bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plant Growth-Promoting Endophytic Bacillus Aryabhattai Triggers Novel Genes to Induce Plant Growth
Authors: Xu Hongli , Gao Jingyao , Portieles Roxana , Du Lihua , Gao Xiangyou , Borrás-Hidalgo Orlando 
Published: December 2021

Abstract
Background: In nature, plants interact with a wide range of microorganisms. Most of these microorganisms have the ability to promote plant growth through the induction of important molecular pathways. The current work evaluated whether the endophytic bacterium Bacillus aryabhattai encourages plant growth and how transcriptional changes might be implicated in this effect.Results: The endophytic bacterium showed a significant effect on plant growth. Our results revealed that B. aryabhattai promotes the growth of Arabidopsis and tobacco plants. Notably, transcriptional changes in Arabidopsis plants treated with the bacterium were identified. Genes such as cinnamyl alcohol dehydrogenase, apyrase, thioredoxin H8, benzaldehyde dehydrogenase, indoleacetaldoxime dehydratase, berberine bridge enzyme-like and gibberellin-regulated protein were highly expressed. Additionally, endophytic bacterial genes such as arginine decarboxylase, D-hydantoinase, ATP synthase gamma chain and 2-hydroxyhexa-2,4-dienoate hydratase were activated during the interaction with Arabidopsis.Conclusions: The results show that new plant growth-related genes are induced during the interaction endophytic bacterium B. aryabhattai, and these changes may promote plant growth in sustainable agriculture.
Lumpy Skin Disease (LSD): Pathomorphological Features and Molecular Detection in Dairy Cattle of West Coastal India
Authors: Nayakvadi Shivasharanappa , Joshi Samruddhi Prasad , Rajkumar Susitha , B. Chethan Kumar H. , Bathini Jagruti , Uddarwar Sanjaykumar 
Published: December 2021

Abstract
Lumpy skin disease (LSD) is an emerging pox viral disease affecting cattle population worldwide. In India, the first outbreak of LSD is reported during August 2019 in Odisha state, which then followed by outbreaks in crossbred and indigenous cattle population of other states. Present investigation designed to study the prevalence, pathomorphological changes and molecular detection of LSD virus in naturally infected cattle. The overall morbidity of LSD was 4.48% among 30 dairy farms. Skin nodular biopsy, whole blood and serum samples (n= 66) were collected for the diagnosis of LSD by histopathology, PCR and sequencing. The envelope protein gene (P32), Fusion protein (F) and DNA dependent RNA polymerase 30 kDa subunit (RPO30) genes were targeted for PCR testing. Out of 66, 46 cattle showed generalized skin nodules and papules of various sizes (0.5 - 6.5cm) on the skin particularly at neck, face, nose, tail, perineum and udder. Microscopic examination of the skin nodule biopsy tissue revealed presence of diffuse granulomatous inflammation, hyperkeratosis, focal to diffuse vasculitis and lymphangitis, vacuolar degeneration, spongiosis and acanthosis. The inflammatory cells typically comprised of macrophages, lymphocytes, neutrophils and eosinophils along with diffuse necrosis in dermis in chronic cases. The eosinophilic intracytoplasmic viral inclusions in keratinocytes and epithelial cells were detected in few cases. Gel-PCR assay detected P32 gene in 83%, F gene in 72% and RPO30 gene in 77% of skin biopsy samples. Three blood samples were also found positive for P32 gene by PCR. Whereas TaqMan™ probe Real Time PCR targeting EEV glycoprotein gene (LSDV126) detected LSDV in 94% of biopsy samples and three blood samples which indicated its higher sensitive for the diagnosis of LSDV. Phylogenetic analysis of RPO30 gene sequence showed that the isolates from this study were grouped in same cluster with LSDV isolates of Bangladesh, Kenya and other Indian isolates detected during 2019-20.
Combination of CD47 Expression and SIRI as a Prognostic Factor in Nasopharyngeal Carcinoma Patients
Authors: Deng Chao , Feng Yuhua , Wang Haihua , Zhang Haixia , Ma Jin'an , Fan Songqing , Hu Chunhong , Liu Xianling , Hou Tao 
Published: December 2021

