bluuebunny/crossref_metadata_2025_split huggingface dataset:
In-situ generation of hydroxyl radicals by B-doped TiO2 for efficient photocatalytic degradation of acetaminophen in wastewater
Authors: Xiao Caofan , Chen Xueqi , Tao Xiumei , Liu Xian , Wang Xun , Zhu Lei 
Published: June 2022

Abstract
Acetaminophen (AP) is a widely used antipyretic analgesic belonging to the class of PPCPs, which is difficult to be effectively degraded by traditional water treatment processes. However, photocatalytic technology may be an effective approach. Herein, B-doped TiO2 photocatalytic materials were synthesized by sol-gel method, calcinated at 600℃ for 2 h, investigated by XRD, TEM, XPS and other characterization methods. The photocatalytic efficiency and factors affecting the photocatalytic activity were assessed by degradation of AP under 365 nm UV light. Compared with naked TiO2, 4%B-TiO2 nanopowder had smaller grain size, higher porosity and lower bandgap energy of 3.11 eV. Scavenging experiments and ESR results showed that •OH was the principal active species. Hence, the degradation efficiency of AP was as high as 98.8% in 30 min when adopting 10 mg/L AP initial concentration and 1 g/L 4%B-TiO2 loading, owing to efficient •OH generated by B-TiO2.
SIRT2 promotes invasion and metastasis of osteosarcoma cells via inhibiting the degradation of Snail
Authors: tian yonghao , liu ruijuan , gao zhixiao , hou xiaoyan , liu xinyu , zhang weifang 
Published: June 2022

Abstract
Osteosarcomas (OS) are highly metastatic and usually lead to poor outcome. Epithelial-mesenchymal transition (EMT) is reported as a critical event in metastasis. SIRT2 exerts dual functions in many different tumors. However, the underlying molecular mechanisms of SIRT2 in osteosarcoma cell metastasis and EMT have not been fully explored. In this study, we confirmed that SIRT2 was highly-expressed in human osteosarcoma MG63 and Saos-2 cell lines. Knockdown of SIRT2 inhibited and overexpression of SIRT2 enhanced migration and invasion of osteosarcoma cells. Moreover, SIRT2 positively regulated EMT and increased the protein levels of mesenchymal markers N-cadherin, Vimentin and MMP2, MMP9. A xenograft mouse model showed that SIRT2 knockdown in osteosarcomas cells led to reduced tumor growth and impaired lung and liver metastasis in vivo. Furthermore, we showed that SIRT2 interacted with and up-regulated the protein level of EMT-associated transcription factor Snail. SIRT2 inhibited the degradation of Snail via its deacetylase activity. In conclusion, SIRT2 plays a crucial role in osteosarcomas metastasis by inhibiting Snail degradation and may serve as a novel therapeutic target to manage osteosarcomas.
CBL-interacting protein kinases (CIPKs) in Chickpea: Genome- wide identification, structure and expression analysis under abiotic stresses and development
Authors: Poddar Nikita , Deepika Deepika , Singh Amarjeet , Kumar Shailesh 
Published: June 2022

Abstract
Calcineurin B-like proteins (CBL)-interacting protein kinases (CIPKs) regulate the developmental processes, hormone signal transduction and stress responses in plants. Although the genome sequence of chickpea is available, information related to the CIPK gene family is missing in this important crop plant. Here, a total of 22 CIPK genes were identified and characterized in chickpea. We found a high degree of structural and evolutionary conservation in the chickpea CIPK family. Our analysis showed that chickpea CIPKs have evolved with dicots from common ancestors, and extensive gene duplication events have played an important role in the evolution and expansion of the CIPK gene family in chickpea. The three-dimensional structure of chickpea CIPKs was described by protein homology modelling. Most CIPK proteins are localized in the cytoplasm and nucleus, as predicted by in-silico subcellular localization. Promoter analysis revealed various cis-regulatory elements related to plant development, hormone signaling, and abiotic stresses. RNA-seq expression analysis indicated that CIPKs are significantly expressed through a spectrum of developmental stages, tissue/organs that hinted at their important role in plant development. The qRT-PCR analysis revealed that several CaCIPK genes had specific and overlapping expressions in different abiotic stresses like drought, salt, and ABA, suggesting the important role of this gene family in abiotic stress signaling in chickpea. Thus, this study provides an avenue for detailed functional characterization of the CIPK gene family in chickpea and other legume crops.
Key traits influencing wind resistance of Eucalyptus camaldulensis
Authors: Xiu-hua Shang , Pei-jian Zhang , Guo Liu , Zhi-hua Wu 
Published: June 2022

