bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blood Pressure and Glomerular Filtration Rate in Youth With Tuberous Sclerosis Complex
Authors: Vargiami Efthymia , Stabouli Stella , Sidira Christina , Kyriazi Maria , Anastasiou Athanasia , Notopoulos Athanasios , Zafeiriou Dimitrios 
Published: April 2021

Abstract
Background
Renal involvement is very common in tuberous sclerosis complex (TSC) and is characterised by the development of angiomyolipoma and cysts. The aims of the present study were to assess kidney function and clinical features of renal involvement in TSC, including kidney function, and blood pressure (BP) levels in children, adolescents and young adults.
Methods
Non-selected patients with a definite diagnosis of TSC attending the paediatric neurology outpatient department of a tertiary hospital were included in a cross-sectional study. All participants had a renal imaging study within 6 months of ambulatory blood pressure (BP) and glomerular filtration rate (GFR) assessment. Data on demographics, history, genotype, kidney function at diagnosis and last imaging were collected.
Results
The median age of the patients was 15 years (IQR range 9 to18). 23.5% of the participants had ambulatory BP hypertension. Systolic BP levels correlated significantly with GFRDTPA values despite the absence of hyperfiltration. Greater increase in GFR from initial TSC diagnosis till the age of the assessment, resulted in higher GFR levels in childhood and adolescence in those that developed hypertension and possibly in those with angiomyolipoma or cysts. All patients with ambulatory BP hypertension had angiomyolipomas or cysts on renal imaging studies.
Conclusions
Hypertension may present with increased frequency in young patients with kidney disease associated with TSC. Routine ambulatory BP measurement could be part of the annual clinical assessment in patients with TSC.
Pilot Testing a Tracking Tool for High Need, High Cost Patients Enrolled in Complex Care Management in Safety-Net Settings
Authors: Yen Irene H. , Nápoles Tessa M. , Tan Sean , Shim Janet K. , Hellerstein Leah , Fleming Mark D. , Thompson-Lastad Ariana , Burke Nancy J. 
Published: April 2021

Abstract
Background: Complex Care Management (CCM) programs record patients’ progress toward health and healthcare utilization goals using a tracking tool in order to ascertain whether the patient is ready to transition to routine primary care. High-need, high-cost (HNHC) patients enrolled in CCM programs make progress, but existing tracking tools do not register the kinds of progress they make, suggesting that current tools may not be suitable in safety-net settings.Methods: We developed the Contextual Health Assessment of Social Stability (CHAOSS), which incorporates a patient’s social circumstances to capture patient experiences that affect their program participation. We used cognitive interviewing methods to test CHAOSS. We sought to understand if the CHAOSS tool could be used to track the kinds of progress CCM patients and providers find clinically relevant, would patients understand the questions and could the questions show meaningful distinctions in patient circumstances.Results: To set up the need for CHAOSS, we document the demographic and clinical characteristics of HNHC patients enrolled in CCM programs in safety-net settings. HNHC patients had extremely poor and volatile health, were economically vulnerable, and experienced challenges such as chronic homelessness. We found that CCM patients understood the CHAOSS questionnaire and generated an array of responses.Conclusion: CHAOSS appears to be a suitable tool for capturing HNHC patient experiences enrolled in CCM programs in safety-net settings.
Plant-derived Antimicrobials have Similar Cytotoxic Effects on Cancerous and Non-cancerous Cells
Authors: Ranjitkar Saurav , Zhang Delong , Sun Fei , Salman Saleh , He Wu , Venkitanarayanan Kumar , Tulman Edan R. , Tian Xiuchun 
Published: April 2021

