bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toughness and spanning trees in K4‐minor‐free graphs
Authors: Ellingham M. N. , Shan Songling , Ye Dong , Zha Xiaoya 
Published: October 2020

AbstractFor an integer , a ‐tree is a tree with maximum degree at most . More generally, if is an integer‐valued function on vertices, an ‐tree is a tree in which each vertex has degree at most . Let denote the number of components of a graph . We show that if is a connected ‐minor‐free graph and
then has a spanning ‐tree. Consequently, if is a ‐tough ‐minor‐free graph, then has a spanning ‐tree. These results are stronger than results for general graphs due to Win (for ‐trees) and Ellingham, Nam, and Voss (for ‐trees). The ‐minor‐free graphs form a subclass of planar graphs, and are identical to graphs of treewidth at most 2, and also to graphs whose blocks are series‐parallel. We provide examples to show that the inequality above cannot be relaxed by adding 1 to the right‐hand side, and also to show that our result does not hold for general planar graphs. Our proof uses a technique where we incorporate toughness‐related information into weights associated with vertices and cutsets.
Edge‐decomposing graphs into coprime forests
Authors: Klimošová Tereza , Thomassé Stéphan 
Published: October 2020

AbstractThe Barát‐Thomassen conjecture, recently proved in Bensmail et al. (2017), asserts that for every tree , there is a constant such that every ‐edge‐connected graph with number of edges (size) divisible by the size of admits an edge partition into copies of (a ‐decomposition). In this paper, we investigate in which case the connectivity requirement can be dropped to a minimum degree condition. For instance, it was shown in Bensmail et al. (2019) that when is a path with edges, there is a constant such that every 24‐edge‐connected graph with size divisible by and minimum degree has a ‐decomposition. We show in this paper that when is a coprime forest (the sizes of its components being a coprime set of integers), any graph with sufficiently large minimum degree has an ‐decomposition provided that the size of divides the size of (no connectivity is required). A natural conjecture asked in Bensmail et al. (2019) asserts that for a fixed tree , any graph of size divisible by the size of with sufficiently high minimum degree has a ‐decomposition, provided that is sufficiently highly connected in terms of the maximal degree of . The case of maximum degree 2 is answered by paths. We provide a counterexample to this conjecture in the case of maximum degree 3.
Proton MR Spectroscopy in Assessing the Biochemical Milieu of Human Testes
Authors: Tsili Athina C. , Astrakas Loukas , Sofikitis Nikolaos , Argyropoulou Maria I. 
Published: October 2020

Proton magnetic resonance spectroscopy (MRS), considered a connection between metabolism and anatomic and functional information provided by standard MRI, gives information on various tissue metabolites and their pathologic changes. Recently, proton MRS has been added as an adjunct tool to the multiparametric protocol of scrotal MRI, providing a new insight into the extremely complex biochemical milieu of normal and abnormal testes. This article reviews proton MR spectra of normal testes, showing age and bilateralism dependence. Disturbances of various metabolic pathways in testes of infertile men resulting in alterations of metabolite peaks are discussed. Preliminary data on proton MR spectra of testicular mass lesions are presented.Level of Evidence5.Technical Efficacy Stage5.
Leucine‐rich alpha‐2 glycoprotein (LRG): A novel acute phase protein expressed in Stage 3 Grade C periodontitis before and after periodontal therapy
Authors: Keles Yucel Zeynep Pinar , Balli Umut 
Published: October 2020

AbstractBackgroundLeucine‐rich alpha‐2 glycoprotein (LRG) is a novel acute phase protein involved in inflammation‐associated diseases and that considered to be induced by multiple proinflammatory cytokines. This study aimed to investigate gingival crevicular fluid (GCF) and serum levels of LRG, interleukin (IL)‐6 and tumor necrosis factor (TNF)‐α in patients with Stage 3 periodontitis before and after non‐surgical periodontal treatment.MethodsTwenty‐five Stage 3 periodontitis and twenty‐five periodontally healthy individuals were enrolled in the study. Clinical periodontal measurements were recorded; periodontitis patients received non‐surgical periodontal treatment, and GCF and serum samples were obtained at baseline and at 6 weeks after treatment. LRG, IL‐6 and TNF‐α were determined by ELISA.ResultsGCF and serum LRG, IL‐6 and TNF‐α were significantly higher in periodontitis group than healthy controls (P < .001). A significant decrease in GCF and serum LRG, IL‐6 and TNF‐α was detected after periodontal treatment compared with baseline values of periodontitis patients (P < .001).ConclusionOur findings revealed that LRG expression was increased in Stage 3 periodontitis both locally and systemically, and non‐surgical periodontal therapy was effective in reducing LRG levels in GCF and serum of these patients.
Porphyromonas gingivalis infection alters Nrf2‐phase II enzymes and nitric oxide in primary human aortic endothelial cells
Authors: Sampath Chethan , Okoro Emmanuel U. , Gipson Michael J. , Chukkapalli Sasanka S. , Farmer‐Dixon Cherae M. , Gangula Pandu R. 
Published: October 2020