Abstract

Background
Wind is an important driving factor influencing forest structure, ecology, and the carbon cycle in temperate and tropical regions. Damage from typhoons poses a significant threat to eucalyptus production in coastal regions of southeast China. However, few strategies have been used and account for key traits impact on wind damage/resistance of eucalyptus. To identify key factors affecting eucalyptus wind resistance, 20 Eucalyptus camaldulensis genotypes were selected, and wind damage indices and traits were measured and evaluated using correlation analysis and principal component analysis.
Results
We identified a correlation between tree traits, wind damage indices, and the traits related to H, V, FP BT, FL, and FW. Five PCs from the above-mentioned traits were obtained and could represent the standing tree traits explained by PCA. PCs and tree-pulling variables were further used for typical correlation and path analyses. Canonical correlation analysis showed the top two canonical correlation coefficients were 0.9547 and 0.9012, respectively, while PC2 reflected that the growth traits were the main trait affecting pull tree variables. The PA-OV model and its modifications with PC functions and tree-pulling variables were introduced and developed for wind resistance estimation. The fitting effect of the two models and the observed data was good, with a P-value of 1.000, RMSEA of 0.000, and other goodness of fit indices over 0.9. Based on effects from model 2, PC4 had the greatest impact on tree-pulling variables. Therefore, our results implied that PC4, composed of holocellulose content, lignin, and fibre width, was the most important factor affecting standing tree stability under windy conditions.
Conclusion
This study provides insights into forest management and planning in coastal typhoon prone areas. Determining the effect of wind on trees can expand our understanding of the factors that contribute to wind damage, thereby improving management practices.
Groundwater storage change estimation using GRACE satellite data in the Helmand River Basin of Afghanistan
Authors: Nazari Aref , Zaryab Abdulhalim , Ahmadi Abdullah 
Published: June 2022

Abstract
Understanding dynamic changes of groundwater storage and quantifying the trends of groundwater fluctuations in the Helmand River Basin (HRB) aquifers, where the groundwater is the main source for drinking and irrigation applications is significantly important for effective management of groundwater resources. This case study quantifies the changes in groundwater storage over 18 years (i.e., from 2003 to 2021) in the HRB by employing the Gravity Recovery and Climate Experiment (GRACE) observations and Global Land Data Assimilation System (GLDAS) data due to sparse groundwater monitoring networks and lack of ground-based information. The data of observation wells was used to validate the results of the GRACE and GLDAS outputs. The results indicate that changes in groundwater storage on average from 2003 to 2021 are equal to (-112.4 ± 237.14 mm or -2.048 ± 4.32 km3/year). In average, during 2003 to 2021 groundwater table decline was -6.10 m in the HRB. The study indicated relatively strong correlation (0.75) between the GRACE derived data and direct in situ measurements. This study highlights the effectiveness of the GRACE-derived data for the reliable estimation of groundwater storage changes in the HRB and may contribute to sustainable groundwater resources management in the region.
Climate Change and Its Impact on Agricultural GDP Growth in Ethiopia: a Time Series Analysis
Authors: Mammo Behailu Tamiru 
Published: June 2022

Abstract
Climate change is now a global phenomenon with growth, poverty, food security, and stability implications, and is one of the greatest challenges the world is facing today. The economic impact of climate change mainly depends on the sectoral composition of the economy. That is certain sectors like agriculture are more sensitive to climate change and the associated variability. The main objective of this paper is to investigate the impact of climate change on agricultural gross domestic product growth in Ethiopia. This study uses time-series annual data from 1992/93to 2017/18 and, an effort is made to identify the long run and short-run impact of climate change in Ethiopia using an autoregressive distributed lag (ARDL) and error correction methods. The results of the study provide evidence that climate change and variability affect real agricultural gross domestic product growth negatively in the long run. The coefficient of the error term that captures the speed of adjustment toward the long-run equilibrium is found with the correct sign and magnitude. The overall findings of the study underlined the importance of building resilience to climate change and minimizing the adverse impacts of climate change to promote agricultural output and hence economic growth in Ethiopia.
Pregnancy and Childbirth Outcomes of Gestational Diabetes Mellitus: A Retrospective Cohort Study
Authors: Shirzadfardjahromi Malihe , Shekari Mitra , Ranjbar Amene , Mehrnoush Vahid , Darsareh Fatemeh , Roozbeh Nasibeh 
Published: June 2022

