bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images
Authors: Ranjbarzadeh Ramin , Bagherian Kasgari Abbas , Jafarzadeh Ghoushchi Saeid , Anari Shokofeh , Naseri Maryam , Bendechache Malika 
Published: May 2021

AbstractBrain tumor localization and segmentation from magnetic resonance imaging (MRI) are hard and important tasks for several applications in the field of medical analysis. As each brain imaging modality gives unique and key details related to each part of the tumor, many recent approaches used four modalities T1, T1c, T2, and FLAIR. Although many of them obtained a promising segmentation result on the BRATS 2018 dataset, they suffer from a complex structure that needs more time to train and test. So, in this paper, to obtain a flexible and effective brain tumor segmentation system, first, we propose a preprocessing approach to work only on a small part of the image rather than the whole part of the image. This method leads to a decrease in computing time and overcomes the overfitting problems in a Cascade Deep Learning model. In the second step, as we are dealing with a smaller part of brain images in each slice, a simple and efficient Cascade Convolutional Neural Network (C-ConvNet/C-CNN) is proposed. This C-CNN model mines both local and global features in two different routes. Also, to improve the brain tumor segmentation accuracy compared with the state-of-the-art models, a novel Distance-Wise Attention (DWA) mechanism is introduced. The DWA mechanism considers the effect of the center location of the tumor and the brain inside the model. Comprehensive experiments are conducted on the BRATS 2018 dataset and show that the proposed model obtains competitive results: the proposed method achieves a mean whole tumor, enhancing tumor, and tumor core dice scores of 0.9203, 0.9113 and 0.8726 respectively. Other quantitative and qualitative assessments are presented and discussed.
Polymerized albumin restores impaired hemodynamics in endotoxemia and polymicrobial sepsis
Authors: Belcher Donald A. , Williams Alexander T. , Palmer Andre F. , Cabrales Pedro 
Published: May 2021

AbstractFluid resuscitation following severe inflammation-induced hypoperfusion is critical for the restoration of hemodynamics and the prevention of multiorgan dysfunction syndrome during septic shock. Fluid resuscitation with commercially available crystalloid and colloid solutions only provides transient benefits, followed by fluid extravasation and tissue edema through the inflamed endothelium. The increased molecular weight (M.W.) of polymerized human serum albumin (PolyHSA) can limit fluid extravasation, leading to restoration of hemodynamics. In this prospective study, we evaluated how fluid resuscitation with PolyHSA impacts the hemodynamic and immune response in a lipopolysaccharide (LPS) induced endotoxemia mouse model. Additionally, we evaluated fluid resuscitation with PolyHSA in a model of polymicrobial sepsis induced by cecal ligation and puncture (CLP). Resuscitation with PolyHSA attenuated the immune response and improved the maintenance of systemic hemodynamics and restoration of microcirculatory hemodynamics. This decrease in inflammatory immune response and maintenance of vascular wall shear stress likely contributes to the maintenance of vascular integrity following fluid resuscitation with PolyHSA. The sustained restoration of perfusion, decrease in pro-inflammatory immune response, and improved vascular integrity that results from the high M.W. of PolyHSA indicates that a PolyHSA based solution is a potential resuscitation fluid for endotoxic and septic shock.
A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance
Authors: Sayeed Alqamah , Choi Yunsoo , Eslami Ebrahim , Jung Jia , Lops Yannic , Salman Ahmed Khan , Lee Jae-Bum , Park Hyun-Ju , Choi Min-Hyeok 
Published: May 2021