ABSTRACTBackgroundPeriodontal disease (PD) is known to be associated with endothelial dysfunction in patients with coronary artery and/or cardiovascular disease. In our study, we sought to explore the virulence of P. gingivalis (Pg) affecting glycogen synthase kinase 3 beta (GSK‐3β)/nuclear factor (erythroid‐derived 2)‐like 2 (Nrf2)/tetrahydrobiopterin (BH4)/ nitric oxide synthase (NOS) expression in primary human aortic endothelial cells (pHAECs).MethodspHAECs were infected for 48 hours with Pg in vitro using the Human oxygen‐Bacteria anaerobic coculture technique. Cell viability was determined, and target gene expression changes were evaluated by quantitative real‐time polymerase chain reaction at the end of each incubation period.ResultsPg impaired pHAEC viability 24 hours post‐infection. Pg infection reduced mRNA expression levels of endothelial NOS (eNOS), Nrf2, and Phase II enzymes (heme oxygenase‐1, catalase, superoxide dismutase‐1) in a time‐dependent manner. Significant (P <0.05) increase in the inflammatory markers (interleukin [IL]‐1β, IL‐6, and tumor necrosis factor‐α) were observed in the medium as well as in the infected cells. Interestingly, inducible NOS mRNA levels showed a significant (P <0.05) increase at 12 hours and 24 hours and were reduced at later time points. BH4 (cofactor of eNOS) biosynthesis enzyme dihydrofolate reductase (DHFR, salvage pathway) mRNA levels showed a significant (P <0.05) decrease, while mRNA levels of GSK‐3β were elevated.ConclusionsThese results suggest that periodontal bacterial infection may cause significant changes in the endothelial GSK‐3β/BH4/eNOS/Nrf2 pathways, which may lead to impaired vascular relaxation. Greater understanding of the factors that adversely affect endothelial cell function could contribute to the development of new therapeutic compounds to treat PD‐induced vascular diseases.
Impact of adjunctive procedures on recombinant human fibroblast growth factor‐2–mediated periodontal regeneration therapy: A retrospective study
Authors: Nakayama Yohei , Matsuda Hideo , Itoh Shoichi , Iwai Yasunobu , Takai Hideki , Mezawa Masaru , Yoshino Shoichi , Ogata Yorimasa 
Published: October 2020

AbstractBackgroundHuman fibroblast growth factor‐2 (rhFGF‐2) therapy has been used for periodontal tissue regeneration. However, few studies have reported their adjunctive procedures based on strategy of tissue engineering. The aim of this retrospective study is to assess the adjunctive effects of modified papilla preservation technique (mPPT) and combination with autogenous bone grafts (AG) on the rhFGF‐2 therapy.MethodsTotal of 44 sites underwent rhFGF‐2 therapies and the evaluations in the survey periods. The primary outcome was set to the radiographic bone fill by radiographic examinations at 6 and 12 months after surgeries. We analyzed the correlation between influencing factors and the primary outcome, and differences of therapeutic effect by combination therapy with mPPT and that with AG.ResultsAfter surgeries, probing depth (PD), clinical attachment level (CAL) and bone defects significantly improved. The improvements of radiographic bone fill were significantly positive correlated with a number of bone walls, combination with mPPT, and AG at 6 months after surgeries, and with combination with mPPT and AG at 12 months after surgeries. The significant differences of improvements of radiographic bone fill were demonstrated between combination with or without mPPT at 12 months after surgeries, and with or without AG at 6 and 12 months after surgeries. Moreover, the multiple linear regression analysis for the radiographic bone fill indicated the significant regression coefficient with conducts of mPPT.ConclusionsmPPT and AG had powerfully adjunctive effects on rhFGF‐2 therapy. Further studies are needed in order to verify by randomized clinical trials.
Posttraumatic Stress Disorder and Conduct Problems: The Role of Self‐Control Demands
Authors: Simons Raluca M. , Walters Kyle J. , Keith Jessica A. , Simons Jeffrey S. 
Published: October 2020

