bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery of vaccine-like recombinant SARS-CoV-2 circulating in human
Authors: He Daniel Chang , He Cheng-Qiang 
Published: August 2022

Abstract
For viral diseases, vaccination with live attenuated vaccine (LAV) is one of the most effective means for fighting the diseases. However, LAVs are easy to spill from the vaccinated individuals and circulate in the population with unforeseen consequences. Currently, SARS-CoV-2 LAVs are undergoing clinical trials. In this study, we found that the recombinant viruses isolated from Indian SARS CoV-2 infected persons may be candidate LAV-derived strains, indicating the risk of SARS-CoV-2 LAV spillover from vaccinated persons, increasing the complexity of SARS-CoV-2 detection. In addition, the property of easy recombination of SARS-CoV-2 increases the chance of LAV virulence reversion. Therefore, how to distinguish the LAV viruses from the wild strain and how to avoid the recombination of the circulating vaccine strain and the wild strain are the challenges currently faced by SARS CoV-2 LAV development.
A post-quantum key exchange protocol from the intersection of quadric surfaces
Authors: Tullio Daniele Di , Gyawali Manoj 
Published: August 2022

Abstract
In this paper, we present a new key exchange protocol in which Alice and Bob have secret keys given by quadric surfaces embedded in a large ambient space by means of the Veronese embedding and public keys given by hyperplanes containing the embedded quadrics. Both of them reconstruct the isomorphism class of the intersection which is a curve of genus 1, and is uniquely determined by the j-invariant. An eavesdropper, to find this j-invariant, has to solve problems which are conjecturally quantum resistant.
Fast sensorimotor learning in middle-aged adults
Authors: Kyriazis Diana , Uji Makoto , Bouyagoub Samira , Cercignani Mara , Ford Paul , Sigala Natasha 
Published: August 2022

Abstract
Cognitive training offers a potential approach for the prevention of cognitive decline in later life. Repetition of targeted exercises may improve, or at least preserve, both specific domain and general cognitive abilities by strengthening neural connections and promoting neuroprotective processes within brain networks. Importantly, middle-aged adults have been omitted from the cognitive training literature. In this experiment, we investigated short-term training (1 session) on a perceptual-cognitive-motor task in middle-aged adults. Furthermore, we examined the functional and structural neural correlates of this training. Twenty-one healthy middle-aged adults between the age of 40 and 50 years underwent one scanning session during which they learned and performed the perceptual-cognitive-motor task. We compared performance and functional imaging on the Early and Late Learning phases of the task. We used diffusion MRI to examine baseline microstructural variation in the brain in relation to training outcome. The diffusion indices included fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), and orientation dispersion index (ODI). We found a significant improvement in performance following training on the task. There were also significant training-induced changes in functional activity in cortical and subcortical brain regions. Furthermore, significant correlations were found between the diffusion indices of FA, MD, and ODI and training outcome. These results show fast neuroplasticity in the middle-aged brain, and that variation in brain microstructure underpins fast motor learning.
Teaching-learning in Clinical Education Based on Epistemological Orientations: A Multi- method Study
Authors: Khani Hamed , Ahmady Soleiman , Sabet Babak , Zandi Shirdel , Mohammadimehr Mojgan , Niakan Somayeh 
Published: August 2022

Abstract
IntroductionTeaching-learning is the heart of medical education in the clinical setting. The objective of this research was to develop a conceptual model of effective clinical teaching in undergraduate medical education and conceptualize its operational framework based on the best fit approach.MethodsThis research consisted of three sub-studies conducted using a multi-method approach. The first sub-study was conducted using a qualitative meta-synthesis approach. The second sub-study used Clarke's situational analysis approach as a postmodern version of grounded theory. Finally, the third sub-study was designed in two stages. First, it was conducted using the expert panel, in the second step, framework of synthesis based on best fit, and the framework of Ottenhoff- de Jonge et al., which formed the basis of this study.ResultsIn the first sub-study, qualitative evidence on the factors of effective teaching-learning in clinical education was synthesized into five dimensions. Based on the second sub-study, the clinical teaching-learning situation in undergraduate medical education in Iran was represented in three maps, including situational, social worlds/arenas, and positional. Finally, in the third sub-study, based on model modification and development in the expert panel, the effective teaching-learning dimensions were developed into behavioral, social, pedagogical, technology, contextual, educational leadership, and financial dimensions. In the second step, based on the framework of Ottenhoff- de Jonge et al., a three-dimensional matrix was developed concerning epistemological orientations about teaching and learning.DiscussionMoving from a single teaching-centered and learning-centered orientation to a teaching-learning-centered orientation is required for effective teaching-learning in clinical medical education.
Social Support in Schools and Related Outcomes for LGBTQ Youth: A Scoping Review
Authors: Leung Enoch , Gomez Gabriela Kassel , Sullivan Samantha , Murahara Flavio , Flanagan Tara 
Published: August 2022