Abstract
Essential oils and their active components, referred here as plant derived antimicrobials (PDAs), have been used for their antimicrobial, anti-inflammatory and antioxidant properties. Many reports also document PDAs’ cytotoxic effects on cancerous cells, raising the hope that they could be used for cancer treatments. Due to the lack of specificity, we hypothesize that PDAs are cytotoxic to both cancerous and non-cancerous cells. Trans-cinnamaldehyde (TCA), carvacrol, and eugenol were assessed for their cytotoxicity on cancerous HeLa cells and normal skin fibroblasts (CCD-1123Sk, CCD) by MTT and LDH assays, flow cytometry, and reverse transcription quantitative PCR (RT-qPCR). After 24 hours of treatment, carvacrol and TCA significantly decreased cell viability (by more than 50%) at 100 µg/ml, whereas eugenol was ineffective up to 400 µg/ml. Cell detachment and significantly increased apoptosis were observed with 100 µg/ml of TCA on both cell types. RT-qPCR for apoptotic genes (Bcl2, Casp3 and Casp8) and necrosis genes (Mlkl, Ripk1 and Ripk3) did not show significant differences between control and treated cells of both types, with the exception of eugenol-treated HeLa cells in which expression of Bcl2, Mlkl and Ripk1 was significantly higher than controls. Taken together, we conclude that the three PDAs studied here exhibited similar cytotoxic effects on both cancerous and non-cancerous cells.
Identification of the High-Risk Area for Schistosomiasis Transmission in China Based on Information Value and Machine Learning—A Newly Data-Driven Modeling Try
Authors: Gong Yan-Feng , Zhu Ling-Qian , Li Yin-Long , Zhang Li-Juan , Xue Jing-Bo , Xia Shang , Lv Shan , Xu Jing , Li Shi-Zhu 
Published: April 2021

Abstract
Objective

Information value (IV) and machine learning models were used to analyze and predict the high-risk distribution of schistosomiasis, in order to provide scientific evidence for disease surveillance and control in China.
Methods

The local case distribution from schistosomiasis surveillance data in China between 2005 and 2019 was assessed based on 19 variables including climate, geography, and social economy. Seven models were built in three categories including IV, three machine learning models (logistic regression, LR; random forest, RF; generalized boosted model, GBM), and three coupled models (coupled model of information value and logistic regression, IV + LR; coupled model of information value and random forest, IV + RF; coupled model of information value and generalized boosted model, IV + GBM). Accuracy, AUC (area under the curve), and F1-score were used to evaluate the prediction performance of the models. The best model was selected to predict the risk distribution for schistosomiasis.
Results

IV + GBM had the highest prediction effect (accuracy = 0.878, AUC = 0.902, F1 = 0.920). The results of IV + GBM showed that the risk area for transmission comprised 4.66% of China, mainly distributed in the coastal regions of the middle and lower reaches of the Yangtze River, the Poyang Lake region, and the Dongting Lake region. Risk areas can be divided into low-risk (2.47%), medium-risk (1.35%), and high-risk (0.84%). High-risk areas are primarily distributed in eastern Changde, western Yueyang, northeastern Yiyang, middle Changsha of the Hunan Province, southern Jiujiang, northern Nanchang, northeastern Shangrao, eastern Yichun in Jiangxi Province, southern Jingzhou, southern Xiantao, middle Wuhan in Hubei Province, southern Anqing, northwestern Guichi, eastern Wuhu in Anhui Province, middle Meishan, northern Leshan, and the middle of Liangshan in Sichuan Province.
Conclusions

The risk of schistosomiasis transmission in China still exists, with high-risk areas relatively concentrated within regions. Coupled models of IV and machine learning provide for effective analysis and prediction, forming a scientific basis for surveillance and control within key areas.
Structural, Vibrational, Quantum Chemical Calculations, Thermal and Antimicrobial Studies On Nitrate Salt Of 3-Nitroaniline
Authors: S Thangarasu , V Siva , S Asath Bahadur , S Athimoolam 
Published: April 2021

Abstract
In this work, 3-nitroanilinium nitrate (3NAN) has been synthesized and crystallized successfully by solution growth combined with solvent evaporation technique. 3NAN molecular structure has been optimized with Density Functional Theory (DFT) using B3LYP function and Hartree-Fock method with a 6-311 + + G(d,p) basis set. The geometrical parameters of the title molecules have been analyzed. The computed vibrational spectra were compared with experimental result which show appreciable agreement. Thermal stability of the crystal was analyzed with TGA/DTA and the melting points of the salt identified at 209 ºC. HOMO-LUMO energy calculations have shown the charge transfer within the molecu le. The possible pharmaceutical/biological activity of the salts confirmed by the Frontier Molecular Orbital (FMO) analysis have lower band gap value. The antimicrobial activity of grown crystals were tested against certain potentially threatening microbes.
The Social Representation of Coronavirus In the Polish Catholic Press
Authors: Zbróg Piotr 
Published: April 2021