Abstract
Background: Understanding the various outcomes of gestational diabetes mellitus (GDM) is essential for initiating a cascade of preparatory steps to address them. Therefore, we aimed to evaluate the pregnancy and childbirth outcomes of GDM.Methods: We retrospectively assessed singleton pregnant mothers diagnosed with GDM who gave birth at Khaleej-e-Fars Hospital (a tertiary hospital) in Bandar Abbas, Iran, between January 1st, 2020, and January 1st, 2022. Records of women with pre-existing diabetes mellitus, chronic hypertension, cardiovascular disease, thyroid dysfunction, preeclampsia, abnormal placentation (previa or acreta), severe anemia (hemoglobin≤7), infertility, and COVID-19 at the time of admission were excluded. Pregnancy and childbirth outcomes included the incidence of the need for induction of labor, placenta abruption, preterm birth, intrauterine growth restriction (IUGR), intrauterine fetal death (IUFD), meconium fluid, fetal distress, methods of delivery, perineal lacerations, postpartum hemorrhage, childbirth injury, shoulder dystocia, macrosomia, low birth weight, congenital malformation, neonatal asphyxia, need for cardiac, respiratory resuscitation, transfer to neonatal intensive care unit (NICU), and newborn death.Results: The records of 7748 eligible mothers were included in the analysis. GDM was diagnosed in 1087 (14%) of mothers. Age was the only sociodemographic factor that differed significantly between GDM and non-GDM mothers. The Chi-square test result revealed that macrosomia, labor induction, instrumental deliveries, NICU admissions, and IUFD were more common in GDM mothers, while the incidence of CS, meconium fluid, and IUGR were less common in GDM mothers. The impact of GDM on adverse events of pregnancy and childbirth was evaluated using logistic regression analysis. GDM mothers had a significantly higher risk of macrosomia (aOR: 2.94, 95%CI: 1.71–4.61), labor induction (aOR: 3.14, 95%CI: 1.72–6.95), instrumental delivery (aOR: 3.16, 95%CI: 1.51–3.87), IUFD (aOR: 1.95, 95%CI: 1.17–3.06), and NICU admission (aOR: 2.19, 95%CI: 0.99–3.82). Other common complications, such as CS, postpartum hemorrhage, shoulder dystocia, childbirth trauma, and extensive perineal lacerations, were not significantly different between GDM and non-GDM mothers.Conclusions: Despite the higher incidence of labor induction and instrumental delivery, we found no significant association between GDM and adverse maternal outcomes. Regarding neonatal outcomes, GDM was linked to macrosomia, IUFD, and NICU admission.
Brown adipose tissue–associated postprandial thermogenesis in humans: Different effects of isocaloric meals rich in carbohydrate, fat, and protein
Authors: Aita Sayuri , Matsushita Mami , Yoneshiro Takeshi , Hatano Takuya , Kameya Toshimitsu , Ohkubo Iwao , Saito Masayuki 
Published: June 2022

