bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Prognostic Necroptosis-Related lncRNA Signature to Predict the Immune Response and Drug Sensitivity of Bladder Cancer
Authors: Tian Chao , Chen Guiliu , Cao Zhengguo 
Published: May 2022

Abstract
Background: Patients with bladder cancer (BLCA), especially those with advanced stage cancer, have a short life span; thus, new drugs need to be developed urgently to improve the situation. Long noncoding RNAs (lncRNAs) are considered regulatory targets for cancer, including BLCA. Therefore, we constructed a promising signature of lncRNAs related to necroptosis and further predicted the immune response and sensitivity of drugs. Methods: We downloaded the transcriptome and clinical data for BLCA from the Cancer Genome Atlas（TCGA）. Necroptosis related to lncRNAs (nrlncRNAs) was subsequently identified by univariate Cox regression. We then constructed the signature by performing the least absolute shrinkage and selection operator(LASSO) and evaluated it by Kaplan–Meier analysis, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, calibration curves, gene set enrichment analyses(GSEA), immune checkpoint, tumor microenvironment(TME), N6-methyladenosine (m6A) modification genes, and the half-maximal inhibitory concentration (IC50) analysis in the risk groups. Results: An 11-nrlncRNAs (AC008750.1, AL133297.1, AC005479.1, AP003559.1, UBE2Q1-AS1, MIR100HG, LINC02709, AC005387.1, LINC00649, AC021321.1, ETV7-AS1) prognostic signature was constructed. Immune checkpoint analysis revealed that the expression of most of the immune genes in the high-risk group was higher than those in the low-risk group. The signature predicted different IC50 values to have statistical significance in high-and low-risk groups for multiple drugs. Conclusion: Our constructed signature may contribute to the prognosis of patients with BLCA as well as serve as clinical predictors of chemotherapy and immunotherapy.
Nematode-citrus plant interactions: host preference, damage rate and molecular characterization of Citrus root nematode Tylenchulus semipenetrans
Authors: Bozbuga Refik , Yildiz Senol , Yuksel Ebubekir , Özer Göksel , Dababat Abdelfattah A. , İmren Mustafa 
Published: May 2022

Abstract
AimsCitrus plants are hosts of numerous plant-parasitic nematodes (PPNs), which are microscopic organisms and hidden enemies for plants. Among the PPNs, the citrus root nematode, Tylenchulus semipenetrans, causes significant damage to citrus plantations in the world. Understanding the citrus nematode population, precise nematode identification, host preference among the citrus species, and damage threshold level are crucially important to control T. semipenetrans. Although some studies have been conducted, minutiae about citrus plant-nematode interactions, nematodes density, and molecular nematode identification have not been well understood. MethodsThis study aimed to reveal nematode identification using molecular and morphological methods, host-nematode interactions, host (citrus species) preference, damage of economic threshold (ET), and economic-injury level (EIL). Therefore, citrus plantations of different provinces located in the Mediterranean region of Turkey were investigated.ResultsITS sequences revealed that samples were infested with the citrus root nematode Tylenchulus semipenetrans. The lowest nematode density was obtained from Mersin (80-second-stage juveniles(J2s)/150g-soil), while the highest density was obtained from Adana (18260-J2s/150g-soil). Out of the 73 samples collected from the Mediterranean region, 21.9% have passed the EIL, while 8.2% are on the ET. Citrus nematode reproduced utmost level on roots of Citrus reticulata, followed by C.sinensis, C.limon, and C.parasidisi, respectively. ConclusionThis study revealed that the Citrus nematode is more common than it was thought and that the population fluctuations change according to the citrus plant species. It is of great importance to investigate the possible genetic changes in nematode populations caused by global warming and its negative impact on citrus yield.
Using the U-Net Family for Epicardial Adipose Tissue Segmentation and Quantification in Non-Contrast CT
Authors: Liu Lu , Ma Runlei , Ooijen Peter van , Oudkerk Matthijs , Vliegenthart Rozemarijn , Brune Christoph , Veldhuis Raymond 
Published: May 2022