Abstract
Aim: The present study aimed to investigate the prognostic value of the combination of CD47 expression and SIRI level in nasopharyngeal carcinoma (NPC) patients.Materials & Methods: NPC patients who received radical chemoradiation therapy between January 2012 and December 2016 at the Second Xiangya Hospital were retrospectively reviewed. The clinical and laboratory data was collected from the electro-history system. The expression of CD47 was detected by immunohistochemical (IHC) method. Receiver operating characteristic curve analysis was used to determine the optimal cut-off value. Survival curves were analyzed using Kaplan-Meier method, and Cox proportional hazard model was used to identify prognostic factors.Results: A cohort of 183 NPC patients were enrolled. CD47 was highly expressed in 36.1% (66/183) patients at a cut-off value of 35%. And SIRI was elevated in 35.0% (64/183) patients at a cut-off value of 0.94. CD47 expression had no significant correlation with NPC patients’ age, gender, ECOG status, clinical stage, smoking history or chemo-agent. While SIRI level was significantly higher in male patients and patients who has smoking history. Univariate analyzes shown that younger age, better ECOG PS, earlier clinical stage, and low expression of CD47 and SIRI level predicts better PFS, while better ECOG PS, earlier clinical stage, and low expression of CD47 and SIRI level predicts longer OS. Further multivariate Cos regression model showed that aside from ECOG PS and clinical stage, CD47 and SIRI statue was an independent prognostic factor for PFS and OS.Conclusion: Our findings indicate that the combination of CD47 expression and SIRI level might be a promising prognostic predictor for the NPC patients.
CT Angiography-Based Radiomics as a Tool for Carotid Plaque Characterization and Surgery Patient Selection: A Pilot Study
Authors: Cilla Savino , Macchia Gabriella , Lenkowicz Jacopo , Tran Elena H. , Pierro Antonio , Petrella Lella , Fanelli Mara , Sardu Celestino , Re Alessia , Boldrini Luca , Indovina Luca , Filippo Carlo Maria , Caradonna Eugenio , Deodato Francesco , Massetti Massimo , Valentini Vincenzo , Modugno Pietro 
Published: December 2021

Abstract
Objectives: Radiomics is a quantitative method able to analyze a high-throughput extraction of minable imaging features. Herein, we aim to develop a CT angiography-based radiomics analysis and machine learning model for carotid plaques to discriminate vulnerable from no vulnerable plaques.Methods: Thirty consecutive patients with carotid atherosclerosis were enrolled in this pilot study. At surgery, a binary classification of plaques was adopted (“hard” vs “soft”). Feature extraction was performed using the R software package Moddicom. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. A univariate analysis was performed to assess the association between each feature and the plaque classification and chose top-ranked features. The feature predictive value was investigated using binary logistic regression. A stepwise backward elimination procedure was performed to minimize the Akaike information criterion (AIC). The final significant features were used to build the models for binary classification of carotid plaques, including logistic regression (LR), support vector machine (SVM), and classification and regression tree analysis (CART). All models were cross-validated using 5-fold cross validation. Class-specific accuracy, precision, recall and F-measure evaluation metrics were used to quantify classifier output quality.Results: A total of 230 radiomics features were extracted from each plaque. Pairwise Spearman correlation between features reported a high level of correlations, with more than 80% correlating with at least one other feature at |ρ| > 0.8. After a stepwise backward elimination procedure, the entropy and volume features were found to be the most significantly associated with the two plaque groups (p< 0.001), with AUCs of 0.92 and 0.96, respectively. The best performance was registered by the SVM classifier with the RBF kernel, with accuracy, precision, recall and F-score equal to 86.7, 92.9, 81.3 and 86.7%, respectively. The CART classification tree model for the entropy and volume features model achieved 86.7% well-classified plaques and an AUC of 0.987.Conclusion: This pilot study highlighted the potential of CTA-based radiomics and machine learning to discriminate plaque composition. This new approach has the potential to provide a reliable method to improve risk stratification in patients with carotid atherosclerosis.
First Description of the Generation of Human Schwann Cells Transfected With CRISPR Cas9 and a Model of Metformin Mitochondrial Metabolism in Metachromatic Leukodystrophy
Authors: Alvarez Nayibe Tatiana Sanchez , Bautista-Niño Paula Katherine , Trejos-Suárez Juanita , Serrano-Díaz Norma Cecilia 
Published: December 2021

