bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silencing LncRNA SCAMP1 inhibits cell proliferation, induces G0/G1 arrest and apoptosis in hepatocellular carcinoma
Authors: Ma Xiaochen , Sun Xiangyang , Li Caixia , Zhang Kai , Xie Yang 
Published: October 2021

Abstract
Background: Long noncoding RNA secretory carrier membrane protein 1 (SCAMP1) has been recently reported to be an oncogene in glioma and ovarian cancer. However, little is known about the clinical significance and functional role of SCAMP1 in hepatocellular carcinoma (HCC).Methods: The expression of SCAMP1 was determined in tissue samples and cell lines using quantitative reverse transcription PCR (qRT-PCR). The clinical significance of SCAMP1 in HCC was evaluated using chi-squared test, Kaplan-Meier survival, as well as univariate and multivariate analysis. Cell proliferation, cell cycle distribution and apoptosis were evaluated using CCK-8 assay, colony formation assay, Flow cytometry analysis. Related protein expression levels were measured by western blot analysis.Results: We found SCAMP1 expression levels were remarkably up-regulated in HCC tissues compared to that in matched adjacent tissues. Increased SCAMP1 expression was significantly correlated with large tumor size, advanced TNM stage and poor survival prognosis in HCC. Knockdown of SCAMP1 significantly inhibited cell proliferation, induced G0/G1 phase arrest and apoptosis in HepG2 and SNU-182 cells. More importantly, knockdown of SCAMP1 downregulated the protein levels of CDK4, Cyclin D1 and Bcl-2, while upregulated the protein levels of p21, p53 and Bax.Conclusions: In summary, our study clarified a positive correlation of the SCAMP1 levels with the HCC cell proliferation.
Statistical Distortion of Supervised Learning Predictions in Optical Microscopy Induced by Image Compression
Authors: Pomarico Enrico , Schmidt Cédric , Chays Florian , Nguyen David , Planchette Arielle , Tissot Audrey , Roux Adrien , Pagès Stéphane , Batti Laura , Clausen Christoph , Lasser Theo , Radenovic Aleksandra , Sanguinetti Bruno , Extermann Jérôme 
Published: October 2021

Abstract
The growth of data throughput in optical microscopy has triggered the extensive use of supervised learning (SL) models on compressed datasets for automated analysis. Investigating the effects of image compression on SL predictions is therefore pivotal to assess their reliability, especially for clinical use.We quantify the statistical distortions induced by compression through the comparison of predictions on compressed data to the raw predictive uncertainty, numerically estimated from the raw noise statistics measured via sensor calibration. Predictions on cell segmentation parameters are altered by up to 15% and more than 10 standard deviations after 16-to-8 bits pixel depth reduction and 10:1 JPEG compression. JPEG formats with higher compression ratios show significantly larger distortions. Interestingly, a recent metrologically accurate algorithm, offering up to 10:1 compression ratio, provides a prediction spread equivalent to that stemming from raw noise. The method described here allows to set a lower bound to the predictive uncertainty of a SL task and can be generalized to determine the statistical distortions originated from a variety of processing pipelines in AI-assisted fields.
A Survey of Crowd Counting CNN-based
Authors: gao hui , deng miaolei , zhao wenjun , zhang dexian 
Published: October 2021

Abstract
Benefiting from the powerful feature representation ability of deep learning, Convolutional Neural Network (CNN) provides a better solution to estimate accurately the number of people in a crowded scene, but it still faces many problems that need to be solved urgently. It is one of the key and difficult points in the field to reduce the complexity of the network and to improve the real-time performance of the network, so as to improve the accuracy of crowd counting. Firstly, this paper introduces the research background and application of crowd counting. Secondly, it focuses on the commonly used counting model, loss function, and dataset and evaluation method. Then compare the performance structure, advantages and disadvantages of different algorithms horizontally on several published datasets. Finally, it summarizes the shortcomings of the existing crowd counting, put forward to the future research direction of crowd counting.
Unlocking Urban Animal Response to Reduced Human Activity during COVID-19 Lockdown
Authors: Basak Sayantani M. , Mahony Declan T. O` , Lesiak Maciej , Basak Arpan Kumar , Ziółkowska Elżbieta , Kaim Dominik , Hossain Md Sarwar , Wierzbowska Izabela A. 
Published: October 2021

