bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel putative drugs and key initiating genes for neurodegenerative disease determined using network‐based genetic integrative analysis
Authors: Mortezaei Zahra , Cazier Jean‐Baptiste , Mehrabi Ali Ashraf , Cheng Chao , Masoudi‐Nejad Ali 
Published: October 2018

AbstractUnderstanding the genetic causes of neurodegenerative disease (ND) can be useful for their prevention and treatment. Among the genetic variations responsible for ND, heritable germline variants have been discovered in genome‐wide association studies (GWAS), and nonheritable somatic mutations have been discovered in sequencing projects. Distinguishing the important initiating genes in ND and comparing the importance of heritable and nonheritable genetic variants for treating ND are important challenges. In this study, we analysed GWAS results, somatic mutations and drug targets of ND from large databanks by performing directed network‐based analysis considering a randomised network hypothesis testing procedure. A disease‐associated biological network was created in the context of the functional interactome, and the nonrandom topological characteristics of directed‐edge classes were interpreted. Hierarchical network analysis indicated that drug targets tend to lie upstream of somatic mutations and germline variants. Furthermore, using directed path length information and biological explanations, we provide information on the most important genes in these created node classes and their associated drugs. Finally, we identified nine germline variants overlapping with drug targets for ND, seven somatic mutations close to drug targets from the hierarchical network analysis and six crucial genes in controlling other genes from the network analysis. Based on these findings, some drugs have been proposed for treating ND via drug repurposing. Our results provide new insights into the therapeutic actionability of GWAS results and somatic mutations for ND. The interesting properties of each node class and the existing relationships between them can broaden our knowledge of ND.
Comprehensive analysis of microRNA‐messenger RNA regulatory network in gemcitabine‐resistant bladder cancer cells
Authors: Zhang Su , Chang Yong‐Yan , Gong Yu‐Wen , Gao Yan‐Jun , Guo Qi , Wang Yu‐Han , Zhao You‐Li , Wang Zhi‐Ping 
Published: October 2018

AbstractChemotherapy is still a standard treatment of unresectable bladder cancer or distant metastases. The chemotherapy resistance always occurs after a period of treatment indicating poor prognosis. The current study aimed to explore the molecular mechanism of chemoresistance in bladder cancer cells. The gene expression profiles of GSE77883, including three untreated T24 cells samples and three gemcitabine‐resistant T24 cells samples, was downloaded from Gene Expression Omnibus database. The screening of differentially expressed genes (DEGs), gene function analysis, and interaction prediction between microRNAs (miRNAs) and DEGs were performed by R software. The protein‐protein interaction (PPI) and miRNA‐DEGs networks were constructed and visualized by Cytoscape software. Then, the small molecules, with potential synergistic or antagonistic effects to gemcitabine resistance, were identified using the Connectivity Map database. Finally, gemcitabine‐resistant T24 cell line was established and key genes were validated by quantitative real‐time polymerase chain reaction (qRT‐PCR). In total, 536 upregulated and 513 downregulated genes were screened and mainly enriched in oxidative stress response and signaling pathways related to extracellular matrix–receptor interaction and focal adhesion. PPI network showed interleukin 6, tumor necrosis factor, kinesin family member 11, and BUB1 mitotic checkpoint serine/threonine kinase B were key genes. The miRNA‐DEGs regulatory networks included 18 miRNAs and 185 DEGs, including miR‐182‐5p, miR‐590‐3p, miR‐320a and serum‐ and glucocorticoid‐regulated kinase 1 (SGK1). Then, the related key genes and miRNAs were confirmed by qRT‐PCR. Furthermore, 81 small molecules with antagonistic or synergistic effect to GEM were screened. We have investigated the molecular mechanisms driving GEM‐resistance in bladder cancer cells that would contribute to the development of chemotherapy for advanced bladder cancer.
Diffusion tensor imaging of white matter in patients with prediabetes by trace‐based spatial statistics
Authors: Liang Minjie , Cai Xiangyi , Tang Yi , Yang Xiao‐ling , Fang Jin , Li Jie , Zhang ShuiHua , Zhou Quan 
Published: October 2018