Abstract
Background: Metachromatic leukodystrophy (MLD) is a neurological lysosomal deposit disease that has an impact on public health despite its low incidence in the population. Existing treatments are expensive and inefficient. Few reports in the literature on pathophysiological events related to enzyme deficiency and subsequent accumulation of sulfatides; therefore, the use of metformin as an alternative treatment was evaluated in vitro to counteract the effects. Methodology: An experimental in vitro study that sought to determine the effect of the use of metformin on the accumulation of sulfates in glycolysis and mitochondrial function in an in vitro model of metachromatic leukodystrophy. Human Schwann cells (CSH) transfected with CRISPR Cas9 and without transfection were treated with different concentrations of sulfatides and metformin. Cell viability was evaluated by MTT and SYTOX Green; mitochondrial and glycolytic function by Seahorse XFe24, determination of reactive oxygen species (ROS) and cell death. Results: In the MTT trials, we found that treatment with different concentrations of sulfates did not affect cell viability. Transfected CSH showed higher cell death and ROS production when exposed to 100 µM sulfatides with a statistically significant difference (p <0.001), compared to nontransfected CSH cells. Sulfatides at concentrations of 10 to 100 µM affect mitochondrial bioenergetics as concentrations increase in transfected cells, in nontransfected cells they respond metabolically to exposure; Furthermore, transfected cells show a decrease in basal respiration and maximum respiration after being exposed to a concentration of 100 µM of sulphates; however, in double treatment of these cells with both sulfates and Metformin, respiration also decreases. Maximum and normal mitochondrial respiratory capacity. Conclusion: This research describes for the first time the generation of transfected CSH and the bioenergetic and mitochondrial effect of sulfates in Schwann cells, treatment with 500 µM of Metformin restores metabolic activity of these cells and decreases ROS production, as well as prevention of cell death.
Estimation model of PM2.5 Concentrations Based on Spatiotemporal Adaptability and Satellite Remote Sensing
Authors: li Weidong , Dong Liye , Bai Linyan 
Published: December 2021

Abstract
Based on satellite remote sensing AOD, we can estimate and monitor the continuous changes of PM2.5, which solved the disadvantages of traditional ground station discrete monitoring. Four-dimensional spatiotemporal heterogeneity is not considered in the construction of traditional empirical regression models, such as geographically weighted regression model (GWR) and spatiotemporal geographically weighted regression model (gtwr). To solve this four-dimensional spatiotemporal nonstationarity, this article proposes and constructs a spatiotemporal adaptive fine particulate matter (PM2.5) concentration estimation model: 4D-GTWR by introducing a DEM (Digital elevation model) and time effects into a GWR model. This method solves the heterogeneity between the three-dimensional space and one-dimensional time by constructing a four-dimensional space kernel function and obtaining its weight. Based on PM2.5 ground observation data and meteorological data collected from December 2017 to February 2018 in Zhengzhou City, Henan Province, PM2.5 estimations are obtained from MODIS MYD-3K AOD data using the GWR, TWR, GTWR and 4D-GTWR models. The results showed that the MAE (mean absolute error) of the 4D-GTWR model decreased by 54.13%, 54.06% and 37.90%, compared to those of the GWR, TWR and GTWR models, respectively, and that the PM2.5 concentrations predicted by the 4D-GTWR model were closest to the measured values. The R2 (the correlation coefficient) of the 4D-GTWR model was 0.9496, which was better than those of the GWR (R2 =0.7761), TWR (R2 =0.7763) and GTWR (R2=0.8811) models. The 4D-GTWR model can not only improve the precision of PM2.5 estimations but can also reveal the four-dimensional spatial heterogeneity of PM2.5 concentrations and the differentiation of the DEM's influence on the spatial dimensions.
Evidence of Neuroinflammation and Immunotherapy Responsiveness in Individuals with Down Syndrome Regression Disorder
Authors: Santoro Jonathan Douglas , Partridge Rebecca , Tanna Runi , Pagarkar Dania , Khoshnood Mellad , Rehmani Mustafa , Kammeyer Ryan M. , Gombolay Grace Y. , Fisher Kristen , Conravey Allison , El-Dahr Jane , Christy Alison L. , Patel Lina , Manning Melanie A , Mater Heather Van , Rafii Michael S. , Quinn Eileen A. 
Published: December 2021