Abstract
The increase of whole-body energy expenditure seen after a single meal ingestion, referred to as diet-induced thermogenesis (DIT), substantially varies depending on the meal’s macronutrient composition. Brown adipose tissue (BAT), a site of nonshivering thermogenesis, may be involved in DIT. To examine the effects of meal composition on BAT-associated DIT in humans, healthy male participants underwent [18F]fluorodeoxyglucose–positron emission tomography to assess BAT activity, and respiratory gas analysis for 2 hours after ingestion of a carbohydrate-, protein-, or fat-rich meal (C-meal, P-meal, and F-meal, respectively). The calculated DIT at 2 hours was 6.44 ± 2.01%, 3.49 ± 2.00%, and 2.32 ± 0.90% of the ingested energy after the P-meal, C-meal, and F-meal, respectively. The DIT after C-meal ingestion correlated positively with BAT activity (P = 0.011), and was approximately twice greater in the group with high-BAT activity than in the group with low-BAT activity (4.35 ± 1.74% vs. 2.12 ± 1.76%, P < 0.035). Conversely, the DIT after F-meal or P-meal ingestion did not correlate with BAT activity, with no difference between the two groups. Thus, BAT has a significant role in facultative DIT after ingestion of a carbohydrate-rich meal, but hardly after ingestion either protein- or fat-rich meal.
Network structure indexes to forecast epidemic spreading in real-world complex networks
Authors: Bellingeri Michele , Bevacqua Daniele , Turchetto Massimiliano , Scotognella Francesco , Alfieri Roberto , Nguyen Ngoc-Kim-Khanh , Le Thi Trang , Nguyen Quang , Cassi Davide 
Published: June 2022

Abstract
Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize the disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks.
Distribution patterns of astrocyte populations in the human cortex
Authors: Forrest Shelley L. , Kim Jordan Hanxi , Crockford Daniel R. , Huynh Katharine , Cheong Rosie , Knott Samantha , Kane Madison A. , Ittner Lars M. , Halliday Glenda M. , Kril Jillian J. 
Published: June 2022

Abstract
Astrocytes are a major class of glial cell in the central nervous system that have a diverse range of types and functions thought to be based on their anatomical location, morphology and cellular properties. Recent studies highlight that astrocyte dysfunction contributes to the pathogenesis of neurological conditions. However, few studies have described the pattern, distribution and density of astrocytes in the adult human cortex. This study mapped the distribution and density of astrocytes immunolabelled with a range of cytoskeletal and membrane markers in the human frontal cortex. Distinct and overlapping astrocyte populations were determined. The frontal cortex from ten normal control cases (75±9 years) was immunostained with glial fibrillary acidic protein (GFAP), aldehyde dehydrogenase-1 L1 (ALDH1L1), connexin-43 (Cx43), aquaporin-4 (AQP4), and glutamate transporter 1 (GLT-1). All markers labelled populations of astrocytes in the grey and white matter, separate cortical layers, subpial and perivascular regions. All markers were informative for labelling different cellular properties and cellular compartments of astrocytes. ALDH1L1 labelled the largest population of astrocytes, and Cx43-immunopositive astrocytes were found in all cortical layers. AQP4 and GLT-1 labelled distal astrocytic process and end-feet in the same population of astrocytes (98% of GLT-1-immunopositive astrocytes contained AQP4). This study highlights the diversity of astrocytes in the human cortex, providing a reference map of the distribution of distinct and overlapping astrocyte populations which can be used for comparative purposes in various disease, inflammatory and injury states involving astrocytes.
Multivariate outlier filtering for A-NFVLearn: an Advanced Deep VNF Resource Usage Forecasting Technique
Authors: St-Onge Cédric , Kara Nadjia , Edstrom Claes 
Published: June 2022

Abstract
Virtual Network Function Resource Adaptation (VNF-RA) aims at adequately adapting Network Function Virtualization Infrastructure (NFVI) resources according to the geographical fluctuation of user demand by maximizing the quality of service (QoS) of the offered services and the energy consumption of the NFVI while limiting the risks of Service Level Agreement (SLA) breaches, the CAPEX and OPEX of the cloud operators and their customers. Virtual Network Function (VNF) resource usage forecasting leads therefore a key role in enabling proactive resource adaptation in dynamic Network Function Virtualization (NFV) environments whose resource demand constantly changes. In parallel, Long Short-Term Memory (LSTM)-based prediction has garnered huge interest in the research community and several research teams have therefore proposed different VNF resource usage prediction algorithms based on this machine learning technique. However, current LSTM-based VNF resource usage forecasting techniques lack the flexibility to take several resource attributes of different scales, over many time steps, in order to predict several other resource attributes over many time steps from a Service Function Chain (SFC). In this paper, we push the state of the art forward by presenting A-NFVLearn, a flexible multivariate, LSTM-based model with an attention mechanism which uses different attributes of resource load history (CPU, memory, I/O bandwidth) from various VNFs of an SFC to forecast future load of multiple resources of a VNF. Next, we propose a multivariate outlier filtering scheme at pre-processing based on Adjusted Outlyingness (AO), which improves training time performance of LSTM-based models without impacting prediction accuracy.
Predictive Potential of ACE phenotyping in Extrapulmonary Sarcoidosis
Authors: Danilov Sergei M. , Kurilova Olga V. , Sinitsyn Valentin E. , Kamalov Armais A. , Garcia Joe GN , Dudek Steven M. 
Published: June 2022