AbstractIssues regarding air quality and related health concerns have prompted this study, which develops an accurate and computationally fast, efficient hybrid modeling system that combines numerical modeling and machine learning for forecasting concentrations of surface ozone. Currently available numerical modeling systems for air quality predictions (e.g., CMAQ) can forecast 24 to 48 h in advance. In this study, we develop a modeling system based on a convolutional neural network (CNN) model that is not only fast but covers a temporal period of two weeks with a resolution as small as a single hour for 255 stations. The CNN model uses meteorology from the Weather Research and Forecasting model (processed by the Meteorology-Chemistry Interface Processor), forecasted air quality from the Community Multi-scale Air Quality Model (CMAQ), and previous 24-h concentrations of various measurable air quality parameters as inputs and predicts the following 14-day hourly surface ozone concentrations. The model achieves an average accuracy of 0.91 in terms of the index of agreement for the first day and 0.78 for the fourteenth day, while the average index of agreement for one day ahead prediction from the CMAQ is 0.77. Through this study, we intend to amalgamate the best features of numerical modeling (i.e., fine spatial resolution) and a deep neural network (i.e., computation speed and accuracy) to achieve more accurate spatio-temporal predictions of hourly ozone concentrations. Although the primary purpose of this study is the prediction of hourly ozone concentrations, the system can be extended to various other pollutants.
Activity of immunoproteasome inhibitor ONX-0914 in acute lymphoblastic leukemia expressing MLL–AF4 fusion protein
Authors: Jenkins Tyler W. , Downey-Kopyscinski Sondra L. , Fields Jennifer L. , Rahme Gilbert J. , Colley William C. , Israel Mark A. , Maksimenko Andrey V. , Fiering Steven N. , Kisselev Alexei F. 
Published: May 2021

AbstractProteasome inhibitors bortezomib and carfilzomib are approved for the treatment of multiple myeloma and mantle cell lymphoma and have demonstrated clinical efficacy for the treatment of acute lymphoblastic leukemia (ALL). The t(4;11)(q21;q23) chromosomal translocation that leads to the expression of MLL–AF4 fusion protein and confers a poor prognosis, is the major cause of infant ALL. This translocation sensitizes tumor cells to proteasome inhibitors, but toxicities of bortezomib and carfilzomib may limit their use in pediatric patients. Many of these toxicities are caused by on-target inhibition of proteasomes in non-lymphoid tissues (e.g., heart muscle, gut, testicles). We found that MLL–AF4 cells express high levels of lymphoid tissue-specific immunoproteasomes and are sensitive to pharmacologically relevant concentrations of specific immunoproteasome inhibitor ONX-0914, even in the presence of stromal cells. Inhibition of multiple active sites of the immunoproteasomes was required to achieve cytotoxicity against ALL. ONX-0914, an inhibitor of LMP7 (ß5i) and LMP2 (ß1i) sites of the immunoproteasome, and LU-102, inhibitor of proteasome ß2 sites, exhibited synergistic cytotoxicity. Treatment with ONX-0914 significantly delayed the growth of orthotopic ALL xenograft tumors in mice. T-cell ALL lines were also sensitive to pharmacologically relevant concentrations of ONX-0914. This study provides a strong rationale for testing clinical stage immunoproteasome inhibitors KZ-616 and M3258 in ALL.
Observing deep radiomics for the classification of glioma grades
Authors: Kobayashi Kazuma , Miyake Mototaka , Takahashi Masamichi , Hamamoto Ryuji 
Published: May 2021

AbstractDeep learning is a promising method for medical image analysis because it can automatically acquire meaningful representations from raw data. However, a technical challenge lies in the difficulty of determining which types of internal representation are associated with a specific task, because feature vectors can vary dynamically according to individual inputs. Here, based on the magnetic resonance imaging (MRI) of gliomas, we propose a novel method to extract a shareable set of feature vectors that encode various parts in tumor imaging phenotypes. By applying vector quantization to latent representations, features extracted by an encoder are replaced with a fixed set of feature vectors. Hence, the set of feature vectors can be used in downstream tasks as imaging markers, which we call deep radiomics. Using deep radiomics, a classifier is established using logistic regression to predict the glioma grade with 90% accuracy. We also devise an algorithm to visualize the image region encoded by each feature vector, and demonstrate that the classification model preferentially relies on feature vectors associated with the presence or absence of contrast enhancement in tumor regions. Our proposal provides a data-driven approach to enhance the understanding of the imaging appearance of gliomas.
An unusual reaction mode of 1-phenylpyrazolidinones toward diazonaphthalen-2(1H)-ones featuring cascade C(sp2)–H and C(sp3)–H bond cleavage
Authors: Wang Muhua , Zhang Linghua , Chen Xi , Zhang Xinying , Fan Xuesen 
Published: May 2021