Abstract
Background: Epicardial adipose tissue (EAT) locates between the visceral pericardium and myocardium and the EAT volume is correlated with cardiovascular risk. Nowadays, many deep learning-based automated EAT segmentation and quantification methods in the U-net family were developed to reduce the workload for radiologists. However, most of the works were based on private or small dataset with di↵erent label types. Thus, their reproducibility is relatively low and comparison of their performance is difficult. Methods: In this work, we comparably studied and evaluated the state-of-the-art segmentation methods, and o↵ered future directions. Our work is based on a dataset of 154 non-contrast CT scans from the ROBINSCA study with two types of labels: (a) region inside the pericardium and (b) pixel-wise EAT labels. We selected four advanced methods from the U-net family: 3D U-net, 3D attention U-net, an extended 3D attention U-net, and U-net++. For evaluation, we did both four-fold cross-validation and hold-out tests. Agreement between the automatic segmentation/quantification and the manual quantification was evaluated with the Pearson correlation and the Bland-Altman analysis.Results: Generally, the models trained with label type (a) showed better performance compared to models trained with label type (b). The U-net++ model trained with label type (a) showed the best performance of segmentation and quantification. The U-net++ model trained with label type (a) efficiently provides better EAT segmentation results(Hold-out test: DCS=80.18 ± 0.20%, mIoU=67.13 ± 0.39%, sensitivity=81.47 ± 0.43%, specificity=99.64 ± 0.00%, Pearson correlation=0.9405) and EAT volume compared to the other U-net-based networks and the recent EAT segmentation method.Conclusions: 3D convolutional neural networks do not always perform better than 2D convolutional neural networks in the EAT segmentation and quantification.And labels of the region inside the pericardium are helpful to train more accurate EAT segmentation models. Deep learning-based methods have the potential to provide good EAT segmentation and quantification.
Blood-based protein biomarkers in definite frontotemporal dementia: a case-control study
Authors: Teunissen Charlotte , Campo Marta Del , Peeters Carel , Meeter Lieke , Seelaar Harro , Koel-Simmelink Marleen , Ramakers Inez , Middelkoop H , De Deyn Peter , Claessen Jurgen , Swieten John van , Bridel Claire , Hoozemans Jeroen , Flier Wiesje van der , Scheltens Philip , Pijnenburg Yolande , Babapour-Mofrad Rosha 
Published: May 2022

Abstract
Background: Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process. Methods: Plasma proteins (n=1303) from pathologically and/or genetically confirmed FTD patients (n=56; FTLD-Tau n=16; age= 58.2±6.2; 44% female, FTLD-TDP n= 40; age= 59.8±7.9; 45% female), AD patients (n=57; age= 65.5±8.0; 39% female), and non-demented controls (n=148; 61.3±7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, tissue proteins of post-mortem frontal brain cortex of FTD (n=10; FTLD-Tau n=5; age= 56.2±6.9, 60% female, and FTLD-TDP n= 5; age= 64.0±7.7, 60% female) and non-demented controls (n=5; age= 61.3±8.1; 75% female) were measured. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis. Results: Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p=0.005). The overall tissue protein expression profile differed between FTD and controls (7-proteins; p=0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified. Conclusions: We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which were mainly associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.
Association of serum creatinine with hepatic steatosis and fibrosis: a cross-sectional study
Authors: Ma Juan , Wei Zhongcao , Wang Qian , Lu Xiaolan , Zhou Zhihua , Li Ruohan , Shu Qiuai , Liu Yixin , Wang Jinhai , Liu Na , Shi Haitao 
Published: May 2022

