bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profiling the neurovascular unit unveils detrimental effects of osteopontin on the blood-brain barrier in acute ischemic stroke
Authors: Spitzer Daniel , Guérit Sylvaine , Pütz Tim , Khel Maryam Ibrahim , Armbrust Moritz , Dunst Maika , Macas Jadranka , Zinke Jenny , Devraj Gayatri , Jia Xiaoxiong , Croll Florian , Sommer Kathleen , Filipski Katharina , Freiman Thomas , Looso Mario , Günther Stefan , Tacchio Mariangela Di , Plate Karl Heinz , Reiss Yvonne , Liebner Stefan , Harter Patrick Nicholas , Devraj Kavi 
Published: June 2022

Abstract
Blood-brain barrier (BBB) dysfunction, characterized by degradation of BBB junctional proteins and increased permeability, is a crucial pathophysiological feature of acute ischemic stroke. Dysregulation of multiple neurovascular unit (NVU) cell types is involved in BBB breakdown in ischemic stroke that may be further aggravated by reperfusion therapy. Therefore, therapeutic co-targeting of dysregulated NVU cell types in acute ischemic stroke constitutes a promising strategy to preserve BBB function and improve clinical outcome. However, methods for simultaneous isolation of multiple NVU cell types from the same diseased central nervous system (CNS) tissue, crucial for the identification of therapeutic targets in dysregulated NVU cells, are lacking. Here, we present the EPAM-ia method, that facilitates simultaneous isolation and analysis of the major NVU cell types (endothelial cells, pericytes, astrocytes and microglia) for the identification of therapeutic targets in dysregulated NVU cells to improve the BBB function. Applying this method, we obtained a high yield of pure NVU cells from murine ischemic brain tissue, and generated a valuable NVU transcriptome database (bioinformatics.mpi-bn.mpg.de/SGD_Stroke). Dissection of the NVU transcriptome revealed Spp1, encoding for osteopontin, to be highly upregulated in all NVU cells 24 hours after ischemic stroke. Upregulation of osteopontin was confirmed in stroke patients by immunostaining, which was comparable with that in mice. Therapeutic targeting by subcutaneous injection of an anti-osteopontin antibody post ischemic stroke in mice resulted in neutralization of osteopontin expression in the NVU cell types investigated. Apart from attenuated glial activation, osteopontin neutralization was associated with BBB preservation along with decreased brain edema and reduced risk for hemorrhagic transformation, resulting in improved neurological outcome and survival. This was supported by BBB-impairing effects of osteopontin in vitro. The clinical significance of these findings is that anti-osteopontin antibody therapy might augment current approved reperfusion therapies in acute ischemic stroke by minimizing deleterious effects of ischemia-induced BBB disruption.
Effects of Furfural residues on community composition and diversity of rhizosphere microbe of seed production
Authors: Zhao Yunchen , Chen Guangquan , Yan Zhibin , Wang Zhijiang , Xiao Rang , Fu Wenjiang 
Published: June 2022

Abstract
The influence of furfural residue on rhizosphere microbiota of corn seed production after long-term cropping were studied by high-throughput sequencing and field plots. The results showed that soil of unplanted, chemical fertilizer (only) application, furfural residue application, and seasonal soil batches recruited distinct rhizosphere microbiota. The microbial community diversity and OTUs increased compared with that of unplanted soil. With exception of Ascomycota, maize plants grown under field conditions were preferentially colonized by Zygomycota in unplanted soil, Mortierellomycota in chemical fertilizer-only soil, while Basidiomycota in frufural residue-treated soil. Potential pathogens as Alternaria, Trichocladium, Bipolaris etc. were not detected, while beneficial microbes as Penicillium, Schizothecium and Rhizophlyctis were presented. Acidobacteria and Bacteroidetes increased, and Actinobacteria and Firmicutes decreased in furfural residue application. The core bacteria after long-term continuous cropping were MND1, RB41, Nitrospira, Cellvibrio, Adhaeribacter etc. The relative abundances of Clostridium, Pseudarthrobacter and Roseiflexus decreased; Haliangium, Nitrospira and MND1 increased; and Pirellula, Ellin6067 and Luteimonas reduced in different seasonal soil batches. Amendment with furfural residue promoted the development of beneficial microbes and decreased the relative abundance of pathogens. Also, the amendment increased cellulose- degrading and complex carbon-decomposing microbes, decreased the number of reductive substance- decomposing microbes, which led to a shift in microbial community structure over time and improved the rhizosphere environment. Furfural residue can be used as a soil amendment to relieve soil-borne diseases and to establish beneficial soil microbes.
Rapid epidemic expansion of the SARS-CoV-2 Omicron BA.2 subvariant during China’s largest outbreaks
Authors: Dai Dr. Yeyu Freddie 
Published: June 2022