Herein, a novel synthesis of pyrazolidinone fused 1,3-benzooxazepine derivatives via a formal [4 + 3] annulation reaction of 1-phenylpyrazolidinones with diazonaphthalen-2(1H)-ones is presented.
Progress of zinc oxide‐based nanocomposites in the textile industry
Authors: Huang Ruihang , Zhang Siyang , Zhang Wen , Yang Xiaoming 
Published: May 2021

AbstractTextile materials have been enriched in function at the composite level with continuous developments in the textile industry. Zinc oxide (ZnO) nanoparticles (ZnO‐NPs) are strongly influenced by ultraviolet (UV) filter, antifungal, high catalysis, and semiconductor/piezoelectric coupling characteristics. Therefore, the antibacterial property and UV resistance of ZnO‐NP materials are zcomprehensively analysed to provide a basis for applying ZnO‐NP in the textile industry. In addition, the textile preparation and application of ZnO‐NP in piezoelectric power generation is discussed. Based on relevant documents for ZnO‐textile industry applications, scanning electron microscopy analysis, biological activity analysis, and UV transmittance analysis of textiles containing composite materials prove that textiles based on ZnO‐based composite materials (ZnO‐NP materials) have antibacterial properties and UV resistance. The antibacterial property and UV resistance of ZnO‐NP materials are analysed comprehensively to provide a basis for applying ZnO‐NP in the textile industry. After the photocatalytic reaction, its practical application as slurry type suspensions is limited because of the difficulty of separating the catalyst particles. In terms of its piezoelectric power generation characteristics, intensity of current voltage analysis and X‐ray diffraction analysis reveal that textiles based on ZnO‐NP materials have obvious semiconductor characteristic and obvious current enhancement signals locally, indicating that the textiles can achieve better piezoelectric properties.
Two‐way constraint network for RGB‐Infrared person re‐identification
Authors: Zeng Haitang , Hu Weipeng , Chen Dihu , Hu Haifeng 
Published: May 2021

AbstractRGB‐Infrared person re‐identification (RGB‐IR Re‐ID) is a task aiming to retrieve and match person images between RGB images and IR images. Since most surveillance cameras capture RGB images during the day and IR images at night, RGB‐IR Re‐ID is helpful when checking day and night surveillance for criminal investigations. Previous related work often only extracts sharable and identity‐related features in images for identification. Few researches specifically extract and make use of features that do not have the ability to distinguish identity, e.g. identity‐unrelated features derived from background and modality. In this Letter, we propose a novel and concise RGB‐IR Re‐ID network named two‐way constraint network (TWCN). Compared with traditional Re‐ID networks, TWCN not only extracts and utilises identity‐related features but also novelly makes full use of identity‐unrelated features to improve the accuracy of the experiment. TWCN uses a reverse‐triplet loss to extract identity‐unrelated features, and proposes an orthogonal constraint to remove identity‐unrelated information from identity‐related features, which improves the purity of identity‐related features. In addition, a correlation coefficient synergy and central clustering (CCSCC) loss is introduced into TWCN to extract identity‐related features effectively. Extensive experiments have been conducted to prove our method is effective.
Infrared spectra of complex organic molecules in astronomically relevant ice matrices
Authors: Terwisscha van Scheltinga Jeroen , Marcandalli Giulia , McClure Melissa K. , Hogerheijde Michiel R. , Linnartz Harold 
Published: May 2021