Abstract
The interrelations between human activity and animal populations are of increasing interest due to the emergence of the novel COVID-19 across the world. Anthropogenic impacts of the pandemic on animals in urban-suburban environments, at this stage, are largely unknown. In this study, temporal and spatial aspects of urban animal response to the COVID-19 lockdown were assessed using animal-vehicle collisions (AVC) data. We used AVC and traffic data over two six-month periods in 2019 and 2020 (January to June) from southern Poland, which included lockdown months. Our analysis of 1741 AVC incidents involving 21 animal species revealed that COVID-19 related lockdown did not significantly impact AVC rates even though traffic levels were reduced, suggesting that animals increased utilisation of urban-suburban interfaces in response to reduced human activity. Given the high incidence and diversity of species involved in AVC in this study, we emphasise the importance of data integrity and mitigation measures to minimise this human wildlife conflict.
Spatio-temporal prediction of the population size at Tehran urban areas using BirnbaumSaunders Markov random fields
Authors: Khaledi Majid Jafari , Bourbour Sara , Safarkhanloo Helia 
Published: October 2021

Abstract
For implementing an intelligent urban management, it is necessary and inevitable to know the population size in different areas of Tehran city and identify how they change over time. Population and housing census data can determine the spatio-temporal distribution of the people and how it evolves. However, census will not be implemented across the country in 2021, like a previous manner, due to issues related to the coronavirus pandemic and its prevalence. From this perspective, the prediction of the population size is significant in different regions of Tehran for the year 2021. This paper focuses on developing a statistical learning model for predicting the population growth rate of Tehran urban areas. To be more specific, since the growth rates data are spatially correlated, skewed to the right, and positive, a Birnbaum- Saunders Markov random field (BSMRF) is proposed. We adopt a Bayesian framework for the parameter estimation and spatial prediction and use Markov chain Monte Carlo methods to sample from the posterior distribution. Then, the results are compared with the traditional models.
Evaluation of Skeletal Muscle Activity During Foot Training Exercises Using Positron Emission Tomography
Authors: Kanayama Tomoyuki , Nakase Junsuke , Mochizuki Takafumi , Asai Kazuki , Yoshimizu Rikuto , Kimura Mitsuhiro , Kinuya Seigo , Tsuchiya Hiroyuki 
Published: October 2021

Abstract
The foot exercises “rock-paper-scissors” and “towel gathering” are widely used in patients with lower limb disorders; however, there are no detailed reports on muscle activity during such training. We quantitatively evaluated the difference in skeletal muscle activity between the two exercises using positron emission tomography. Eight university student athletes were included. Four participants each were assigned to the foot rock-paper-scissors and towel gathering groups. Participants in each group underwent continuous training for 15 min. They received an intravenous injection of 18F-fluorodeoxyglucose and retrained for 15 min, following which they rested for 45 min. Regions of interest were defined in 25 muscles. The standardized uptake value (SUV) in the trained limb was compared with that in the non-trained control limb. SUVs increased in four skeletal muscles (tibialis anterior, peroneus brevis, extensor hallucis brevis, and abductor hallucis) in the rock-paper-scissors group, and in four muscles (flexor digitorum longus, extensor hallucis brevis, extensor digitorum brevis, and quadratus plantae) in the towel gathering group. Thus, foot rock-paper-scissors and towel gathering affected skeletal muscles related to the medial longitudinal arch and toe grip strength, respectively. Given that the two exercises target different skeletal muscles, they should be taught and implemented according to their respective purposes.
Serial and Parallel Convolutional Neural Network Designs for NFDM Signals
Authors: Zhang Wen Qi , Chan Terence , V. Shahraam Afshar 
Published: October 2021