Abstract
A complete and accurate statistical analysis of cases of contraction with SARS-CoV-2, under the conditions of strict mandatory quarantine and isolation and of a high rate of full vaccination, during the largest COVID-19 outbreaks driven by the Omicron BA.2 subvariant in China are given. SARS-CoV-2 is still new, and little is known about either its directions of variations or its laws of propagation. No country other than China has been able to disclose every case of infection in every epidemic or outbreak since April of 2020. Here, this study reveals that Omicron BA.2 subvariant can still spread very fast and wide in areas with strict “dynamic zero-COVID strategy”1 in China, that there exist cities twenty-fold differences in morbidity rates unrelated to any of the known factors contributing to incidence of infectious diseases, and that Omicron BA.2 subvariant is unpredictable in its virulence, although its severity rate of symptomatic cases is low. This analysis provides first-hand original and valuable information for further research on similar epidemics in the future. It may bring new thoughts for correction of present epidemiological theory and mathematical models. It may also give other countries time to be better prepared for the coming 6th wave driven by Omicron BA.2.
Field scale plant water relation of maize (Zea mays) under drought – impact of root hairs and soil texture
Authors: Jorda Helena , Ahmed Mutez A. , Javaux Mathieu , Carminati Andrea , Vetterlein Doris , Duddek Patrick , Vanderborght J. 
Published: June 2022

Abstract
Background and aims: Impact of drought on crop growth depends on soil and root hydraulic properties that determine the acces of plant roots to soil water. Root hairs may increase the accessible water pool but their effect depends on soil hydraulic properties and adaptions of root systems to drought. These adaptions are difficult to investigate in pot experiments that focus on juvenile plants. Methods: A wild-type and its root hairless mutant maize (Zea mays) crop were grown in the field in loam and sand substrates during two growing seasons with a large precipitation deficit. A comprehensive dataset of soil and plant properties and monitored variables was collected and interpreted using simulations with a mechanistic root water uptake model. Results: Total crop water use was similar in both soils and for both genotypes whereas shoot biomass was larger for the wild type than for the hairless mutant and did not differ between soils. Total final root length was larger in sand than in loam but did not differ between genotypes. Simulations showed that root systems of both genotypes and in both soils extracted all plant available soil water, which was similar for sand and loam, at a potential rate. Leaf water potentials were overestimated by the model, especially for the hairless mutant in sand substrate because the water potential drop in the rhizosphere was not considered. Conclusions: A direct effect of root hairs on water uptake was not observed but root hairs might influence leaf water potential dependent growth.
Machine Intelligence by Central Pivot Ranges (MICPR): An Optimal Resource Scheduling Strategy for Cloud Services
Authors: Rao Uma Maheswara , Sastry JKR 
Published: June 2022

Abstract
Alongside the increasing demand for cloud computing solutions, the other critical factor in focusing on cloud computing solutions is effective cloud resource sensing and scheduling. In the real-time scenario, there are numerous resource scheduling models available to support effective managing resource scheduling. However, resource sensing and scheduling challenges remains in the increasing complexities of background processing in the cloud servers. Thus, in this manuscript, a machine intelligence model that provides significant insights into how the load balance can be sensed and handled using the sever performance's critical metrics is proposed. The model is an automated machine intelligence (MI) approach that uses pivot range (CPR), support, and resistance models for estimating if the load of the system as per the metrics chosen is running heavy load or normal. Accordingly, the decision can be triggered automatically by MICPR to choose the fundamental resource sensing and scheduling algorithms. The experimental study of the model refers to potential ways in which the system can be feasible, and if implemented on a large scale, it can help reduce the backend load on the cloud servers.
Host-Guest Binding Selectivity of Ethylated Pillar[5]arene (EtP5A) towards Octane, 1,7-Octadiene, and 1,7-Octadiyne: A Computational Investigation
Authors: Krid Adel , Belkhiri Lotfi , Allal Hamza , Kuznetsov Aleksey , Boucekkine Abdou 
Published: June 2022