BackgroundPrediabetes is an intermediate state in which blood glucose is higher than normal but does not meet the diagnostic criteria for diabetes. Diffusion tensor imaging (DTI) is an MRI method that can sensitively detect microscopic lesions in the white matter of the brain, but most previous DTI studies only focused on patients with diabetes, and little is known about prediabetes.PurposeTo investigate the changes in the microstructure of brain white matter in prediabetes patients using DTI and trace‐based spatial statistics (TBSS).Study TypeProspective.PopulationSixty subjects (30 patients with prediabetes and 30 healthy volunteers) were enrolled.Field Strength/Sequence3.0T/DTI‐MRI sequence with single‐shot echo‐planar imaging sequence (SE‐EPI).AssessmentDTI data were collected and analyzed using the TBSS method in the FMRIB software library.Statistical TestsDTI using a two‐sample t‐test. Pearson correlation analysis was performed on DTI values and neuropsychology scale results (mini‐mental state examination [MMSE], Montreal cognitive assessment [MoCA], self‐rating anxiety scale [SAS], and self‐rating depression scale [SDS])ResultsCompared with the control group, the fractional anisotropy (FA) values in the right part of the corpus callosum body (bCC) (P = 0.035), the right superior longitudinal fasciculus (SLF.R) (P = 0.047), and the left superior longitudinal fasciculus (SLF.L) in the prediabetic group were reduced (P = 0.040).Data ConclusionDTI as a noninvasive technique can assess early changes in the white matter microarchitecture of patients with prediabetes.Level of Evidence: 2Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2019;49:1105–1112.
Improvement of radiographer commenting accuracy of the appendicular skeleton following a short course in plain radiography image interpretation: A pilot study
Authors: Williams Imelda , Baird Marilyn , Pearce Beverley , Schneider Michal 
Published: October 2018

AbstractIntroductionRadiographers are at times required to provide preliminary information on plain radiography when significant findings are identified. The aim of the study was to evaluate the effectiveness of two short training modules to improve the accuracy of image interpretation of the appendicular skeleton amongst a group of radiographers.MethodsEight radiographers volunteered to participate in the study. All undertook a pre‐test and, following delivery of course materials, an immediate post‐test for two consecutive modules. A retention test was undertaken 6 months later. Sensitivity (Sn), specificity (Sp) and accuracy (Acc) scores were evaluated against the “Gold Standard” radiologists’ reports. Paired‐samples t‐tests were carried out to compare image interpretation scores between the start of module one to the end of module two, and between the end of module 2 and 6 months later. Summary receiver operating characteristics (SROC) scores on each of the participants’ module two post‐test study results were undertaken.ResultsSignificant improvements in scores were achieved between the mean (SD) scores of module 1 pre‐test (77.5 (±3.9)) and the module 2 post‐test (83.6 (±3.2) (P =0.022)). Sn, Sp and Acc scores increased from the start of module 1 pre‐test to the end of module 2 post‐test (Sn: 82.28–86.25%; Sp: 75.29–84.66%; Acc: 81.68–85.97%). The retention test revealed a non‐significant reduction in mean scores (80.0 (±5.1)) when compared to post‐test module 2 (83.6 (±3.2) (P =0.184)). SROC revealed an area under the curve of 0.90.ConclusionParticipants achieved significant improvements in commenting accuracy on plain radiography of the appendicular skeleton after completion of the two modules. However, continuous application and ongoing professional development is essential in order to maintain and develop the skills acquired.
Soil mapping and delineation of management zones in the Western Ghats of coastal India
Authors: Verma Ram Ratan , Manjunath Begur Lakshminarasimha , Singh Narendra Pratap , Kumar Anil , Asolkar Trupti , Chavan Virendra , Srivastava Tapendra Kumar , Singh Pushpa 
Published: October 2018