Abstract
Background.Elevated ACE expression in tissues (reflected by blood ACE levels) is associated with increased risk of cardiovascular diseases and is a marker for granulomatous diseases. We developed a new approach for characterization of ACE status in the blood - ACE phenotyping - and established normal values of ACE levels as 50–150% of control pooled plasma.Methods.ACE phenotyping was performed in citrated plasma of 120 patients with known interstitial lung diseases and included 1) simultaneous determination of ACE activity with 2 substrates (ZPHL and HHL); 2) calculation of the ratio of hydrolysis of two substrates (ZPHL/HHL ratio); 3) determination of the levels of ACE immunoreactive protein and ACE conformation with a set of monoclonal antibodies (mAbs) to ACE.Results.In the 1st set of 100 patients, 22 patients had ACE levels > 150%; ACE phenotyping also objectively identified the presence of ACE inhibitors in the plasma of 15 patients. After excluding these patients and one other patient with ACE mutation that increases ACE shedding, 17 patients were identified as a suspicious for systemic sarcoidosis based on elevation of blood ACE (> 150% of mean). Our newly established parameter–ACE immunoreactivity (with mAb 9B9)—allowed us to detect 22 patients with decreased values (< 80%) of this parameter, which may indicate the presence of ACE in the blood that originates from macrophages/dendritic cells of granulomas. In the remaining 20 patients, this new parameter (mAbs binding/activity ratio) was calculated using 3 mAbs (9B9, 3A5 and i1A8 - having overlapping epitopes), and 8 patients were identified as having decreased levels, thus increasing dramatically the sensitivity for detection of patients with systemic sarcoidosis. Whole body PET scan confirmed extrapulmonary granulomas in some patients with lower immunoreactivity towards anti-ACE mAbs.Conclusions.These results demonstrate that ACE phenotyping has novel potential to noninvasively detect patients with systemic sarcoidosis.
Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (HIPEC) for ovarian cancer in an Australian institution: Lessons from 20 years experience
Authors: Farrell Rhonda , Liauw Winston , Morris David 
Published: June 2022

Abstract
Objectives: We report the 20-year experience of the largest Australian unit performing cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) for ovarian cancer and reflect on learning opportunities. Methods: A retrospective review of all cases of CRS for ovarian cancer at St George Peritonectomy Unit from Jan 1998- Jan 2018 was performed. Prospectively collected data include age, stage, histology, disease extent (PCI), completeness of cytoreduction (CC score), HIPEC regime, 30-day surgical morbidity, disease recurrence, and death. Survival was computed using Kaplan-Meier method and analysed using log-rank tests and Cox-proportional hazards models. Results: Forty-one women with advanced ovarian cancer (11 primary stage III/IV, 30 recurrent) underwent CRS, 29 (71%) with HIPEC. Most (68%) had high-volume disease (PCI >15). In 98%, CC0/CC1 (residual <2.5mm) was achieved. Fourteen (34%) had grade 3/4 complications, 1 patient (2%) died within 30 days and 2 patients (5%) died within 90 days. Progression-free and median overall survival was 30.0 and 67.0 months for primary cancer, and 6.7 and 18.1 months for recurrent cancer. Survival was associated with platinum-sensitivity, PCI£15, and CC score 0, but not HIPEC. Conclusion: This study reports outcomes for patients with advanced ovarian cancer patients treated in an Australian centre offering CRS and HIPEC. Whilst survival and morbidity outcomes were good for primary disease, they were poorer than predicted from the literature for cases of recurrent disease. The incorporation of evidence-based predictors of survival and multidisciplinary input are essential to achieve the best survival outcomes.