bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional Connectivity Disturbances of the Locus Coeruleus in Chronic Insomnia Disorder
Authors: Li Chunlong , Ma Xiaofen , Liu Yuexia , Yang Ning , Lan Zhihong , Huang Shumei , Wu Yunfan , Jiang Guihua 
Published: January 2022

Abstract
In recent years, people have gained a profound understanding of chronic insomnia disorder (CID), but the pathophysiological mechanism of CID is still unclear. There is some evidence that the locus coeruleus (LC) is involved in the regulation of wakefulness in CID, but there have been few studies using brain functional imaging. The purpose of this study was to evaluate the resting-state functional connectivity (FC) between the LC and other brain voxels in CID and whether these abnormal FC are involved in the regulation of wakefulness. A total of 49 patients with chronic insomnia disorder and 47 healthy controls (HC) matched for gender, age, and education were examined with rs-fMRI in this study. The LC was selected as the region of interest, and then seed-based analysis was conducted on the LC and other voxels to obtain the brain regions with abnormal FC. The correlation between the FC value of the abnormal connection area and the clinical scale score was analyzed. Compared with the HC, the FC between the LC and right precuneus, right posterior cingulate cortex, left middle temporal gyrus, left calcarine, and right superior orbitofrontal cortex was significantly enhanced (p < 0.05, FDR correction), and the functional connectivity signal value between the locus coeruleus and left middle temporal gyrus was positively correlated with the Self-Rating Depression Scale (p = 0.021).The abnormal FC between the LC and multiple brain regions may contribute to a better understanding of the neurobiological mechanism of CID.
A novel MALDI-TOF mass spectrometry sample preparation strategy for improved proteomic biotyping of clinically significant Mycobacteria
Authors: Pillay Melendhran , Myende Siyanda , Krishna Suresh Babu Naidu , Green Ezekiel , Govender Patrick 
Published: January 2022

Abstract
A precise routine method is essential for the rapid identification of pathogenic mycobacterial species to support our publicly maintained health care management systems to efficiently treat and control and emerging tuberculosis pandemic that is threatening populations of global third world economies. To date, many conventional and more recently developed molecular genotyping methods are employed to this end. However, current technologies are limited in respect in that they are time consuming nature and dependent on highly skilled technical personnel expertise. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been recently reported as reliable, economical, and highly efficient method for both bacteria, yeast and to a limited extent for mycobacterial strain identification. Unlike other microbes, a major impediment exists in the efficient extraction of cellular proteins from mycobacteria, especially due to their complex cell wall associated lipid structure. In this study, the manufacturer prescribed mycobacterial sample preparation method for MALDI TOF MS is modified and optimised to generate more efficient cellular protein extraction for efficient biotyping. In this regard, the newly developed sample preparation method is inclusive of a glass bead cellular disruption/delipidation followed by a chloroform-methanol solvent extraction event. Interestingly, the data from this locally based study shows that newly developed method generates unique and highly reproducible mass spectra profiles. A new and independent main spectral profile reference library (CMEFA-MSP) representing clinically relevant American Type Culture Collection (ATCC) mycobacterial strains and clinical isolates was established and subsequently used to unequivocally identify 110 (n = 100) blind-coded clinical mycobacterial isolates to the species level that displayed log score values of ≥2.3. This strongly suggests that MALDI-TOF MS when used in conjunction with the CMEFA sample preparation protocol has potential as a simple and cost-effective alternative for the unambiguous identification of clinically important mycobacteria.
Performance Evaluation of IRI-Plas 2017 model with Ionosonde Data Measurements of Ionospheric Parameters
Authors: Lake Endeshaw , Seyoum Alene 
Published: January 2022