Abstract
Host−guest binding selectivity of the perethylated pillar[5]arene (EtP5A) macrocycles with aliphatic modified hydrocarbons, i.e., octane, 1,7-octadiene, and 1,7-octadiyne as guests, has been investigated computationally employing molecular docking simulations. Density Functional Theory (DFT) investigations were also performed on these host-guest complexes using the dispersion-corrected approach BLYP-D3(BJ)/TZP/COSMO calculations as implemented in the ADF program and two dispersion-corrected density functionals, ωB97XD and B97D, along with the 6-311G* basis set, coupled with the PCM solvation model as implemented in the Gaussian software. We performed analysis of the frontier molecular orbitals (FMO) and Natural Bond Orbitals (NBO), Energy Decomposition Analysis (EDA), and Non-Covalent Interaction (NCI-RDG) analysis. The study sheds light on the structures and binding energetics of EtP5A with the above-mentioned guests as well as on the physicochemical nature of the noncovalent interactions involved in these host-guest inclusion complexes. Based on the docking simulations, the EtP5A host revealed slightly better binding ability in the complex with the alkyne guest than with the octane and alkene, corroborated by the EDA analysis. The results showed that the complexation of EtP5A with the hydrocarbons is mainly governed by the interplay of electrostatic interactions and dispersive noncovalent interactions. These results agree well with NCI-RDG and NBO analysis showing that host − guest binding interactions result predominantly from electrostatic CH···π and van der Waals forces, the H-bonding being weak or not observed. The results obtained using different computational methods were found to be in good agreement and complementary.
Remimazolam besylate for the sedation of postoperative patients with invasive mechanical ventilation in the ICU: a prospective dose-response study
Authors: Chen Xiaoyan , Zhang Jiancheng , Yuan Shiying , Huang Haiyan 
Published: June 2022

Abstract
Background
This single-center study aims to determine the effective dose and safety of remimazolam besylate for the sedation of postoperative patients with invasive mechanical ventilation in the intensive care unit (ICU).
Methods
Mechanically ventilated patients admitted to the ICU after surgery were included. The Narcotrend index (NTI) was used to assess the depth of sedation, and the Richmond Agitation-Sedation Scale (RASS) was also recorded. Remimazolam besylate was administered initially at a loading dose of 0.02 mg/kg, followed by a gradual increase of 0.005 mg/kg each time until targeted depth of sedation was achieved (NTI 65–94). A maintenance dose of remimazolam besylate was administered starting at 0.2 mg/kg/h, followed by increments or subtractions of 0.05 mg/kg each time until a satisfactory depth of sedation was achieved and maintained for at least 30 minutes. The demographic data, anesthesia, surgery types, hemodynamics and respiratory parameters were recorded.
Results
Twenty-three patients were included for this study eventually over a year. A satisfactory depth of sedation could be achieved by a single intravenous infusion of remimazolam besylate at a loading dose of 0.02–0.05 mg/kg followed by a pump maintenance dose of 0.20–0.35 mg/kg/h. There were no significant changes in hemodynamic and respiratory parameters within 10 minutes after administration of remimazolam besylate. In addition, a significant correlation was observed between NTI and RASS for assessing sedation (r = 0.721, P༜0.001). NTI showed a prediction probability of RASS score of 0.817.
Conclusions
Remimazolam besylate was effective for mild/moderate sedation of postoperative invasively mechanically ventilated patients in ICU, while maintaining excellent respiratory and hemodynamic stability. The NTI could be used as a good tool for the objective evaluation of the depth of sedation and agitation.
Risk assessment of acute respiratory failure requiring advanced respiratory support using machine learning
Authors: Allen Angier , Zeng Cecilia , Tso Chak Foon , Singh Navan , Iqbal Zohora , Attwood Misty M , Gordon Veronica , Wang Cindy , Hoffman Jana 
Published: June 2022