Abstract
The article presents the components of the social representation of coronavirus discussed on the basis of headings from the most important religious periodicals in Poland. The object of research is currently one of the most frequently discussed and commented upon phenomena in the digital space. In addition to the cognitive image of SARS-CoV-2 which has been constructed in mainstream portals, the particular version produced by the Catholic media constitutes an interesting supplement. Basing on the analysis of the contexts for anchoring the coronavirus nomination, general elements of its social representation have been distinguished, e.g. “coronavirus is hindering participation in religious services”, “coronavirus is an opportunity for mankind”, “prayer fights the Covid pandemic”. This kind of perception of the coronavirus has prompted a large group of Catholics in Poland to form their own opinions about the pandemic, in digital and real space; this has subsequently determined the undertaking or abandoning of specific activities and provoked various polemical opinions.
Transcriptional Drug Repositioning Improves Development Of Somatic Cell Nuclear Transfer Embryos Via Inhibition Of CDK4/6 And Cyclin D1 During First Cleavage of Bovine Pseudo-Zygotes
Authors: Behdarvandiyan Paria , Hosseini Sayedeh Sahar , Jafarpour Farnoosh , Hajian Mehdi , Hosseini Morteza , Rahimi Mohsen , Moradi Reza , Motamedi Yasaman Kalantar , Bender Andreas , Nasr-Esfahani Mohammad Hossein 
Published: April 2021

Abstract
Since the birth of the first cloned sheep, ‘Dolly’, Somatic Cell Nuclear Transfer (SCNT) has become a powerful method in the fields of agricultural and biomedical research. However, due to the accumulation of errors during nuclear reprogramming, the efficiency of this technique remained low. In this study, we applied a transcriptional drug repositioning approach for selecting small molecules to improve SCNT efficiency. This involved identifying a blueprint signature of differentially expressed genes in SCNT embryos compared to IVF embryos and finding compounds that target those genes effectively. As a result of the analysis, two highly ranked compounds, namely the breast cancer treatment Palbociclib and the retinoid derivative Fenretinide, were selected which are selective inhibitor of the cyclin-dependent kinases 4/6 (CDK4/6) and inhibitor of Cyclin D1, respectively. We hypothesized that treatment of SCNT reconstructed oocytes during the first cleavage with these two small molecules may prolong the first cleavage in SCNT embryos, which can have a favorable impact on reprogramming by prolonging the exposure of the fibroblast cell to reprogramming factors in the oocyte. We found that the optimal concentration and time of treatment with either Palbociclib (100 nM for 12 h) and Fenretinide (16 µM for 6 h) prolonged the time of first cleavage in treated SCNT embryos, increased the cleavage rate after 72h and improved developmental competence of SCNT derived embryos similar to IVF embryos in vitro. Hence, a transcriptional drug repositioning approach was in this work for the first time applied successfully for improving bovine SCNT efficiency.
Impact of COVID-19 Pandemic on the Prevalence of Respiratory Viruses in Children With Lower Respiratory Tract Infections in China
Authors: Liu pengcheng , Xu Menghua , Cao Lingfeng , Su Liyun , Lu Lijuan , Dong Niuniu , Jia Ran , Zhu Xunhua , Xu Jin 
Published: April 2021

Abstract
Background: The multifaceted public health interventions taken during COVID-19 epidemic not only decrease the spreading of the SARS-CoV-2, but have impact on the prevalence of other viruses. This study aimed to explore the prevalence of common respiratory viruses among hospitalized children with lower respiratory tract infections (LRTIs) in China during the COVID-19 pandemic.Methods: Respiratory specimens were obtained from children with LRTIs at children’s hospital of Fudan University for detection of respiratory syncytial virus (RSV), adenovirus (ADV), parainfluenza virus (PIV) 1 to 3, influenza virus A (FluA), influenza virus B (FluB), human metapneumovirus (MPV) and rhinovirus (RV). The data were analyzed and compared between the year of 2020 (COVID-19 pandemic) and 2019 (before COVID-19 pandemic).Results: A total of 7107 patients were enrolled, including 4600 patients in 2019 and 2507 patients in 2020. Compared with 2019, we observed an unprecedented reduction of RSV, ADV, FluA, FluB, and MPV infections in 2020, despite of reopening of schools in June, 2020. However, The RV infection was significantly increased in 2020 and a sharp increase was observed especially after reopening of schools. Besides, the PIV infection showed resurgent characteristic after September of 2020. The mixed infections were significantly less frequent in 2020 compared with the year of 2019.Conclusions: The public health interventions during the COVID-19 pandemic have great impact on the prevalence of common respiratory viruses in China. Yet, we do need to be cautious for a possible resurgence and the resurgence may not follow the usual seasonal patterns such as RV and PIV, as COVID-19 restrictions are ongoing eased.
Slow Slip Events Following the 2002 Mw 7.1 Hualien Offshore Earthquake Afterslip
Authors: Chen Sean Kuanhsiang , Wu Yih-Min , Chan Yu-Chang 
Published: April 2021