Abstract
This study presents the performance evaluation of International Reference Ionosphere extended to the plasmasphere (IRI-Plas 2017) model from the Addis Ababa ionosonde station, Ethiopia ionospheric parameters measurement with geographic latitude 9.00o N and longitude 38.70o E; geomagnetic latitude 0.16, geomagnetic longitude 110.44) in selected days of the year 2014. During comparison, hourly and day-to-day variability of ionospheric parameters of the electron density profile, peak electron density (NmF2), peak height (hmF2) and critical frequency (foF2) measurements are consider. In the evaluation of the IRI-Plas 2017 model with the ionosonde data, the percentage deviation and the correlation coefficient (R) is used as the measure of the performance of the IRI-Plas 2017 model. The overall results, show that the IRI-Plas 2017 model mostly overestimates in most altitudes and hours of electron density measurements. The IRI-Plas 2017 model has a good agreement with the ionosonde electron density measurement from 100 km to 200 km altitude and mostly during in between 0:00-06:00 UT and 12:00-18:00 UT hours, while the model biases in other altitudes and hours with overestimate or underestimate in the ionosonde electron density measurements. The IRI-Plas 2017 model has a good correlation during after midnight and around midday hours with about ±2 percentage deviation from the ionosonde electron density measurement. The model has high percentage deviation value of electron density measurements mostly in between altitudes from 200 km to 450 km and during early nighttime and before midnight hours. The IRI-Plas 2017 model measurements of the NmF2, hmF2 and foF2 mostly underestimates from the ionosonde data during the night-time (18:00 UT- 06:00 UT) and overestimates during day-time (06:00 UT-18:00 UT). The IRI-Plas 2017 model measurement of the foF2 values are in a good agreement with the ionosonde result than in hmF2 and NmF2 and the model measurement of the NmF2 values are closer than hmF2.
Spatial and Temporal Variability of Key Bio-Temperature Indicators and their Effects on Vegetation Dynamics in the Great Lakes Region of Central Asia
Authors: Gao Xuan , Zhao Dongsheng , Liu Lei 
Published: January 2022

Abstract

Dryland ecosystems are fragile to climate change due to harsh environmental condition. Climate change affects vegetation growth primarily by altering some key bio-temperature thresholds. Key bio-temperatures are closely related to vegetation growth, and slight changes could produce substantial effects on ecosystem structure and function. Therefore, this study selected the number of days with daily mean temperature above 0 °C (DT0), 5 °C (DT5), 10 °C (DT10), 20 °C (DT20), the start of growing season (SGS), the end of growing season (EGS), and the length of growing season (LGS) as bio-temperature indicators to analyze the response of vegetation dynamics to climate change in the Great Lakes Region of Central Asia (GLRCA) for the period 1982–2014. On the regional scale, DT0, DT5, DT10, and DT20 exhibited an overall increasing trend. Spatially, most of the study area showed that the negative correlation between DT0, DT5, DT10, DT20 with annual NDVI increased with increasing bio-temperature thresholds. Especially, more than 88.3% of the study area showed a negative correlation between annual NDVI and DT20, as increased DT20 exacerbated ecosystem drought. Moreover, SGS exhibited insignificantly advanced trend, and EGS experienced a significantly delayed trend. The overall extending trend in LGS was mainly attributed to the delayed EGS. Besides, our study revealed that about 54.7% of the study area showed a negative correlation between annual NDVI and LGS, especially in the north, indicating a negative effect of climate warming on vegetation growth in the drylands. The results of this study will help assess the stability of vegetation to climate variability, and predict the response of vegetation to future climate change in the GLRCA.
Fat Mass and Obesity–Associated Protein Promotes Liver Steatosis By Targeting PPARα
Authors: Wei Xiaohui , Zhang Jielei , Tang Min , Wang Xuejiao , Fan Nengguang , Peng Yongde 
Published: January 2022