AbstractThe pace of land degradation has almost doubled across the Western Ghats of India, one of the world's ‘hotspots’ for biodiversity, owing to soil erosion, mining, and rampant urbanization. The arising nutrient depletion leading to land degradation is thus a serious threat to agricultural sustainability in this region. Delineation of spatial soil property maps for nutrient management is an effective strategy for precision agriculture. The present investigation was carried out in North Goa District in Western Ghats, a seldom researched domain in the Indian coastal region. The study involved spatial array analysis of soil properties of 383 georeferenced soil samples and used fuzzy k‐means clustering for delineation of management zones (MZs). Soils were found highly acidic with low available N, P, and medium exchangeable K with a widespread Zn, Cu, and Fe deficiency and sporadic salinity. Soil properties exhibited low to high levels of skewness except for soil pH and Mn. Correlations between soil pH and K, Zn, and Mn, between EC and Fe, between soil organic carbon (SOC) and N, P, K, Cu, and Mn was positive and significant (P = 0.01). Geostatistical analysis revealed varied distribution pattern for soil properties with Gaussian (pH, P, and Cu), spherical (EC), stable (SOC), hole effect (N), K‐Bessel (K and Fe), exponential (Zn), and circular (Mn) as best fit semivariogram models with weak and strong spatial dependence. The spatial variability was mapped, and two MZs were delineated. The developed maps will be crucial in site‐specific nutrient management for agricultural and ecological sustainability in the Western Ghats of India.
Nitrogen addition can improve seedling establishment of N‐sensitive species in degraded saline soils
Authors: Zhang Hongxiang , Xiang Yang , Irving Louis J. , Li Qiang , Zhou Daowei 
Published: October 2018

AbstractSalinization is an important cause of land degradation globally, and these soils are usually nutrient deficient, which inhibits plant establishment and growth. Medicago sativa and Leymus chinensis are important legume and grass forage species, respectively, in China and are frequently used in pasture establishment. We aimed to test whether nitrogen (N) addition can increase the salt tolerance of these two glycophytes and whether the two species inhibit each other at the germination and seedling emergence stages. M. sativa and L. chinensis seeds were germinated separately or together in 0‐, 100‐, and 200‐mM NaCl solutions with supplemental 0‐, 20‐, or 40‐mM N solutions. N addition increased germination percentage and rate, shoot length, and seedling N concentration under moderate NaCl conditions for L. chinensis but had no effect on Na+ concentrations. Conversely, N addition stimulated Na+ uptake in M. sativa, but it had little effect on germination parameters, with salt suppressing N uptake. The presence of M. sativa stimulated L. chinensis germination percentage in mixed treatments. Our results suggest that proper N application may aid establishment of N‐sensitive species L. chinensis in grass–legume mixtures in degraded saline soils, through both direct influence as a nutritional and/or osmotic resource and indirect effect by increasing salt sequestration by M. sativa. N application had little effect on establishment of the N‐fixing species M. sativa.
Laser threshold and cell damage mechanism for intravascular photoacoustic imaging
Authors: Sowers Timothy , VanderLaan Don , Karpiouk Andrei , Donnelly Eleanor M. , Smith Ethan , Emelianov Stanislav 
Published: October 2018