Abstract
Recent research has increasingly focused on positive factors and supports for LGBTQ youth. This scoping review explores existing social support for LGBTQ youth in schools through the ecological systems approach to respond to the following four objectives: 1) define social support systems in schools, 2) identify current research on outcomes for LGBTQ youth, 3) identify barriers to support LGBTQ youth in schools, and 4) identify areas for future research for LGBTQ youth and social support in schools. A systematic search (Arksey & O’Malley, 2005) between 2007 through 2021 resulted in 94 articles. This review gave rise to an organizational framework to consolidate various systems of social support for LGBTQ youth in schools. Social support consisted of seven social support systems (family, curriculum, family, peers, school policies, GSAs and programs, and school climate) that are positively associated with the promotion of positive socioemotional, behavioural, and educational outcomes for LGBTQ youth. Though the literature has been clear surrounding the risks associated with LGBTQ youth, this scoping review provides a positive outlook on LGBTQ youth’s school experiences and how these systems of social support allow for LGBTQ youth to act as active participants to foster a positive school climate and sense of safety.
Nuclear-anchored FGFR regulates cell proliferation and cisplatin resistance in pancreatic ductal adenocarcinoma
Authors: Yue Zhi-qiang 
Published: August 2022

Abstract
Background
In natural physiological conditions, FGF is a pleiotropic growth factor with multiple bio-activities and FGF/FGFR system has many important biological functions and roles. Interestingly, more and more evidences show that FGF/FGFR system plays an important role in the occurrence and development of pancreatic ductal adenocarcinoma.
Methods
In our study, we explored the cellular characteristics of FGF/FGFR system in pancreatic ductal adenocarcinoma cells. In addition, we also investigated the relationship between nuclear localized FGF/FGFR and cisplatin resistance. A series of experimental techniques including indirect immunofluorescence, Western-blot and ELISA were used to analyze the cellular characteristics of FGF/FGFR. We systematically assessed the cell behavior of IGF-1/IGF-1R in the Pancreatic ductal adenocarcinoma cell model.
Results
We have three main findings: First, we found that IGF-1R could transport into the cell nuclei of Pancreatic ductal carcinoma cell, and the nuclear-localized FGF/FGFR was closely related to the proliferation of Pancreatic ductal carcinoma cells. Additionally, we also found that the nuclear-localized FGF/FGFR might be closely associated with cisplatin resistance in pancreatic ductal adenocarcinoma, this may be a potential mechanism of cisplatin resistance; Secondly, we found that the nuclear-localized FGF/FGFR showed a positive correlation with the intensity of AKT signaling.
Conclusions
Taken together, this work lays the foundation for further research on the relationship between the nuclear FGF/FGFR and the pancreatic ductal adenocarcinoma development or cisplatin resistance in pancreatic ductal adenocarcinoma.
Typical and anomalous pathways of surface-floating material in the northern North Atlantic and Arctic Ocean
Authors: Herman Agnieszka , Wesławski Jan Marcin 
Published: August 2022