Abstract
Background: Recent studies have shown that chronic kidney disease (CKD) prevalence is significantly higher in patients with hepatic steatosis (HS); however, it remains unclear whether HS is associated with serum creatinine (SCr). We aimed to explore the association between SCr levels and HS in a Chinese population.Methods: We performed a cross-sectional study among 56569 Chinese individuals. SCr level, other clinical and laboratory parameters, abdominal ultrasound and noninvasive fibrosis scores were extracted, and the fibrosis 4 score (FIB-4) was calculated.Results: A total of 27.1% of the subjects had HS. After 1:1 propensity score matching (PSM) according to sex and age, we included 13301 subjects with HS and 13,301 subjects without HS. SCr levels were significantly higher in the HS group than in the non-HS group (73.19±15.14 vs. 71.75±17.49, p<0.001). Univariate and multivariate regression analyses showed a positive association between SCr and the prevalence of HS. Stepwise regression analysis showed that the association between SCr and HS was independent of other metabolic syndrome components. The prevalence of HS increased significantly with increasing SCr levels. Metabolism-related indicators and liver enzymes were significantly higher in the HS group than in the non-HS group; furthermore, these parameters increased with increasing SCr levels. FIB-4 was significantly higher in the HS group than in the non-HS group but did not show an increasing trend with increasing SCr levels.Conclusions: Our results showed an independent association between SCr level and HS risk in a Chinese population.
Serum marker and CT characteristics of coronary calcified nodule assessed by intravascular ultrasound
Authors: Li Jing , Li Jing , Jian Zhijie , Wu Jianhua , Yang Jian , Guo Ning , Huang Xin 
Published: May 2022

Abstract
Background: Calcified nodule (CN) is a type of potentially vulnerable plaque. Its formation mechanism remains unknown. This study was to assess serum marker and computed tomography angiography (CTA) characteristics of CN validated by intravascular ultrasound (IVUS).Methods: Patients underwent coronary CTA followed by invasive coronary angiography and IVUS were retrospectively analyzed. Serum levels of alkaline phosphatase (ALP), gamma-glutamyltransferase, and calcium were collected.Results: IVUS detected 128 de novo calcified plaques in 79 patients with coronary artery disease (CAD). CNs were identified in 11.4% (9/79) of patients and 9.4% (12/128) of lesions. Compared with patients with non-nodular calcified plaques, CN patients had higher serum level of ALP (82.00 vs 65.00 mmol/L, P = .022) and total plaque volume (673.00 vs 467.50 mm3, P = .021). Multivariable analyses revealed that serum ALP level and total plaque volume independently associated with the prevalence of CN in CAD patients with calcified plaques. At lesion level, the CN group had a more frequency of moderate to heavy calcification on angiography (75.0% vs 40.5%, P = .017). In terms of CTA characteristics, plaques with CN had a more severe diameter stenosis (79.00% vs 63.00%, P = .007), higher plaque burden (85.40% vs 77.05%, P = .005), total plaque density (398.00 vs 283.50 HU, P = .008), but lower lipid percentage (14.65 % vs 19.75%, P = .010) and fiber percentage (17.90 % vs 25.65%, P = .011). Mean plaque burden is an independent predictor of the prevalence of CN in calcified plaques (odds ratio = 1.102, 95% CI: 1.025-1.185, P = .009). The AUC is 0.753 (95% confidence interval: 0.615-0.890, P = .004). When using 84.85% as the best cutoff value, the diagnostic sensitivity and specificity of mean plaque burden for predicting the presence of CN within calcified plaques were 66.7% and 80.2% respectively.Conclusion: CN had different CTA imaging features from non-nodular coronary calcification. The presence of a CN was associated with a higher serum ALP level and plaque burden.
Thiamethoxam evoked neural oxido-inflammatory stress in male rats through modulation of Nrf2/NF-kB/iNOS signaling and inflammatory cytokines: neuroprotective effect of silymarin.
Authors: Habotta Ola , Ateya Ahmed , Saleh Rasha M. , El-Ashry Eman S. 
Published: May 2022