AbstractWe tested within‐ and between‐person effects of posttraumatic stress disorder (PTSD) symptoms on conduct problems and alcohol intoxication via self‐control demands using multilevel structural equation modeling in a longitudinal burst‐design study of 251 U.S. veterans who participated in the recent wars in Iraq and Afghanistan. We theorized that experiencing PTSD symptoms engenders efforts to regulate mood, control thoughts, and inhibit or control behavior that is taxing to the individual (i.e., it places demands on self‐control) and hypothesized that this process results in subsequent deficits in regulatory control that manifest in heightened intoxication and conduct problems associated with PTSD. At the within‐person level, daytime PTSD symptoms, IRR = 1.09, and self‐control demands, IRR = 1.12, exhibited within‐person associations with nighttime conduct problems over and above nighttime intoxication. Consistent with our hypothesis, daytime increases in self‐control demands mediated the associations between daytime PTSD symptoms and subsequent nighttime conduct problems. The indirect effect between daytime PTSD symptoms and nighttime intoxication via self‐control demands was nonsignificant. At the between‐person level, self‐control demands mediated the associations between PTSD symptoms and conduct problems; however, the expected between‐person associations with intoxication were nonsignificant. Drinking behavior is related to but cannot fully account for various difficulties in psychosocial functioning associated with PTSD. The present results suggest that dysregulated behavior may, ironically, stem from individuals’ concerted efforts to control and manage overwhelming symptoms. Self‐control demands may be a common factor that accounts for a broad range of functional impairments associated with PTSD.
Mobile fosfomycin resistance genes in Enterobacteriaceae—An increasing threat
Authors: Zurfluh Katrin , Treier Andrea , Schmitt Kira , Stephan Roger 
Published: October 2020

AbstractAntimicrobial resistance is one of the major threats to the health and welfare of both humans and animals. The shortage of new antimicrobial agents has led to the re‐evaluation of old antibiotics such as fosfomycin as a potential regimen for treating multidrug‐resistant bacteria especially extended‐spectrum‐beta‐lactamase‐ and carbapenemase‐producing Enterobacteriaceae. Fosfomycin is a broad‐spectrum bactericidal antibiotic that inhibits the initial step of the cell wall biosynthesis. Fosfomycin resistance can occur due to mutation in the drug uptake system or by the acquisition of fosfomycin‐modifying enzymes. In this review, we focus on mobile fosfomycin‐resistant genes encoding glutathione‐S‐transferase which are mainly responsible for fosfomycin resistance in Enterobacteriaceae, that is, fosA and its subtypes, fosC2, and the recently described fosL1‐L2. We summarized the proposed origins of the different resistance determinants and highlighted the different plasmid types which are attributed to the dissemination of fosfomycin‐modifying enzymes. Thereby, IncF and IncN plasmids play a predominant role. The detection of mobile fosfomycin‐resistant genes in Enterobacteriaceae has increased in recent years. Similar to the situation in (East) Asia, the most frequently detected fosfomycin‐resistant gene in Europe is fosA3. Mobile fosfomycin‐resistant genes have been detected in isolates of human, animal, food, and environmental origin which leads to a growing concern regarding the risk of spread of such bacteria, especially Escherichia coli and Salmonella, at the human–animal–environment interface.
Biologically active indolizidine alkaloids
Authors: Zhang Junmin , Morris‐Natschke Susan L. , Ma Di , Shang Xiao‐Fei , Yang Chen‐Jie , Liu Ying‐Qian , Lee Kuo‐Hsiung 
Published: October 2020

AbstractIndolizidine alkaloids are chemical constituents isolated from various marine and terrestrial plants and animals, including but not limited to trees, fungi, ants, and frogs, with a myriad of important biological activities. In this review, we discuss the biological activity and pharmacological effects of indolizidine alkaloids and offer new avenues toward the discovery of new and better drugs based on these naturally occurring compounds.
Upregulation of miR‐9 and miR‐193b over human Th17 cell differentiation
Authors: Shirani Fahimeh , Baghi Masoud , Rostamian Delavar Mahsa , Shoaraye Nejati Alireza , Eshaghiyan Amir , Nasr‐Esfahani Mohammad Hossein , Peymani Maryam , Ghaedi Kamran 
Published: October 2020