Abstract
Background: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. The fat mass and obesity–associated protein (FTO) has been shown to be involved in obesity; however, its role in NAFLD and the underlying molecular mechanisms remain largely unknown. Methods: FTO expression was first examined in the livers of patients with NAFLD and animal and cellular models of NAFLD by real-time PCR and Western blotting. Next, its role in lipid accumulation in hepatocytes was assessed both in vitro and in vivo via gene overexpression and knockdown studies. Results: FTO expression was obviously elevated in the livers of mice and humans with hepatic steatosis, probably due to its decreased ubiquitination. FTO overexpression in HepG2 cells induced triglyceride accumulation, whereas FTO knockdown exerted an opposing effect. Consistent with the findings of in vitro studies, adeno-associated viruses 8 (AAV8)-mediated FTO overexpression in the liver promoted hepatic steatosis in C57BL/6J mice. Mechanistically, FTO inhibited the mRNA of peroxisome proliferator-activated receptor α (PPARα) in hepatocytes. Activation of PPARα by the its agonist GW7647 reversed lipid accumulation in hepatocytes induced by FTO overexpression.Conclusions: Overall, FTO expression is increased in NAFLD, and it promotes hepatic steatosis by targeting PPARα.
Application of Deep Learning Technology in Glioma for Healthcare Applications
Authors: Hoang Doan T. 
Published: January 2022

Abstract
Glioma is the most common primary brain tumor, and it's extremely dangerous for the patient's health. Magnetic Resonance Imaging (MRI) based glioma segmentation is an important tool for doctors to use when examining, analyzing, and diagnosing glioma's outward appearance both for the indoor and outdoor patients. Among other methods, deep learning-based glioma segmentation is the most widely used in literature. Therefore, in this paper, we have proposed glioma segmentation methods which is primarily based on deep learning more specifically convolution neural networks. A DM-DA-based cascade method for glioma segmentation based on 2DResUnet is proposed to address the problem of insufficient 3D spatial information acquisition in 2D full convolutional networks and the memory consumption problem of 3D full convolutional networks. Use of multiple-scale fusion mechanisms, DenseBlock, Attention, and multi-scale convolutional networks to segment gliomas at different stages and fixed region sampling to reduce the model's three-dimensionality in the Unet model using the glioma image's multi-sequence information, the convolutional network can better segment the tumor by using less memory. Use the BraTS18 data set for local five-fold cross-validation, and use the BraTS17 data set for official online evaluation. The evaluation results show that the average Dice Score of the edema, core and enhancement areas of the glioma segmentation results on the BraTS17 validation set by DM-DA-Unet achieves higher performance. The average sensitivity is also high, which is close to the best model segmentation effect on the BraTS17 validation set, and can accurately segment gliomas.
Comparisons of Watershed Delineation of River Network Representation and Morphometric Analysis in Karnaphuli River Basin, Chittagong, Bangladesh: A study with Different Digital Elevation Model (DEM)
Authors: Roy Sujit Kumar , Chowdhury Md. Arif , Talukdar Swapan , Billah Md Mostaim , Banik Anik Chandra , Mallick Javed 
Published: January 2022

Abstract
The present study aimed to delineate robust watershed boundary and extract its morphometric parameters in Karnaphuli watershed, Bangladesh using different types of digital elevation models (DEMs). Two DEMs, such as Shuttle Radar Topographic Mission (SRTM) and the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), were utilized to delineate watershed boundary and evaluate several morphometric characteristics. From the findings, it is revealed that there is a visual difference between the data sets as ASTER has a larger watershed area than SRTM. Also, regarding stream order, there are actually 1 to 6 orders of stream, so there are so many small, medium and main channels of the river, where the drainage density for SRTM (spatial resolution: 30m) and ASTER (spatial resolution: 30m) is 0.52 km/km2 and 0.51 km/km2. The bifurcation ratio ranges from 1.94 and 2.45 for SRTM and ASTER, respectively, representing the influence of geological structure as well as suffering more structural disturbances. The form factor denotes the study area's elongated shape. The entire dimension of the stream and the extent of the watershed imply that the mean annual rainfall discharge is moderate. The watershed has rather high denudation rates, according to the basin relief. The watershed's drainage density is low, demonstrating that infiltration is more important. This study may help policymakers to take decisions on the Karnaphuli River on conservation of the river stream and flow path, which will ultimately enrich the river ecology and other vegetation cover in Chittagong, Bangladesh.
The Conformational Impact of Eliminating the C-Terminal Peptide Extension from IMPDH1-604 Retinal Isoform Via Experimental and Molecular Dynamics Simulation Approaches
Authors: Ebli Parisa Elyasi , Yazdanparast Razieh , Gharaghani Sajjad 
Published: January 2022