Abstract
Thiamethoxam, a neonicotinoid insecticide, is a widely used insecticide with neurotoxic potential. This study explored the neuroprotective effects of silymarin on thiamethoxam-triggered cortical injury in male rats. Animals were divided into four groups and treated daily either with SM (150 mg/kg), TMX (78.15 mg/kg), or both at the aforementioned doses for 28 days. Our results revealed marked declines in cortical SOD and CAT activities with elevations in MDA, IL-1b and TNF-α levels in thiamethoxam-treated rats. Further, thiamethoxam induced down-regulation in gene expressions of Sod, Cat, Gpx, and Nrf-2 genes, with up-regulation in the expression of IL-1b, IL-6, iNOS, TNF-α and NF-kB genes. Interestingly, pre-treatment with SM provided a notable neuroprotective action against TMX-mediated cortical damage that indicates its promising antioxidant and anti-inflammatory activities. This effect may be mediated by Nrf2/NF-kB/iNOS signalling and suppression of excess free radicals and production of inflammatory cytokines.
Validation of the Moroccan version of the Cohen perceived stress scale (PSS-10) among women with Breast cancer
Authors: Mounjid Chaimaa , M’rabti Hind , Sossé Leila Alaoui , Laraqui Abdelilah , Chajès Véronique , Khannoussi Basma El , Bakri Youssef , Errihani Hassan 
Published: May 2022

Abstract

BackgroundThe possible contribution of psychological stress to the development of BC has been largely investigated. One of the most extensively used psychological scales is the Perceived Stress Scale (Health Soc Behav 24:385 − 96, 1983), which demonstrates sufficient reliability and validity. The PSS-10 has been translated and adapted into over 30 languages on different samples. Thus, the purposes of this study were first to translate the PSS-10 into the Moroccan Arabic dialect language and second to evaluate its validity in women with breast cancer (BC).MethodsA method of translation and counter-translation into the Moroccan dialect was performed for the 10-item of PSS. Then the translated questionnaire was administered to a representative sample of 100 women with BC. Validation of metrological qualities was established by examining: internal reliability, test-retest reliability, convergent validity, and factorial structure.ResultThe Moroccan version of the PSS showed a good internal reliability (α = 0.87) and test-retest reliability (0.95 with IC95%=[0.88,0.98]. The confirmatory factor analysis showed a bi-dimensional structure with two related latent factors. Moreover, the principal component analysis of the Perceived Stress Scale allowed us to extract two factors that explained 67% of the total variance.ConclusionsThe present study showed that the Moroccan version of the PSS-10 has good internal consistency and reliability. The factor structure is similar to that of the PSS translated into other languages. We consider this version of the PSS-10 to be an adequate instrument for assessing perceived stress in the Moroccan population and can provide an important tool in medical practice such as oncology. Moreover, it will be interesting to conduct further studies as comparative investigations between patients with BC and healthy women by using this validated Scale PSS.
Improving bond strength of translucent zirconia through surface treatment with SiO 2 –ZrO 2 coating
Authors: Cui Tiehan , Du Qiao , Niu Guangliang , Qiu Jiaxuan , Yang Bin 
Published: May 2022

Abstract
Purpose: Zirconia is a kind of chemically stable material that is able to form a weak bond with resin. For the purpose of investigating the surface properties of SiO2–ZrO2 coating on zirconia and its bonding with resin.Methods: the translucent zirconia discs based on different surface treatments were named CT (control group), SB (sandblasting), C21, C11 and C12 groups (with SiO2: ZrO2 = 2: 1,1: 1 and 1: 2 coatings). The surface of translucent zirconia coating was analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), surface roughness assessment (Ra), X-ray diffraction (XRD), water contact angle (WCA), fracture toughness (KIC), flexural strength (FS), translucence parameter (TP) and shear bond strength (SBS). A 2-way analysis of variance (ANOVA) for shear bond strength results and a 1-way ANOVA for other data were performed as statistical analysis.Results: The SEM images revealed the existence of SiO2 islands on the coated translucent zirconia. The Ra of C12, C11, and C21 groups was larger than that of SB and CT groups. The XRD showed that phase transformation was not detected in any group. In addition, sandblasting and SiO2–ZrO2 coatings couldn’t reduce certain physical properties of translucent zirconia, but could reduce the WCA. According to the TP results, the translucency of the group C21 decreased, as well as group C11 illustrated the highest shear bond strength under both aging conditions.Conclusion: The SiO2–ZrO2 coating is a promising method to enhance the bonding between resin cement and translucent zirconia.
Tracing Coalition Changes in Knowledge in and Engagement with Childhood Obesity Prevention to Improve Intervention Implementation
Authors: Moore Travis R. , Pachucki Mark C. , Hennessy Erin , Economos Christina D. 
Published: May 2022