Context. Infrared spectroscopy of star and planet forming regions is at the dawn of a new age with the upcoming James Webb Space Telescope (JWST). Its high resolution and unprecedented sensitivity allows us to probe the chemical complexity of planet forming regions, such as dense clouds, embedded protostars, and protoplanetary disks, both in the solid state and gas phase. In support of these observations, laboratory spectra are required to identify complex organic molecules in the ices that cover the dust grains in these regions.
Aims. This study aims to provide the necessary reference spectra to firmly detect methyl formate (HCOOCH3) in the different evolutionary stages of star and planet forming regions. Methyl formate is mixed in astronomically relevant matrices, and the peak positions, full width at half maximum, and relative band intensities are characterized for different temperatures to provide an analytical tool for astronomers.
Methods. Methyl formate was deposited at 15 Kelvin on a cryogenically cooled infrared transmissive window under high-vacuum conditions. Specifically, methyl formate was deposited pure and mixed with CO, H2CO, CH3OH, H2O, and CO:H2CO:CH3OH combined. The sample was linearly heated until all solid-state constituents were desorbed. Throughout the experiment, infrared spectra were acquired with a Fourier transform infrared spectrometer in the range from 4000 to 500 cm−1 (2.5–20 μm) at a spectral resolution of 0.5 cm−1.
Results. We present the characterization of five solid-state methyl formate vibrational modes in pure and astronomically relevant ice matrices. The five selected vibrational modes, namely the C=O stretch (5.804 μm), the C−O stretch (8.256 μm), CH3 rocking (8.582 μm), O−CH3 stretching (10.98 μm), and OCO deformation (13.02 μm), are best suited for a JWST identification of methyl formate. For each of these vibrational modes, and each of the mixtures the temperature versus spectra heatmaps, peak position versus full width at half maximum and relative band intensities are given. All spectra are publicly available on the Leiden Ice Database. Additionally, the acquired reference spectra of methyl formate are compared with archival Spitzer observations of HH 46. A tentative detection of methyl formate provides an upper limit to the column density of 1.7 × 1017 cm−2, corresponding to an upper limit relative to water of ≤2.2% and ≤40% with respect to methanol.
Accuracy and Reliability of Pulse O2 Saturation Measured by a Wrist-worn Oximeter
Authors: Hermand Eric , Coll Clemence , Richalet Jean-Paul , Lhuissier Francois J. 
Published: May 2021

AbstractThis study aims to evaluate the accuracy of the Garmin Forerunner 245 heart rate (HR) and pulse O2 saturation (SpO2) sensors compared with electrocardiogram and medical oximeter, from sea level to high altitude. Ten healthy subjects underwent five tests in normoxia and hypoxia (simulated altitudes from 3000 to 5500 m), consisting in a 5-min rest phase, followed by 5-min of mild exercise. Absolute error (±10 bpm for HR and ±3% for SpO2, around criterion) and intraclass correlations (ICC) were calculated. Error rates for HR remained under 10%, except at 3000 m, and ICCs evidenced a good reliability between Garmin and criterion. Overall SpO2 was higher than criterion (P<0.001) with a >50% error rate (>80% above 4800 m), and a poor reliability with criterion. The Garmin device displayed acceptable HR data at rest and exercise for all altitudes, but failed to provide trustworthy SpO2 values, especially at high altitude, where a pronounced arterial O2 desaturation could lead to acute mountain sickness in hypoxia-sensitive subjects, and its life-threatening complications; moreover, readings of overestimated SpO2 values might induce trekkers into further hazardous behavior by pursuing an ascent while being already at risk. Therefore, its use to assess SpO2 should be proscribed in altitude for acclimatization evaluation.
Association Between Urinary Stress Incontinence and Levator Avulsion Detected by 3D Transperineal Ultrasound
Authors: Zhong Chunyan , Hu Pan , Ran Suzhen , Tang Jing , Xiao Chunmei , Lin Yun , Zhang Xiaohang , Rong Yao , Liu Mingbo 
Published: May 2021

Abstract
Purpose To determine the association between levator avulsion and urinary stress incontinence (USI) by 3/4D transperineal ultrasound.
Materials and Methods 842 patients who were admitted to our hospital from 2016 to 2019 were recruited for our study. 3D/4D transperineal ultrasound was performed. After standard interview and clinical evaluation, general conditions and levator hiatus data were collected and measured to compare with each group. The odds ratio (OR) of USI symptoms or ultrasound features with levator avulsion were calculated.
Results A total of 593 women were studied: 204 suffered from levator avulsion (96 cases of left-side avulsion, 80 cases of right-side avulsion and 28 cases of bilateral avulsion) and 389 women had no avulsion. The gravidity and episiotomy conditions of the avulsion groups were significantly different from the no-avulsion group. Significant differences were found in the transverse diameters and anteroposterior diameters between the levator avulsion group and the no-avulsion group, but there was no difference among the avulsion groups, regardless of whether the patient was at rest or performing the Valsalva maneuver. Interestingly, a significant difference was found in the presence of USI symptoms between the uni-avulsion group and the no-avulsion group. The odds ratio (OR) of USI symptoms in the uni-avulsion group is 2.786 (95 %CI, 1.663–4.669), but 0.939 (95 %CI, 0.276–3.199) for the bilateral avulsion and no-avulsion groups.
Conclusion Unilateral levator avulsion may be a risk factor for urinary stress incontinence.
New Phosphorylating Agents for the Synthesis of Phosphatidyl­ethanolamines
Authors: Okauchi Tatsuo , Tsubaki Kouta , Yamanaka Tomoki , Hisamitsu Takuya , Shimooka Hirokazu , Kitamura Mitsuru 
Published: May 2021

