Medical Students To Support Peers: A Qualitative Interview Study
Authors: Graves Jane , Flynn Eleanor , Woodward-Kron Robyn , Hu Wendy C.Y. 
Published: June 2021

Abstract
BackgroundStudents may be the first to recognise and respond to psychological distress in other students. Peer support could overcome medical student reluctance to seek help despite their high rates of mental ill-health. Yet, despite the adoption of peer support programs, there is little evidence of impact on students. Peer support programs may assume that medical students accept and view peer support positively. We explored these assumptions by asking students about their experiences and views on peer support. MethodsQualitative semi-structured interviews exploring peer support experiences and views on peer support were conducted with ten medical students at two contrasting medical schools. Informed by a constructivist stance, interview transcripts underwent thematic analysis. ResultsThree groups of themes were identified: participants’ experiences of peer support encounters, concerns about providing support, and views on students’ roles in peer support. Participants readily recalled signs of peer distress. Encounters were ad hoc, informal, and occurred within relationships based on friendship or by being co-located in the same classes or placements. Concerns about initiating and offering support included lack of expertise, maintaining confidentiality, stigma from a mental health diagnosis, and unclear role boundaries, with implications for acceptance of student roles in peer support. Conclusions: Our study emphasised the centrality of social relationships in enabling or discouraging peer support. Relationships developed during medical studies may anticipate the collegial relationships between medical professionals. Nevertheless, only some students are willing to undertake peer support roles. We suggest different strategies for promoting informal peer support that can be offered by any student, to those promoting formal support roles for selected students. Future research focusing on the impact for both the students who receive, and on the students who provide peer support is called for.