Abstract
Background
While most coalition research focuses on studying the effects of peer relationship structure, this study examines the coevolution of coalition structure and behavior across three communities in the U.S. with the goal of identifying coalition dynamics that impact a childhood obesity prevention intervention.
Methods
Over two years (2018–2020), three communities within the U.S. participated in a childhood obesity prevention intervention at different times. This intervention was guided by the Stakeholder-Driven Community Diffusion theory, which describes an empirically testable mechanism for promoting community change. Measures are part of the Stakeholder-driven Communtiy Diffusion (SDCD) survey with demonstrated reliability, which include knowledge of and engagement with childhood obesity prevention and social networks. Data were used to build stochastic actor-oriented models to examine the coevolution of coalition structure with coalition behavior defined a priori as knowledge of and engagement with obesity prevention among coalition members only (Network A) and coalition members and their nominated alters (Network B).
Results
Overall, coalitions decrease in size and their structure becomes less dense over time. Both Network A and B show a consistent preference to form and sustain ties with those who have more ties. In Network B, there was a trend for those who have higher knowledge scores to increase their number of ties over time. The same trend appeared in Network A but varied based on their peers’ knowledge in and engagement with childhood obesity prevention. Across models, engagement with childhood obesity prevention research was not a significant driver of changes in either coalition network structure or knowledge.
Conclusions
The trends in coalition Network A and B’s coevolution models may point to context-specific features (e.g., ties among coalition members) that can be leveraged for better intervention implementation. To that end, examining tie density, average path length, network diameter, and the dynamics of each behavior outcome (i.e., knowledge in and engagement with childhood obesity prevention) may help tailor WoC interventions. Future research should attend to additional behavioral variables (e.g., group efficacy) that can capture other aspects of coalition development and that influence implementation, and to testing the efficacy of network interventions after trends have been identified.
Assessment of Alzheimer-related Pathologies of Dementia Using Machine Learning Feature Selection
Authors: Rajab Mohammed D , Jammeh Emmanuel , Taketa Teruka , Brayne Carol , Matthews Fiona E , Su Li , Ince Paul G , Wharton Stephen B , Wang Dennis 
Published: May 2022

Abstract
Although a variety of brain lesions may contribute to the pathological diagnosis of dementia, the relationship of these lesions to dementia, how they interact and how to quantify them remain uncertain. Systematically assessing neuropathological measures in relation to the cognitive and functional definitions of dementia may enable the development of better diagnostic systems and treatment targets. The objective of this study is to apply machine learning approaches for feature selection to identify key features of Alzheimer-related pathologies associated with dementia. We applied machine learning techniques for feature ranking and classification as an unbiased comparison of neuropathological features and assessment of their diagnostic performance using a cohort (n = 186) from the Cognitive Function and Ageing Study (CFAS). Seven feature ranking methods using different information criteria consistently ranked 22 out of the 34 neuropathology features for importance to dementia classification. Braak neurofibrillary tangle stage, Beta-amyloid and cerebral amyloid angiopathy features were the most highly ranked, although were highly correlated with each other. The best performing dementia classifier using the top eight ranked neuropathology features achieved 79% sensitivity, 69% specificity, and 75% precision. A substantial proportion (40.4%) of dementia cases was consistently misclassified by all seven algorithms and any combination of the 22 ranked features. These results highlight the potential of using machine learning to identify key indices of plaque, tangle and cerebral amyloid angiopathy burdens that may be useful for the classification of dementia.