AbstractThe preparation of three novel phosphorylating agents and their application toward the synthesis of phosphatidylethanolamines is described. These reagents are stable to air and moisture, and phosphorylate glycerols in good yield. The experimental procedures using these phosphorylating agents are simple. Moreover, the appropriate reagent can be selected based on the desired functional groups of the targeted phosphatidylethanolamine.
Serum Concentration of Myelin Basic Protein as a Prognostic Marker in Mild-to-moderate Head Injury Patients: A Prospective Study in a Tertiary Care Center
Authors: Singh Ashvamedh , Singh Kulwant , Sahu Anurag , Prasad R. S. , Pandey N. , Dhar Sambuddha 
Published: May 2021

Abstract
Objective To estimate the level of myelin basic protein (MBP) and look for its validity in outcome prediction among mild-to-moderate head injury patients.
Materials and Methods It was a prospective study done at the Department of Neurosurgery, Institute of Medical Sciences, Banaras Hindu University from Jan 2018 to July 2019. All patients who presented to us within 48 hours of injury with mild-to-moderate head injury with apparently normal CT brain were include in the study. The serum sample were collected on the day of admission and 48 hours later, and patients were treated with standard protocols and observed 6 months postdischarge.
Results Of the 32 patients enrolled, we observed mean MBP level was higher for severity of brain damage, but not associated with age, mode of injury, and radiological diagnosis. Mean MBP levels were not statistically associated with Glasgow coma scale (GCS) score at admission but was correlated to outcome with p < 0.05, with sensitivity of 50% and specificity 72%, that is, patients with good outcome have lower mean MBP levels.
Conclusion MBP as per our analysis can be used as a prognostic marker in patients with head injury. It is not the absolute value rather a trend showing rise in serum MBP levels, which carries a significant value in outcome prediction.
Clinical, Surgical and Outcome Predictive Factor Analysis of Operated Acute Subdural Hematoma Cases: A Retrospective Study of 114 Operated Cases at Tertiary Centre
Authors: Singh Rahul , Prasad Ravi Shankar , Singh Kulwant , Sahu Anurag , Pandey Nityanand 
Published: May 2021

Abstract
Objective To analyze clinical, surgical and outcome predictive factors of operated acute subdural hematoma (SDH) cases for prognostication and surgical outcome prediction.
Material and Methods This retrospective study includes 114 patients operated for acute SDH in the Department of Neurosurgery of IMS BHU, Varanasi, India, a tertiary care center, between 1 August 2018 and 1 November 2019. Each patient was evaluated for age, sex, mode of injury, localization of hematoma, clinical presentation, comorbidity, severity of injury, best motor response, CT findings, and Glasgow outcome scale (GOS) at discharge. The outcome was also evaluated by further making a dichotomized group using GOS in death/dependent (1–3) versus independent (4–5). Statistical tests were done using the GraphPad Prism version 8.3.0.
Results The most common age group operated upon in this study was the 40 to 60 years age group (n = 45, 39.48%). Males were 78% with male to female ratio of 3.56:1. The most common clinical presentation was altered sensorium (98.25%). The most common comorbidity was hypertension (n = 32, 28.07%). GCS at admission, severity of injury, pupillary changes, and best motor response (p < 0.0001) were significantly associated with surgical outcome.
Conclusion GCS at admission, severity of injury, pupillary changes, and best motor response were significantly (p < 0.05) associated with surgical outcome. Age and gender of patients were not found to be significantly associated.