Abstract
Retinitis Pigmentosa (RP), blindness with acquired and hereditary origins, includes 2 percent of global cases of blindness. RP10, a gene involved in autosomal dominant form of the RP, encodes for isoform 1 of inosine 5'-monophosphate dehydrogenase (IMPDH1). IMPDH1, the rate-limiting enzyme in the purine nucleotide de novo synthesis pathway, retinal isoforms are identified as the root cause of observing diverse phenotypes of IMPDH1 mutations in other tissue cells in comparison to the retinal photoreceptors. Considering previously reported significant varied kinetic activity among retinal isoforms, the central focus of the current article is prediction of possible structural explanations. The recombinant 604-isoform lacking carboxyl terminus peptide fragment has been used in proteolytic digestion with α-Chymotrypsin as a means of detecting intermolecular interactions. Dimer models of wild type 604-isoform were subjected to Molecular dynamics simulation. Our results indicated that a 604-isoform lacking C-terminal peptide tends to have a more accessible surface and thus a more rapid proteolysis. Our computational data predict a possible spontaneous inhibition due to formation of a novel helix in GTP binding site in the engineered protein.
A Decision Support System for Preclinical Assessment of Nanomaterials in Medical Products: The REFINE DSS
Authors: Zabeo Alex , Rosada Fabio , Pizzol Lisa , Caputo Fanny , Borgos Sven Even , Parot Jeremie , Geertsma Robert E , Pouw Joost Jacob , Vandebriel Rob J , Moreno Oihane Ibarrola , Hristozov Danail 
Published: January 2022

Abstract
The application of nanomaterials in medicine has led to novel pharmaceuticals and medical devices that have demonstrated a strong potential for increasing the efficacy/performance and safety of therapeutic and diagnostic procedures to address a wide range of diseases. However, the successful translation of these technologies from their inception (proof-of-concept) to clinical practice has been challenged by substantial gaps in the scientific and technical capacity of R&D companies, especially SMEs, to keep up with the ever-evolving regulatory expectations in the emerging area of nanomedicine. To address these challenges, the EU Horizon 2020 project REFINE has developed a Decision Support System (DSS) to support developers of nanotechnology-enabled health products in bringing their products to the clinic. The REFINE DSS has been developed to support experts, innovators and regulators in the implementation of Intelligent Testing Strategies (ITS) for efficient preclinical assessment of nanotechnology-enabled health products. The DSS applies logical rules provided by REFINE experts which generate prioritized lists of assays to be performed (i.e. ITSs) for physicochemical characterisation and for immunotoxicological endpoints. The DSS has been tested against several case studies and was validated by internal project experts as well as external ones.
Contrast Enhanced Ultrasound Imaging with Nanobubbles: Unique Second-Wave Phenomenon
Authors: Chen Chuan , Perera Reshani , Kolios Michael C. , Wijkstra Hessel , Exner Agata A. , Mischi Massimo , Turco Simona 
Published: January 2022

Abstract
Investigation of nanobubble (NB) pharmacokinetics in contrast-enhanced ultrasound (CEUS) at the pixel level shows a unique phenomenon where the first pass of the contrast agent bolus is accompanied by a second wave. This effect has not been previously observed in CEUS with microbubbles. The objective of this study was to investigate this second-wave phenomenon and its potential clinical applications. Seven mice with a total of fourteen subcutaneously-implanted tumors were included in the experiments. After injecting a bolus of NBs, the NB-CEUS images were acquired to record the time-intensity curves (TICs) at each pixel. These TICs are fitted to a pharmacokinetic model which we designed to describe the observed second-wave phenomenon. The estimated model parameters are presented as parametric maps to visualize the characteristics of tumor lesions. Histological analysis was also conducted in one mouse to compare the molecular features of tumor tissue with the obtained parametric maps. The second-wave phenomenon is evidently shown in a series of pixel-based TICs extracted from either tumor or tissues. The value of two model parameters, the ratio of the peak intensities of the second over the first wave, and the decay rate of the wash-out process are significantly different between malignant and tissue (Kolmogorov–Smirnov statistic D > 0.25). The occurrence of a second wave is a unique phenomenon that we have observed in NB-CEUS imaging of both mouse tumor and tissue. As the characteristics of the second wave are different between tumor and tissue, this phenomenon has the potential to support the diagnosis of cancerous lesions.
WITHDRAWN: Artificial Intelligence-enabled English Translation System Using Unsupervised Learning for Wireless Network
Authors: Ali Shah Rukh 
Published: January 2022