Abstract
Two conceptual convolutional neural network designs are proposed for directly decoding NFDM signals with the consideration of hardware implementation. A serial network is designed for small network size suitable for small user applications and a parallel network is designed for speed suitable for places such as data centres. In the numerical demonstrations, the serial design only occupies 0.5 MB of memory space while the parallel design occupies 128 MB of memory but allow parallel computing. Both network designs were trained with simulated data and able to reach more than 99.9% accuracy.
Stack-ZDPD: A Novel Encoding Scheme for Mass Spectrometry Data
Authors: Wang Jinyin , Lu Miaoshan , Wang Ruiming , An Shaowei , Xie Cong , Yu Changbin 
Published: October 2021

Abstract
As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient, while most research on compression algorithms rarely provides flexible random file reading scheme. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on Airdpro, for file conversion and the Java-API Aird SDK, for data parsing.
Effect of β-Resin and Oxygen Functional Group of Binderless Coke on Mechanical Properties of High-Density Carbon Blocks According to Molding Pressure
Authors: Park Seungjoo , Lee Seon Ho , Lee Song Mi , Jung Doo-Hwan 
Published: October 2021

Abstract
High-density carbon blocks have excellent mechanical, thermal, and electrical properties. In particular, these blocks are applied in various fields while maintaining excellent physical properties even in harsh environments. In this study, binderless coke manufactured under certain conditions was used to form green bodies (GBs) under various pressure conditions of 50 to 250 MPa, and the bodies were carbonized to form a high-density carbon block (CB). Then, the effect of the β-resin and oxygen functional groups of binderless coke on the mechanical properties of the high-density carbon block according to molding pressure was considered. When molding at a pressure of under 200 MPa, the ratio of O and C (O/C) has a greater effect, and the larger the O/C, the higher the mechanical properties. On the other hand, when molding at a high pressure of 250 MPa, the β-resin content has a greater effect and steadily increases when the β-resin content is low and when the mechanical properties are sufficiently reduced. In particular, in the case of CB-N7A3–250, which has the highest β-resin content of 3.7 wt%, the density was 1.79 g/cm3, the flexural strength was 106 MPa, and the shore hardness was 99 HSD.
Leveraging Data Science Tools and Algorithms to Unveil New Insights on Historical Research Data: A Case of Insect Morphometrics
Authors: Salifu Daisy , Ibrahim Eric Ali , Tonnang Henri 
Published: October 2021

Abstract
The move towards open access and re-use of scientific research data is rapidly being embraced by the research community as best practice. Many research institutions are adopting a set of global data policy guiding principles to make data Findable, Accessible, Interoperable and Reusable (FAIR). This study is product of good research data stewardship of open access and re-use. We explored the use and application of advanced data science with machine learning tools and algorithms on historical data of insect morphometrics that were previously analyzed using conventional statistical methods, principal component analysis and canonical variate analysis. Herein, we assess the predictive performance of four machine learning classifiers; K-nearest neighbor (KNN), random forest (RF), support vector machine (the linear, polynomial and radial kernel SVMs) and artificial neural networks (ANNs) on the historical data of fruit fly morphometrics. KNN and RF performed poorly with overall model accuracy lower than “no-information rate” (NIR) (p-value>0.1). The SVM models had a predictive accuracy of >95% and Kappa >0.78 with accuracy significantly higher than NIR, p<0,001; while ANN model had a predictive accuracy of 96% and Kappa of 0.83 with accuracy also greater than NIR. We conclude that SVM and ANN models could be used to discriminate fruit fly species based on wing vein and tibia length measurements or any other morphologically similar pest taxa. These algorithms could be used as candidates for developing an integrated and smart application software for insect discrimination and identification.
Quantitative Evaluation of Human Lens Epithelial Cell Viability and Cytolysis by Distilled Water Ex Vivo
Authors: Zhang Wen-Wen , Zhang Rong-Pei , Liu Ya-Jun , He Zi-Fang , Zhang Si , Xie Zheng-Gao 
Published: October 2021