Abstract
Background:
Acute respiratory failure (ARF) presents within a spectrum of clinical manifestations and illness severity, and mortality occurs in approximately 30% of patients who develop ARF. Early risk identification is imperative for implementation of prophylactic measures prior to ARF onset. In this study, we develop and validate a machine learning algorithm (MLA) to predict patients at risk of ARF requiring advanced respiratory support.
Methods:
This retrospective study used data from 155,725 patient electronic health records obtained from five United States community hospitals. An XGBoost classifier was developed using patient EHR data to produce risk scores at 3-hour intervals to predict the risk of ARF within 24 hours. An alert was generated only once prior to ARF onset, defined by implementation of advanced respiratory support, for patients whose risk score exceeded a predefined threshold. We used a novel time-sensitive area under the receiver operating characteristic (tAUROC) curve that integrated the timing of the alert relative to ARF onset to evaluate the accuracy of the MLA. The MLA was assessed on two testing sets and compared with oxygen saturation (SpO2) measurement and the modified early warning score (MEWS).
Results:
The MLA demonstrated significantly higher eSensitivity and specificity operating points on the temporal testing and external validation sets (tAUROC of 0.858/0.883, respectively) than SpO2 (0.771/0.810) and MEWS (0.676/0.774) for prediction of ARF requiring advanced respiratory support. The MLA also achieved lower false positive rates than SpO2 and MEWS at these operating points.
Conclusions:
The MLA predicts patients at risk of ARF requiring advanced respiratory support and achieves higher accuracy and produces earlier alerts than the use of SpO2 or MEWS. Importantly for clinical practice, the MLA has a lower false positive rate than these comparators while maintaining high sensitivity and specificity.
A Deep CNN Approach for Islanding Detection of Integrated DG with Time Series Data and Scalogram
Authors: Reddy Ch Rami , G B Srikanth , Kalyan Ch Naga Sai , Va P Srinivasa , Kumar D Ravi , Kumari B Seshu , Kondalu M 
Published: June 2022

Abstract
The ever increasing demand of electricity leads to the advancement of Distributed Generation (DG). Almost the DG sources are renewable in nature. One of the major complications with high penetration of DG sources is islanding. The islanding may damage the clients and their equipment. As per the IEEE 1547 DG interconnection standards, the islanding will be identified in a period of two seconds and the DG must be turned off. In this paper an advanced islanding detection process stand on deep learning technique with Continuous Wavelet Transforms (CWT) and Convolution Neural Networks (CNN) is implemented. This approach basically transformes the time series information into scalogram images, later the images are used to train and to test the islanding and non islanding events. The outcomes are correlated with the Artificial Neural Networks (ANN) and Fuzzy logic methods. The comparison shows that the proposed deep learning approach efficiently detects the islanding and non islanding events.
Unilateral angle-closure glaucoma in combination with neurofibromatosis: a case report
Authors: Jiang Mingming , Zhang Jing , Wan Xiaomei , Ding Yichao , wang yuan 
Published: June 2022

Abstract
Background: Neurofibromatosis I(NFI) is an autosomal dominant genetic disease that causes multi-system damage. It is rare have both angle-closure glaucoma and NF, especially in pediatric patients. We report a case of unilateral angle -closure glaucoma with NFI.Case presentation: A 5-year-old girl accompanied by a large subcutaneous soft mass and multiple coffee-milk spots scattered presented with low vision ,increased IOP and angle-closure in her right eye. Slit-lamp examination demonstrated multiple Lisch nodules in both eye. In her right eye, Ectropion uveae were observed at the top and bottom margins of the pupi. There were no abnormalities on MRI of skull and orbit. Finally ,trabeculectomy was performed on the right eye, after which the right eye showed a stable IOP.Conclusions: The incidence of NFI with angle-closure glaucoma is low and clinically rare. Early diagnosis and treatment can generally achieve good results, but the long-term efficacy still needs further follow-up, especially the contralateral eye.
Microstructure and Corrosion Behavior of Friction Surfaced 304L Austenitic Stainless Steels
Authors: Agiwal Hemant , Sridha Kumar , Pfefferkorn Frank , Yeom Hwasung 
Published: June 2022