Abstract
Background

Down syndrome regression disorder is a symptom cluster consisting of neuropsychiatric regression without cause. This study evaluated the incidence of neurodiagnostic abnormalities in individuals with Down syndrome regression disorder and determine if abnormalities are indicative of responses to therapeutic intervention.
Methods

A retrospective, multi-center, case-control, study was performed. Patients were required to have subacute onset and the presence of four of five symptom groups present (cognitive decline, expressive language, sleep derangement, loss of ability to perform activities of daily living and/or a new movement disorder) and no other explanation for symptoms.
Results

Individuals with Down syndrome regression disorder were comparable to a cohort of individuals with only Down syndrome although had higher rates of autoimmune disease (p= 0.02, 95%CI: 1.04-1.75). Neurodiagnostic abnormalities were found on EEG (n=19, 26%), neuroimaging (n=16, 22%) and CSF (n=9, 17%). Pleocytosis was appreciated in five cases, elevated total protein in nine, elevated IgG index in seven, and oligoclonal bands in two. Testing within two years of symptom onset were more likely to have neurodiagnostic abnormalities (p= 0.01, 95%CI: 1.64-37.06). In individuals with neurodiagnostic abnormalities immunotherapy was nearly four times more likely to have a therapeutic effect than in those without neurodiagnostic abnormalities (OR: 4.11, 95%CI: 1.88-9.02). In those with normal neurodiagnostic studies (n=43), IVIg was effective in 14 of 17 (82%) patients as well although other immunotherapies were uniformly ineffective.
Conclusions

This study reports the novel presence of neurodiagnostic testing abnormalities in individuals with Down syndrome regression disorder, providing credence to this symptom cluster potentially being of neurologic and/or neuroimmunologic etiology.
PD-L1, Vimentin and Ki-67 Acting as Immunotherapy Predictive Biomarkers in Pulmonary Carcinomas Transthoracic and Bronchial Biopsies
Authors: Figueiredo Maria Inês , Sousa Vítor , Carvalho Lina 
Published: December 2021

Abstract
Introduction:

Programmed death-ligand 1 (PD-L1) expression became a routine biomarker to preview response to programmed death-1 (PD-1)/PD-L1 inhibitors, with diverging parameters concerning PD-L1 scoring and variable response to immunotherapy agents. The aim of this study was to evaluate association between PD-L1 expression and immunohistochemistry panel applied in Pathology practice, defining any of those antibodies as biomarkers concurrent in patients selection for PD-1/PD-L1 blockade therapy.
Methods

A total of 97 cTNM IIIb/IV staged pulmonary carcinoma biopsies were randomly selected between 2018/2020, after adequate representativeness and PD-L1 expression scored through Dako 22C3 antibody. The panel with cytokeratin 7, thyroid transcription factor 1 (TTF1), cytokeratin 5.6, cluster of differentiation 56 (CD56), periodic acid-Schiff (PAS-D), vimentin expression, and ki-67 labeling index (LI) was considered for retrieving reports and respective archival slides.
Results

PD-L1 expression in tumor cells (TCs) was identified in 56 samples and significantly associated with male gender (p=0.028), vimentin expression (p=0.018) and ki-67 LI>30% (p=0.029). A tendency to PD-L1 positivity came up in lymphocytic-predominant/immune-inflamed stroma (9/10), adenocarcinoma solid subtype (21/23) and CK7-negative squamous cell carcinomas (8/13). When more than 50% TCs expressed PD-L1, the risk of vimentin expression was 3.85 times higher (OR=3.85; p=0.013), and for ki-67 LI>30% the risk was 9.90 times higher (OR=9.90; p=0.033), compared with PD-L1-negative samples.
Conclusion

High proliferation status defined by ki-67 LI>30% and epithelial-mesenchymal transition phenotype verified by vimentin staining analysis might complement PD-L1-positive TCs percentage determination for immunotherapy prescription. These patients will more likely benefit from PD-1/PD-L1 blockade therapy, overcoming the limitations of selection based on PD-L1 immunohistochemistry status.
Identification of Methylated Differentially Expressed Hub Genes and Immune Infiltration in Diabetic Retinopathy
Authors: Zhou Qi , Xiong Xin , Tang Min , Lei Yingqing , Lv Hongbin 
Published: December 2021