Abstract
Purpose: To investigate the role of distilled water (DW) in isolated human lens epithelial cells (LECs) viability and lysis ex vivo.Methods: After immersion in DW or balanced salt solution (BSS) for 1-, 2-, and 3-minutes, respectively, the cell viability of LECs was quantitatively evaluated. In addition, the capsule samples soaked in DW or BSS for 1-, 2-, and 3-minutes were combined with rinse for 1 minute to analyze the difference of LECs shedding percentage in each subgroup. The histopathological changes of the samples after treating were observed.Results: The percentage of LECs shed in DW immersion combined with rinse was significantly higher than in DW immersion alone (p all <0.001). In the subgroup soaked in DW for 3 minutes, the death number, mortality, and the percentage of cell shedding of LECs was the most (p all <0.001). The histopathological changes showed that the cell destruction in the DW subgroup for 1-, 2-, and 3-minutes, and the transmission electron microscope results showed that the cells were partially detached from the capsule in the DW 3 minutes subgroup.Conclusions: Soaking in the DW can cause LECs death, and DW immersion combined with rinse was an effective method to remove LECs. The histopathology changes of treated DW suggested cellular necrosis was one type of LECs death mechanism.
Implication of High Variance in Germplasm Characteristics
Authors: Yu Ju-Kyung , Chang Sungyul , Han Gyung Deok , Kim Seong-Hoon , Ahn Jinhyun , Park Jieun , Kim Yooha , Kim Jaeyoung , Chung Yong Suk 
Published: October 2021

Abstract
The beauty of conserving germplasm is the securement of genetic resources with numerous important traits, which could be utilized whenever they need to be incorporated into current cultivars. However, it would not be as useful as expected if proper information was not given to breeders and researchers. In this study, we demonstrated that there is a large variation, both among and within germplasm, using a low-cost image-based phenotyping method; this could be valuable for improving gene bank screening systems and for crop breeding. Using the image analyses of 507 accessions of buckwheat, we identified a wide range of variations per trait between germplasm accessions and within an accession. Since this implies a similarity with other important agronomic traits, we suggest that the variance of the presented traits should be checked and provided for better germplasm enhancement.
What’s the Cut-Point?: A Systematic Investigation of Tau PET Thresholding Methods
Authors: Weigand Alexandra June , Maass Anne , Eglit Graham , Bondi Mark 
Published: October 2021

Abstract
Background: Tau positron emission tomography (PET) is increasing in popularity for biomarker characterization of Alzheimer’s disease (AD), and recent frameworks rely on tau PET cut-points to stage individuals along the AD continuum. Given the lack of standardization in tau PET thresholding methods, this study sought to systematically canvass and characterize existing studies that have derived tau PET cut-points and then directly assess different methods of tau PET thresholding in terms of their concurrent validity.Methods: First, a literature search was conducted in PubMed to identify studies of AD and related clinical phenotypes that used the Flortaucipir (AV-1451) tau PET tracer to derive a binary cut-point for tau positivity. Of 540 articles screened and 47 full-texts reviewed, 23 cohort studies met inclusion criteria with a total of 6,536 participants. In a 2x2x2 design that systematically varied region (temporal meta-ROI and entorhinal cortex), analytic method (receiver-operating characteristics and 2 standard deviations above comparison group), and criterion/comparison variable (amyloid-beta positivity or cognitive diagnosis), a sample from the Alzheimer’s Disease Neuroimaging Initiative yielded eight different tau PET cut-points. Results: For the systematic review, notable variability in sample characteristics, preprocessing methods, region of interest, and analytic approach were observed, which were accompanied by discrepancy in proposed tau PET cut points. The empirical follow-up indicated the cut-point derived based on 2 standard deviations above a cognitively unimpaired group in the temporal meta-ROI best differentiated tau positive and negative groups on cerebrospinal fluid phosphorylated tau, Mini-Mental State Examination score, and delayed memory performance. Conclusions: Given the impact of discrepant thresholds on tau positivity rates, biomarker staging, and eligibility for future clinical treatment trials, recommendations are offered to standardize cut-point derivations as additional tau PET tracers are developed and implemented in AD studies.
Cyclic Peptide D7 Promotes Osteogenesis and Inhibits Osteoclastogenesis by Regulating Redox Balance of Bone Remodeling
Authors: Cui Zichen , Feng Changgong , Chen Jiazheng , Wang Yi , Feng Dianjie , Cheng Yifan , Li Ziqing , Sun Shui 
Published: October 2021