Abstract
The recurrence intervals of slow slip events may increase gradually after a large earthquake during the afterslip. Stress perturbations during coseismic and postseismic periods may result in such an increase of intervals. However, the increasing recurrence intervals of slow slip events are rarely observed during an afterslip. The evolution process along with the afterslip remains unclear. We report an observation of slow slip events following the 2002 Mw 7.1 Hualien offshore earthquake afterslip in the southernmost Ryukyu subduction zone. Slow slip events in 2005, 2009, and 2015 are adjacent to the Mw 7.1 earthquake hypocenter. An increasing slow-slip interval of 3.1, 4.2, and 6.2 years has been observed after the earthquake. We calculated coseismic and postseismic slips from the Mw 7.1 earthquake and then estimated the Coulomb stress changes in the slow slip region. The Mw 7.1 earthquake has contributed positive Coulomb stresses to both the 2005 slow-slip region and 2009/2015 repeating slow-slip region. The coseismic and postseismic Coulomb stress change on the 2005 slow-slip region is approximately 0.05 MPa and 0.035 MPa, respectively. However, both Coulomb stress changes on the 2009/2015 repeating slow-slip region are not over 0.03 MPa. The ongoing afterslip following the Mw 7.1 earthquake last for at least five years, evolving with a decaying stress rate with time. The long-term stress perturbations may be able to trigger the 2005 slow slip event during the afterslip. The 2009 slow slip event seems to be influenced by the afterslip as well. Postseismic stress evolution and frictional and stressed conditions of the slow-slip region can be a reason to affect the evolution process of slow slip events intervals.
Activation of transient receptor potential vanilloid 4 protects articular cartilage against IL-1β-induced inflammatory responses by regulating the CaMKK/AMPK/NF-κB signaling pathway
Authors: Hattori Kyosuke , Takahashi Nobunori , Terabe Kenya , Ohashi Yoshifumi , Kishimoto Kenji , Yokota Yutaka , Suzuki Mochihito , Kojima Toshihisa , Imagama Shiro 
Published: April 2021

Abstract
Transient receptor potential vanilloid 4 (TRPV4) plays an important role in chondrocytes via Ca2+ signaling. However, its role in the progression of osteoarthritis is unclear. This study aimed to evaluate the effects of TRPV4 activation on articular cartilage and chondrocytes stimulated with interleukin (IL)-1β. Bovine and human articular chondrocytes were stimulated with various agents, including IL-1β, GSK1016790A (GSK101; a TRPV4 agonist), Compound C (an AMP-activated protein kinase (AMPK) inhibitor), and STO-609 (a calmodulin-dependent protein kinase kinase (CaMKK) inhibitor), and were processed for Western blot analysis and real-time PCR. The dimethylmethylene blue (DMMB) assay and Safranin O staining were also performed. GSK101 reversed the IL-1β-induced increase in expression of matrix metalloproteinase (MMP)-13 and decrease in expression of aggrecan. GSK101 also decreased proteoglycan release in the DMMB assay and retained Safranin O staining of articular cartilage tissue. Furthermore, GSK101 increased AMPK phosphorylation and decreased IL-1β-induced nuclear factor kappa B (NF-κB) phosphorylation. Compound C and STO-609 reversed the suppressive effects of GSK101 on NF-κB activation and MMP-13 expression. In conclusion, TRPV4 activation had chondroprotective effects on articular cartilage stimulated with IL-1β by activating CaMKK/AMPK and suppressing the NF-κB pathway. TRPV activators may offer a promising therapeutic option for preventing the progression of osteoarthritis.
An innovative method for rapid detection of urinary oxalate in goats with urolithiasis
Authors: Esfandiary Tina , Patel Suraj , Wanchoo Arun , Voigt Alexandria , Tao Samuel , Reuss Sarah , Nguyen Cuong 
Published: April 2021