Abstract
BackgroundDiabetic retinopathy (DR), a severe complication of diabetes mellitus (DM), is a global social and economic burden. However, the pathological mechanisms mediating DR are not well-understood. This study aimed to identify differentially methylated and differentially expressed hub genes (DMGs and DEGs, respectively) and associated signaling pathways, and to evaluate immune cell infiltration involved in DR. MethodsTwo publicly available datasets were downloaded from the Gene Expression Omnibus database. Transcriptome and epigenome microarray data and multi-component weighted gene coexpression network analysis (WGCNA) were utilized to determine hub genes within DR. One dataset was utilized to screen DEGs and to further explore their potential biological functions using functional annotation analysis. A protein-protein interaction network was constructed. Gene set enrichment and variation analyses (GSVA and GSEA, respectively) were utilized to identify the potential mechanisms mediating the function of hub genes in DR. Infiltrating immune cells were evaluated in one dataset using CIBERSORT. The Connectivity Map (CMap) database was used to predict potential therapeutic agents. ResultsIn total, 673 DEGs (151 upregulated and 522 downregulated genes) were detected. Gene expression was significantly enriched in the extracellular matrix and sensory organ development, extracellular matrix organization, and glial cell differentiation pathways. Through WGCNA, one module was found to be significantly related with DR (r=0.34, P =0.002), and 979 hub genes were identified. By comparing DMGs, DEGs, and genes in WGCNA, we identified eight hub genes in DR ( AKAP13, BOC, ACSS1, ARNT2, TGFB2, LHFPL2, GFPT2, TNFRSF1A ), which were significantly enriched in critical pathways involving coagulation, angiogenesis, TGF-β, and TNF-α-NF-κB signaling via GSVA and GSEA. Immune cell infiltration analysis revealed that activated natural killer cells, M0 macrophages, resting mast cells, and CD8 + T cells may be involved in DR. ARNT2, TGFB2, LHFPL2 , and AKAP13 expression were correlated with immune cell processes, and ZG-10, JNK-9L, chromomycin-a3, and calyculin were identified as potential drugs against DR. Finally, TNFRSF1A , GFPT2 , and LHFPL2 expression levels were consistent with the bioinformatic analysis. ConclusionsOur results are informative with respect to correlations between differentially methylated and expressed hub genes and immune cell infiltration in DR, providing new insight towards DR drug development and treatment.
Ex vivo Fluorescence Confocal Microscopy: Chances and Changes in the Analysis of Breast Tissue
Authors: Nackenhorst Maja Carina , Kasiri Mohammad , Gollackner Bernd , Regele Heinz 
Published: December 2021

Abstract
Background: Rapid histologic diagnosis of frozen sections is essential for a variety of surgical procedures. Frozen sections however, require specialized lab equipment, are prone to freezing artifacts and are not applicable to all types of tissue. Adipose tissue is especially difficult to process in frozen sections. Although these limitations are well known, no alternative method for microscopic tissue analysis that might replace frozen sections could be established. Our objective was to evaluate whether tissue imaging based on ex vivo fluorescent confocal microscopy (FCM) is applicable for rapid microscopic assessment of breast tumors specimens with abundant adipose tissue.Methods: We evaluated 17 tissue samples from mastectomy specimens, rich in adipose tissue, submitted to the department of pathology at the Medical University of Vienna. We conducted our study on the FCM VivaScope® 2500M-G4 (Mavig GmbH, Munich, Germany; Caliber I.D.; Rochester NY, USA).Results: When comparing FCM to frozen sections, we found a very similar overall processing time for FCM images and frozen sections respectively. Image quality was mostly superior to frozen sections (especially for adipose tissue and nuclear detail) but inferior to H&E stained FFPE sections. Limitations of the technology were uneven coloring, invisibility of ink applied for marking tissue margins and distortion artifacts if too much pressure is applied to the tissue. Conclusion: FCM has the potential to expand the application and usefulness of rapid tissue analysis as speed is comparable and quality exceeds that of frozen sections especially in tissues rich in adipose cells such as breast specimen.