ObjectivesIntravascular photoacoustic (IVPA) imaging is being developed to image atherosclerotic plaques, a leading cause of morbidity and mortality in the United States. However, the safety of this imaging modality, which requires repeated irradiation with short laser pulses, has not yet been investigated. This study has two objectives. First, determine in vitro the limit of cumulative fluence that can be applied to cells before death at IVPA relevant wavelengths. Second, evaluate if high single pulse fluences are a potential cause of cell death during IVPA imaging.Materials and MethodsExperiments were conducted using endothelial cells, macrophages, and smooth muscle cells. The cumulative fluence experiments were conducted at 1064 and 1197 nm, using a high pulse repetition frequency laser. Cells were irradiated with a wide range of cumulative fluences and evaluated for cell death. The thresholds for death were compared to the maximum expected clinical cumulative fluence. To evaluate the effect of single pulse fluences, cells were irradiated at 1064, 1210, and 1720 nm. Light was delivered at a range of pulse energies to emulate the fluences that cells would be exposed to during clinical IVPA imaging.ResultsAt 1064 nm, all three cell types remained viable at cumulative fluences above the maximum expected clinical cumulative fluence, which is calculated based on common IVPA imaging protocols. At 1197 nm, cells were viable near or just below the maximum expected clinical cumulative fluence, with some cell type to cell type variation. All three cell types remained viable after irradiation with high single pulse fluences at all three wavelengths.ConclusionThe cumulative fluence experiments indicate that safety considerations are likely to put constraints on the amount of irradiation that can be used in IVPA imaging protocols. However, this study also indicates that it will be possible to use IVPA imaging safely, since cumulative fluences could be reduced by as much as two orders of magnitude below the maximum expected clinical cumulative fluence by varying the imaging protocol, albeit at the expense of image quality. The single pulse fluence experiments indicate that cell death from single pulse fluence is not likely during IVPA imaging. Thus, future studies should focus on heat accumulation as the likely mechanism of tissue damage. Lasers Surg. Med. 51:466–474, 2019. © 2018 Wiley Periodicals, Inc.
Impact of colonoscopic screening in Familial Colorectal Cancer Type X
Authors: Hatfield Elizabeth , Green Jane S. , Woods Michael O. , Warden Geoff , Parfrey Patrick S. 
Published: October 2018

AbstractBackgroundHereditary Non‐Polyposis Colorectal cancer is caused by Lynch Syndrome (LS; an autosomal dominant condition) or by Familial Colorectal Cancer Type‐X (FCCTX; a condition of high family risk that fulfills Amsterdam criteria). The lifetime risk of developing colorectal cancer (CRC) in FCCTX family members is high and CRC occurs later than in LS.MethodsTo determine the impact of primary prevention colonoscopic screening in asymptomatic first‐degree relatives of incident CRC cases in 20 families with FCCTX, we compared cancer incidence and survival in 79 males and 83 females, assumed to be at 50% risk of inheriting a genetic CRC susceptibility factor, who entered screening to an unscreened control group from the families, matched for age at entry into screening and for sex.ResultsIn males, median age at entry into screening was 44.8 years, median follow‐up 12.4 years, 12% developed CRC, and 46% died after 30 years of follow‐up. Compared to the unscreened group, relative risk of CRC was 0.27 (95% confidence intervals (CI) 0.10–0.71). In screened females, comparable results were 44.5 years at entry, 11.2 years of follow‐up, 7.1% developed CRC, and 7.2% died after 30 years of follow‐up. The relative risk of CRC compared to the unscreened group was 0.19 (95% CI 0.07–0.48).ConclusionPrimary prevention screening colonoscopy in asymptomatic family members significantly decreased the risk of CRC in FCCTX.
Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography?
Authors: Sarwar Tabinda , Ramamohanarao Kotagiri , Zalesky Andrew 
Published: October 2018

PurposeHuman connectomics necessitates high‐throughput, whole‐brain reconstruction of multiple white matter fiber bundles. Scaling up tractography to meet these high‐throughput demands yields new fiber tracking challenges, such as minimizing spurious connections and controlling for gyral biases. The aim of this study is to determine which of the two broadest classes of tractography algorithms—deterministic or probabilistic—is most suited to mapping connectomes.MethodsThis study develops numerical connectome phantoms that feature realistic network topologies and that are matched to the fiber complexity of in vivo diffusion MRI (dMRI) data. The phantoms are utilized to evaluate the performance of tensor‐based and multi‐fiber implementations of deterministic and probabilistic tractography.ResultsFor connectome phantoms that are representative of the fiber complexity of in vivo dMRI, multi‐fiber deterministic tractography yields the most accurate connectome reconstructions (F‐measure = 0.35). Probabilistic algorithms are hampered by an abundance of false‐positive connections, leading to lower specificity (F = 0.19). While omitting connections with the fewest number of streamlines (thresholding) improves the performance of probabilistic algorithms (F = 0.38), multi‐fiber deterministic tractography remains optimal when it benefits from thresholding (F = 0.42).ConclusionsMulti‐fiber deterministic tractography is well suited to connectome mapping, while connectome thresholding is essential when using probabilistic algorithms.
On the accuracy and precision of PLANET for multiparametric MRI using phase‐cycled bSSFP imaging
Authors: Shcherbakova Yulia , van den Berg Cornelis A. T. , Moonen Chrit T. W. , Bartels Lambertus W. 
Published: October 2018