AbstractBackgroundTh17 cells are a newly discovered subset of CD4+ T cells known as key participants in various immune responses and inflammatory conditions including autoimmune diseases. Mi(cro)RNAs are a family of non‐coding RNAs that regulate numerous critical immune functions. Immuno‐miRNAs modulate cell biological processes in T cells, such as differentiation and function of Th17 cells. The aim of the present study is to investigate the expression of miR‐9‐5p, miR‐193b‐3p, and autoimmunity‐related genes during human Th17 cells differentiation.MethodsHuman naïve CD4+ T cells were purified from peripheral blood mononuclear cells (PBMCs) by magnetic cell sorting system (MACS) and their purity was checked by flow‐cytometric analysis. Naïve CD4+ T cells were cultured under Th17‐polarizing condition for 6 days. IL‐ 17 secretion was determined by means of enzyme‐linked immunosorbent assay (ELISA). Next, the expression levels of miRNAs and putative targets genes were assessed by qRT‐PCR at different time points of differentiation.ResultsOur result showed dramatic downregulation of TCF7, MAP3K1, ENTPD1, and NT5E genes during human Th17 differentiation. Polarization also had a significant inducible effect on the expression of miR‐9 and miR‐193b over differentiation of human Th17 cells. According to our results, miR‐9‐5p and miR‐193b‐3p may contribute to Th17 differentiation probably by inhibiting the expression of negative regulators of Th17 differentiation.ConclusionThis study confirmed deregulation of TCF7, MAP3K1, ENTPD1, and NT5E genes in Th17 differentiation process and introduced miR‐9 and miR‐193b as Th17 cell‐associated miRNAs, making them good candidates for further investigations.
A k‐space‐to‐image reconstruction network for MRI using recurrent neural network
Authors: Oh Changheun , Kim Dongchan , Chung Jun‐Young , Han Yeji , Park HyunWook 
Published: October 2020

PurposeReconstructing the images from undersampled k‐space data are an ill‐posed inverse problem. As a solution to this problem, we propose a method to reconstruct magnetic resonance (MR) images directly from k‐space data using a recurrent neural network.MethodsA novel neural network architecture named “ETER‐net” is developed as a unified solution to reconstruct MR images from undersampled k‐space data, where two bi‐RNNs and convolutional neural network (CNN) are utilized to perform domain transformation and de‐aliasing. To demonstrate the practicality of the proposed method, we conducted model optimization, cross‐validation, and network pruning using in‐house data from a 3T MRI scanner and public dataset called “FastMRI.”ResultsThe experimental results showed that the proposed method could be utilized for accurate image reconstruction from undersampled k‐space data. The size of the proposed model was optimized and cross‐validation was performed to show the robustness of the proposed method. For in‐house dataset (R = 4), the proposed method provided nMSE = 1.09% and SSIM = 0.938. For “FastMRI” dataset, the proposed method provided nMSE = 1.05 % and SSIM = 0.931 for R = 4, and nMSE = 3.12 % and SSIM = 0.884 for R = 8. The performance of the pruned model trained the loss function including with L2 regularization was consistent for a pruning ratio of up to 70%.ConclusionsThe proposed method is an end‐to‐end MR image reconstruction method based on recurrent neural networks. It performs direct mapping of the input k‐space data and the reconstructed images, operating as a unified solution that is applicable to various scanning trajectories.
Breast tumor segmentation in 3D automatic breast ultrasound using Mask scoring R‐CNN
Authors: Lei Yang , He Xiuxiu , Yao Jincao , Wang Tonghe , Wang Lijing , Li Wei , Curran Walter J. , Liu Tian , Xu Dong , Yang Xiaofeng 
Published: October 2020