Abstract
Background: Oxalate is a natural and abundant metabolic by-product; as a highly oxidized organic compound with powerful chelating activity, in high concentrations it can cause morbidity and mortality in both animals and humans. Elevated levels in urine (i.e., hyperoxaluria) have been found to correlate with several human diseases, especially urolithiasis or kidney stone disease (KSD)- a disease also prevalent in goats. Current methods for measuring oxalate are highly technical, cumbersome, and time-consuming, which often forces clinics to utilize expensive diagnostic laboratories. Therefore, in this study, we designed an innovative device, Oxalometer, to measure urinary oxalate in goats. Results: The results indicate that the Oxalometer performed as accurately as the standard commercially available test. The Oxalometer was able to measure higher levels of urinary oxalate in goats with urolithiasis compared to non-urolithiasis goats. The data demonstrate the accuracy and sensitivity of the Oxalometer. Conclusions: This proof-of-concept study supports the future application of the device in determining on-the-spot oxalate levels in patients and brings kidney stone prevention to point-of-care practice for ruminants.
Developing and validating an individual-level risk calculator for COVID-19 in the United States
Authors: Hu Xindi , Starling Jennifer , Lipman Erin , Pendl-Robinson Emma 
Published: April 2021

Abstract
COVID-19 is one of the leading causes of death in the United States. Certain subsets of the U.S. population account for a disproportionately large number of deaths, and risk varies widely across individuals. Evidence-based risk assessment tools customized to individuals can help users understand their risk level and risk management strategies. Here we present the 19andMe COVID-19 Risk Calculator that we developed and validated to assess COVID-19 risks based on geography, demographics, health condition and adherence to public health guidelines. The calculator, which is reviewed periodically to reflect the most recent evidence, is publicly available through both a web-based tool (167,276 visitors between April 1, 2020, and January 13, 2021) and an Application Programming Interface. To validate our methods, we compared risk scores for a set of users from Nexoid’s COVID-19 survival calculator (n = 51,799) using multiple publicly available calculators: 19andMe, Nexoid and the COVID-19 Estimated Risk (COVER). Mortality risk estimates were consistent between 19andMe and Nexoid, with 98.5% of users within 10% of each other (Spearman correlation rs = 0.91). We also correlated exposure risk estimates between 19andMe and Nexoid (rs = 0.48). The risk estimates for hospitalization, admission to intensive care unit and mortality were consistent between 19andMe and COVER (rs = 0.89, 0.87 and 0.93 respectively).
Adaptive Congestion Prediction in Vehicular Ad-hoc Networks (VANET) using Type-2 Fuzzy Model to Establish Reliable Routes
Authors: Giripunje Lokesh Manohar , Vidyarthi Abhay , Shandilya Shishir Kumar 
Published: April 2021

Abstract
In urban areas, a significant increase in vehicles day-by-day leads to challenges like accidents and pollution such as air and noise. The emission of Carbon dioxide (CO2) from vehicles leads to air pollution. The major cause of increased emission is traffic conditions in urban areas. Thus, Quality of Service (QoS) becomes a very challenging research problem by considering eco-friendly and reliable transportation. The appropriate congestion or traffic situation management techniques reduce the possibilities of accidents and pollution. The congestion control methods should take into account the properties such as fairness, decentralization, network characteristics, and application demands in VANET. The current methods failed to address all such properties and trade-offs for VANET communications. This paper proposed Adaptive Congestion Aware Routing Protocol (ACARP) for VANET using the dynamical artificial intelligence (AI) technique. In ACARP, the adaptive congestion detection algorithm is designed using the type-2 fuzzy logic AI technique. The fuzzy model builds to detect the congestion around each vehicle using three fuzzy-inputs such as bandwidth occupation, link quality, and moving speed. Using three parameters, the fuzzy rules are designed in the first phase. In the second phase, the inferences model introduced where the fuzzy decision has been made. In the last phase, defuzzifuzification is applied and the congestion probability estimated in the range of 0-1 for each vehicle. Then the status of congestion detection updated using the pre-defined threshold value for each vehicle. The status of congestion and its probability values have been utilized to establish safe and reliable routes for data transmission. It saves significant communication overhead and hence CO2 emissions in the network. The simulation results prove that the planned protocol improved the QoS presentation and significant CO2 emission compared to underlying fuzzy-based methods.