AbstractPurposeIn this work we demonstrate how sequence parameter settings influence the accuracy and precision in T1, T2, and off‐resonance maps obtained with the PLANET method for a single‐component signal model. In addition, the performance of the method for the particular case of a two‐component relaxation model for white matter tissue was assessed.MethodsNumerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single‐component model, as well as for a two‐component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated.ResultsBy making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single‐component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin‐related signal component in white matter, an underestimation of approximately 30% in T1 and T2 was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates.ConclusionFor a single‐component signal model there is a broad “sweet spot” of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single‐component PLANET reconstruction results in systematic errors in the parameter estimates as expected.
Lesion segmentation for MR spectroscopic imaging using the convolution difference method
Authors: Maudsley Andrew A. 
Published: October 2018

PurposeDelineation of lesion boundaries from volumetric MRSI metabolite ratio maps using a method that accounts for the spatial response function of the acquisition and variable spectral quality and is robust to signal heterogeneity within the lesion.MethodsA novel method for lesion segmentation, termed convolution difference, has been developed that is robust to signal heterogeneity within the lesion and to differences in the spatial response function. Procedures are described for processing metabolite ratio maps and to exclude regions of inadequate spectral quality. This method was evaluated using computer simulations, and the results were compared with an iterative thresholding technique that determines an optimal amplitude threshold, and with the use of a fixed amplitude threshold. These methods were evaluated for segmentation of volumetric MRSI studies of gliomas using maps of the choline to N–acetylaspartate ratio, and a qualitative comparison of lesion volumes carried out.ResultsSimulation studies indicated improved performance for the convolution difference method when applied to ratio maps. Variations in tumor volume were observed for the in vivo studies between the convolution difference and the iterative thresholding methods; however, visual analysis indicates that both showed improved accuracy in comparison to using a fixed amplitude threshold.ConclusionThis study reinforces previous reports indicating that the use of fixed threshold values for segmentation of maps with broad spatial response functions can result in errors in lesion volume definition. A novel segmentation method, termed the convolution difference, has been introduced and demonstrated to be robust for segmentation of volumetric MRSI metabolite data.
Design and psychometric testing of instruments to measure qualified intensive care nurses’ attitudes toward obese intensive care patients
Authors: Robstad Nastasja , Siebler Frank , Söderhamn Ulrika , Westergren Thomas , Fegran Liv 
Published: October 2018

ABSTRACTThe purpose of this pilot study was to design and test research instruments to measure qualified intensive care nurses’ implicit and explicit attitudes and behavioral intentions toward obese intensive care patients. In previous studies researchers have demonstrated that some health professionals hold negative attitudes toward obese patients; however, little is known about qualified intensive care nurses’ attitudes toward these patients. Our cross‐sectional pilot study involved Implicit Association Tests, the Anti‐fat Attitude questionnaire, an explicit bias scale comprising ratings of explicit beliefs and feelings, assessment of behavioral intentions based on vignettes, and demographic questions. Thirty qualified intensive care nurses from a general intensive care unit in Norway (80% female; age range 31–62 years) completed the study. Nurses reported implicit and explicit preferences for thin over thick patients and found obese patients lazier than normal‐weight patients. Measures of behavioral intentions and anti‐fat attitudes were reliable. Generally, the nurses intended to help obese patients immediately. Nevertheless, explicit anti‐fat attitudes (rho = −0.49) as well as implicit anti‐obese stereotypes (rho = −0.40) were negatively correlated with such intentions. Data supported satisfactory face validity, and convergent and discriminant validity within and between implicit and explicit attitudes and stereotypes. The set of research instruments were reliable, valid, and suitable tools to measure qualified intensive care nurses’ implicit and explicit attitudes; however, the present findings need to be replicated in a larger‐scale study.