Abstract
Friction surfacing is a solid-state deposition process that provides microstructural and mechanical property benefits over fusion-based deposition methods as a result of the lower heat input and hot working. The study examines microstructure and corrosion properties for friction surfaced 304L stainless steel consumable rods on 304L stainless steel substrates. Microstructural characterization revealed fine-grained microstructure with distributed strain-induced martensite and high residual compressive stresses. Corrosion studies of friction surfaced specimens were carried out by exposure to FeCl3 and MgCl2 solutions per ASTM G48 and ASTM G36 standards, respectively. The corrosion tests showed friction surfacing led to shallower and smaller pits than the uncoated substrate, however, the pit number density was higher in the friction surfaced specimens. The microstructural transformations during friction surfacing are beneficial to mitigating pitting corrosion and potentially chloride-induced stress corrosion cracking (CISCC).
Iron oxide (Fe2 O3 ) nanoparticles alleviate PEG-simulated drought stress in grape (Vitis vinifera L.) plants by regulating leaf antioxidants
Authors: Bidabadi Siamak Shirani , Sabbatini Paolo , VanderWeide Josh 
Published: June 2022

Abstract
Iron nanoparticles (Fe NPs) have a wide array of biological and medical applications. In agriculture, Fe NPs have the potential to be used as an innovative technique to alleviate Fe deficiency in various crops, such as grape. However, the effect of Fe NPs on alleviating stresses in grapevine are unexplored. The aim of this study was to evaluate the efficiency of Fe NPs in protecting ‘Asgari’ seedless grape (Vitis vinifera L.) against oxidative stress induced by polyethylene glycol (PEG)-induced drought exposure. Here, we compared six concentrations of Fe NPs to both well-watered and drought-stressed grape plants and evaluated physiological and biochemical parameters in leaves after 30-days of exposure. Our results revealed that physiological indices of plant health such as chlorophyll content, chlorophyll fluorescence (Fv/Fm), and leaf relative water content (RWC) decreased with increased production of H2O2 caused by drought stress. MDA, proline, non-enzymatic (e.g. AsA and GSH) and enzymatic antioxidants (including MDHAR, DHAR, CAT, GPX, GR and GST) exhibited varied responses. Increasing levels of Fe NPs up to 10 µM caused an increase in chlorophyll content and fluorescence under PEG-induced drought stress. Moreover, Fe NPs induced antioxidant protection by reducing MDA and H2O2 generation, and enhancing the concentration of the non-enzymatic antioxidants, such as GSH/GSSG ratio and ascorbate. Enzymatic activities reported a wide response range, with increases to CAT, GPX, GR, MDHAR and DHAR activities and decreases to GST and APX activities. In conclusion, this study demonstrated that Fe NPs have the potential to be used as an effective method in reducing the negative impact of drought stress in grapevine.
Phylogrouping and pathogrouping of Potato virus Y isolates from pepper plants in Turkey
Authors: TOPKAYA Serife , Gibbs Adrian J 
Published: June 2022

Abstract
Potato virus Y (PVY) causes yield loss of pepper (Capsicum) crops worldwide, but little is known of its molecular diversity in pepper in Turkey or elsewhere. During 2016 and 2017, pepper crops were surveyed in three different provinces of Turkey, and plants with virus-like symptoms were collected. Four hundred and twenty one samples were collected and 35 found to be infected with PVY by DAS-ELISA using PVY-specific antisera. The positive samples were tested by RT-PCR and viral genes of some were sequenced. Conventional comparisons indicated that eight of the isolates were probably from phylogroup C, and three from pathogroup N-Wi, which is part of phylogroup R1. Other methods of using sequence data were tested in an attempt to identify how PVY, a multiply recombinant virus, can be most economically phylogrouped; one using Genbank searches and a database of over 600 PVY complete genomic ORF sequences was found to be effective and objective. The same data confirmed that sequencing the P1 and CP genes is more cost effective for phylogrouping PVY than other gene combinations. This is the first report of recombinant PVY isolates in pepper plants in Turkey.