Abstract
At present, high-quality English-Chinese parallel corpus is currently in a stage of scarcity. How to use existing monolingual corpus data for unsupervised training has become an important research direction of English-Chinese machine translation. This work proposes an unsupervised English neural machine translation system and deploys it in a wireless network to perform unsupervised English translation. The specific work content of this work is as follows: 1) To alleviate the issue of low accuracy for unsupervised English-Chinese dictionary induction methods, an unsupervised English-Chinese dictionary induction method based on translation model is proposed. First, an unsupervised English-Chinese statistical machine translation model is built, and with this model, a bilingual dictionary is summarized through statistical word alignment technology. After that, the bilingual dictionary summarized by the translation model is combined with the language model, unsupervised translation model is initialized, unsupervised English-Chinese neural machine translation model is optimized through the back translation method. 2) To alleviate the problem that the unsupervised translation model built based on the denoising autoencoder is not natural and accurate, this paper implements a pre-trained English-Chinese language model based on the masked sequence-to-sequence (MASS) method. First, use monolingual corpus combined with random masking, and train the Transformer together to obtain a language model.
Changing Characteristics and Influencing Factors of the Bacterial and Fungal Communities in the Litter of Casuarina Equisetifolia Forests of Different Ages in Hainan Island
Authors: Xu Zhixia , Zuo Linzhi , Zhang Yaqian , Huang Rui , Li Lei 
Published: January 2022

Abstract
Casuarina equisetifolia, an important pioneer tree with resistance to typhoon and stress tolerance, is mainly cultivated in the coastal areas of tropical and subtropical zones. Casuarina equisetifolia forests have high litter accumulation rates and slow litter decomposition rates. The accumulation of litter may affect the secondary regeneration of Casuarina equisetifolia, and the decomposition of litter is largely controlled by microorganisms such as bacteria and fungi. While the characteristics of the microbial diversity in the litter of Casuarina equisetifolia forests have not yet been resolved. In order to explore the microbial distribution characteristics and community dynamic changes in the litter of a Casuarina equisetifolia forest, we used Illumina Miseq high-throughput sequencing technology to analyze the endophytic and exophytic bacterial and fungal communities of Casuarina equisetifolia forests of three ages (young forest, half-mature forest, and mature forest). The results showed that the young and half-mature forests had the highest bacterial diversity, and the half-mature and mature forests had the highest fungal diversity. The community structure and endophytic and exophytic communities of different forest ages were also different. Exophytic bacteria of the phylum Proteobacteria had a gradually decreasing abundance with stand age, while endophytic bacteria of the phylum Actinomycetes had a gradually increasing abundance with stand age; in the half-mature forest, the abundance of nitrogen-fixing microorganisms, such as the genera Rhizobium, Bradyrhizobium, and Actinoplanes, were increased relative to all of the other forest age types. The fungal community structure was different than the bacterial structure. Specifically, the fungal communities of both the young and mature forests were dominated by the class Dothideomycetes of the phylum Ascomycota, while phylum Basidiomycota was dominant in the half-mature forest. The correlation with the physicochemical properties of the litter showed that exophytic bacteria were related to the organic carbon and water content of the litter, endophytic bacteria were related to litter pH and nitrogen content, and fungi were correlated tonitrogen and phosphorus contents. In summary, the community structures of bacteria and fungi in the half-mature forest were more uniform, which was beneficial to the growth of Casuarina equisetifolia plants, and the changes observed in the physical and chemical factors of litter were one of the key factors driving microbial community structure.