Abstract
BackgroundMilitary training usually causes excessive physical burden to the bones and joints of soldiers, which in turn disturbs the balance of bone homeostasis and eventually induces bone metabolic diseases. In our previous studies, a cyclic peptide D7 in was characterized through phage display technology from the peptide phage display library (Ph.D.‑C7C) and was proven to enhance the adhesion, expansion, and proliferation of bone marrow mesenchymal stem cells (BMSCs) on the biomaterial scaffold. However, we found that cyclic peptide D7 also has a certain affinity for mouse calvarial osteoblast precursor cells (OPCs) and bone marrow-derived monocytes/macrophages (BMMs). To investigate whether D7 can protect physiological bone remodeling and maintain bone homeostasis, we elucidated the mechanisms by which D7 promotes osteogenesis and inhibits osteoclastogenesis. MethodsThe affinity of D7 peptide towards calvarial OPCs and BMMs was investigated using fluorescence cytochemistry. The roles of D7 in osteogenesis and osteoclastogenesis by regulating redox balance was confirmed by cell counting kit-8, special stain assays (alkaline phosphatase stain, alizarin red stain and tartrate‐resistant alkaline phosphatase stain), fluorescence cytochemistry, western blotting, quantitative real-time polymerase chain reaction. ResultsThe results demonstrated that D7 promoted the osteogenesis of calvarial OPCs by upregulating the expression of osteogenic differentiation factors. In contrast, D7 inhibited osteoclast differentiation and resorption by downregulating the expression of osteoclast phenotype marker. We further identified that these phenomenons may be due to the suppressive effect of D7 on reactive oxygen species production and the enhancing effect on antioxidant expression in both OPCs and BMMs, thereby regulating the redox balance of bone remodeling.Conclusions﻿Cyclic peptide D7 could maintain bone homeostasis by regulating redox balance and provide a potential approach to strengthen the skeletal fitness of soldiers and prevent the occurrence of bone metabolic diseases.
The role of lncRNAKCNQ1OT1/miR-301b/Tcf7 Axis in Cardiac Hypertrophy
Authors: e mingyao , Ren Feifei , Liu Guohong , Yu Yanhua , Li Haiyan , Shen Chao , Sha Chunyan 
Published: October 2021

Abstract
Cardiac hypertrophy, acting as a pathologic progress of chronic hypertension and coronary disease. Increasing evidence indicates that lncRNA potassium voltage-gated channel subfamily q member 1 overlapping transcript 1 (KCNQ1OT1) may led to MI. Recent studies showed, miR-301b level was evidently decreased in heart failure patients. To explore the regulate effect of lncRNAKCNQ1OT1 and miR-301b in cardiac hypertrophy, gain-and-lose function assays were tested. Notably, lncRNAKCNQ1OT1 overexpression causes a significant result as cardiac hypertrophy. Furthermore, lncRNAKCNQ1OT1 sponge microRNA-301b. The results showed that miR-301b exhibited lower expression in cardiac hypertrophy model, indicating that it may exert anti-hypertrophic role. Furthermore, the BNP and β-MHC expression increased, as well as cardiomyocyte surface area, with Ang II treatment, while the effect was repealed by miR-301b. Moreover, the protein expression of Tcf7 was down-regulated or up-regulated by miR-301b or AMO-301b. As displayed by luciferase reporter assay, miR-301b binds to 3’UTR of Tcf7. Briefly, we aimed to elucidate a down-regulate role of miR-301b in cardiac hypertrophy, as to provide potential therapeutic strategies.