PurposeAutomatic breast ultrasound (ABUS) imaging has become an essential tool in breast cancer diagnosis since it provides complementary information to other imaging modalities. Lesion segmentation on ABUS is a prerequisite step of breast cancer computer‐aided diagnosis (CAD). This work aims to develop a deep learning‐based method for breast tumor segmentation using three‐dimensional (3D) ABUS automatically.MethodsFor breast tumor segmentation in ABUS, we developed a Mask scoring region‐based convolutional neural network (R‐CNN) that consists of five subnetworks, that is, a backbone, a regional proposal network, a region convolutional neural network head, a mask head, and a mask score head. A network block building direct correlation between mask quality and region class was integrated into a Mask scoring R‐CNN based framework for the segmentation of new ABUS images with ambiguous regions of interest (ROIs). For segmentation accuracy evaluation, we retrospectively investigated 70 patients with breast tumor confirmed with needle biopsy and manually delineated on ABUS, of which 40 were used for fivefold cross‐validation and 30 were used for hold‐out test. The comparison between the automatic breast tumor segmentations and the manual contours was quantified by I) six metrics including Dice similarity coefficient (DSC), Jaccard index, 95% Hausdorff distance (HD95), mean surface distance (MSD), residual mean square distance (RMSD), and center of mass distance (CMD); II) Pearson correlation analysis and Bland–Altman analysis.ResultsThe mean (median) DSC was 85% ± 10.4% (89.4%) and 82.1% ± 14.5% (85.6%) for cross‐validation and hold‐out test, respectively. The corresponding HD95, MSD, RMSD, and CMD of the two tests was 1.646 ± 1.191 and 1.665 ± 1.129 mm, 0.489 ± 0.406 and 0.475 ± 0.371 mm, 0.755 ± 0.755 and 0.751 ± 0.508 mm, and 0.672 ± 0.612 and 0.665 ± 0.729 mm. The mean volumetric difference (mean and ± 1.96 standard deviation) was 0.47 cc ([−0.77, 1.71)) for the cross‐validation and 0.23 cc ([−0.23 0.69]) for hold‐out test, respectively.ConclusionWe developed a novel Mask scoring R‐CNN approach for the automated segmentation of the breast tumor in ABUS images and demonstrated its accuracy for breast tumor segmentation. Our learning‐based method can potentially assist the clinical CAD of breast cancer using 3D ABUS imaging.
Acute ischemic stroke induces magnetic resonance susceptibility signs dominated by endothelial nitric oxide synthase activation
Authors: Chen Chiao‐Chi V. , Chang Chen , Lin Ming‐Fang , Huang Guo‐Shu , Chan Wing P. 
Published: October 2020

PurposeAcute ischemic stroke induces deoxyhemoglobin accumulation around the ischemic region while activating endothelial nitric oxide synthase (eNOS) coupling and the subsequent release of nitric oxide (NO). Because deoxyhemoglobin is a natural NO spin trap, its interplay with NO could be prominent during acute stroke. Its interaction with NO has been shown to induce overt paramagnetic signals in vitro; our goal was to investigate whether this interplay can be detected using MRI.MethodsTo verify the in vivo image effects using the deoxyhemoglobin‐NO interaction during acute stroke, eNOS states were manipulated in an animal model of acute ischemia, and the susceptibility signals, cerebral perfusion, and infarction were assessed noninvasively via MR susceptibility weighted imaging (SWI).ResultsOcclusion of the right middle cerebral artery increased eNOS coupling and susceptibility signals in the ischemic cortex while abolishing regional cerebral blood flow. Pharmacological eNOS blockage led to weakened susceptibility signals in the ischemic cortex as well as worsened tissue survival. Consistently, abolishment of eNOS coupling through genetic editing reduced the regional susceptibility signals in the ischemic cortex, causing large infarcts.ConclusionUpregulation of eNOS during acute ischemia sustains tissue viability through the interaction between NO and deoxyhemoglobin. This interplay can be traced in vivo using SWI and can be considered a sensitive marker revealing the delicate oxygenation status of the ischemic tissue, therefore, guiding the management of acute stroke in clinical settings.
Unsupervised learning for magnetization transfer contrast MR fingerprinting: Application to CEST and nuclear Overhauser enhancement imaging
Authors: Kang Beomgu , Kim Byungjai , Schär Michael , Park HyunWook , Heo Hye‐Young 
Published: October 2020

PurposeTo develop a fast, quantitative 3D magnetization transfer contrast (MTC) framework based on an unsupervised learning scheme, which will provide baseline reference signals for CEST and nuclear Overhauser enhancement imaging.MethodsPseudo‐randomized RF saturation parameters and relaxation delay times were applied in an MR fingerprinting framework to generate transient‐state signal evolutions for different MTC parameters. Prospectively compressed sensing–accelerated (four‐fold) MR fingerprinting images were acquired from 6 healthy volunteers at 3 T. A convolutional neural network framework in an unsupervised fashion was designed to solve an inverse problem of a two‐pool MTC Bloch equation, and was compared with a conventional Bloch equation–based fitting approach. The MTC images synthesized by the convolutional neural network architecture were used for amide proton transfer and nuclear Overhauser enhancement imaging as a reference baseline image.ResultsThe fully unsupervised learning scheme incorporated with the two‐pool exchange model learned a set of unique features that can describe the MTC–MR fingerprinting input, and allowed only small amounts of unlabeled data for training. The MTC parameter values estimated by the unsupervised learning method were in excellent agreement with values estimated by the conventional Bloch fitting approach, but dramatically reduced computation time by ~1000‐fold.ConclusionGiven the considerable time efficiency compared to conventional Bloch fitting, unsupervised learning‐based MTC–MR fingerprinting could be a powerful tool for quantitative MTC and CEST/nuclear Overhauser enhancement imaging.