Abstract
Surface waters of the oceans carry large amounts of material, including sediment grains, plankton organisms, ice crystals, as well as pollutants, e.g., oil and plastic. Transport and spatio-temporal distribution of that material depend on its properties and on the dynamical processes in the ocean mixed layer – currents, waves, turbulence, and convective mixing – acting at a wide range of scales. Due to its importance for marine physics, biogeochemistry and ecology, substantial research effort has been put in recent years into observations and modelling of ocean material transport, especially in the context of marine plastic pollution. Nevertheless, many important questions remain unanswered. In this work, numerically simulated trajectories of surface-floating particles in the period 1993–2020 are used to analyze usual and anomalous transport pathways in the northern North Atlantic and the Arctic Ocean. Lagrangian trajectories are computed based on surface currents from a hydrodynamic model and Stokes drift from a spectral wave model. It is shown that due to high amplitudes of Stokes drift (comparable with wind-induced currents in ice-free parts of the domain of study), combined with its high directional variability, it substantially modifies the drifting paths, underlying the important role of wave-induced currents in surface material transport. A statistical analysis of ∼1.6·108 trajectories reveals patterns of connections between nearshore locations in the domain of study, the associated drift times and path sinuosity. Seasonal variability of transport, different in the Arctic Ocean and the North Atlantic, is found for typical transport routes following the larger-scale circulation patterns. Crucially, in both sub-domains episodic, but very strong transport events between otherwise isolated locations occur, associated with anomalous atmospheric circulation and, arguably, providing ‘windows of opportunity’ for dispersal of various organisms to new locations. It is shown for two examples in the North Atlantic region that an unusual combination of atmospheric circulation indices explains the anomalous transport, thus providing a predictive tool for future events. In the Arctic, analogous phenomena are modified by the state of the sea ice cover.
A Selective LVQ Algorithm for Improving Instance Reduction Techniques and its Application for Text Classification
Authors: Hayel Rafa , Hindi Khalil El , Hosny Manar , Alharbi Rawan , Alsalman Hussien 
Published: August 2022

Abstract

Instance-Based learning, such as the k Nearest Neighbor (kNN), is a simple yet effective machine learning algorithm for text classification. However, it may take long classification time and large memory requirement which motivated the development of instance reduction techniques that discard irrelevant and noisy instances. This usually comes at the expense of reducing the classification accuracy. This work proposes a Selective Learning Vector Quantization algorithm (SLVQ) and uses it to fine-tune the reduced datasets in a way that improves their representation of the full dataset. Unlike classical Learning Vector Quantization (LVQ) algorithms, SLVQ can deal with nominal attributes, while using the instances in the reduced datasets as the initial codebook vectors and using the original dataset to fine-tune them. The algorithm addresses the problem of dealing with nominal values, which is crucial, since many real-world datasets contain nominal attributes and require the use of an appropriate distance measure, such as the Value Distance Measure (VDM). SLVQ modifies the Value Difference Metric (VDM) distances between nominal values instead of modifying the weight vectors themselves. Our experimental results using four instance reduction algorithms and 17 text classification datasets demonstrate our approach’s effectiveness in improving the classification accuracy of the reduced sets.
Comparison of pneumonia incidence between long-acting muscarinic antagonist and inhaled corticosteroid plus long-acting beta agonist in patients with COPD : A retrospective cohort study in a real-world setting
Authors: Lee Eung Gu , Kim Youlim , Hwang Yong Il , Yoo Kwang Ha , Lee So Eun , Jung Kyung Yoon , Lee Doik , Park Yong Bum , Rhee Chin Kook 
Published: August 2022

Abstract
Background
Pneumonia is an infectious disease commonly associated with chronic obstructive pulmonary disease (COPD). However, few studies have directly compared the incidence of pneumonia in patients on common COPD treatments such as long-acting muscarinic antagonists (LAMA) with those on inhaled corticosteroids and long-acting β2-agonist (ICS/LABA). Moreover, risk factors for pneumonia in COPD are still unclear. We compared the incidence of pneumonia in COPD patients on LAMA and those on ICS/LABA and explored the risk factors associated with pneumonia.
Methods
This nationwide cohort study used Korean National Health Insurance claim data from January 2002 to April 2016. Patients who received COPD medication, either LAMA or ICS/LABA, with the COPD diagnostic code, were selected. We enrolled patients with good compliance (medication possession ratio ≥ 80%). The primary outcome was pneumonia in COPD patients initiating LAMA or ICS/LABA. We investigated the risk factors associated with pneumonia, including the sub-types of ICS treatments. The observation period was a minimum of 12 months and a maximum of 136 months.
Results
After propensity score matching, the incidence rate per 1,000 person-years of pneumonia was 93.96 for LAMA (n = 1,003) and 136.42 for ICS/LABA (n = 1,003) patients (p < 0.001). The adjusted hazard ratio (HR) for pneumonia in patients on fluticasone/LABA was 1.496 (95% confidence interval [CI] 1.204–1.859) compared with LAMA (p < 0.001). In multivariable analysis, a history of pneumonia was a risk factor associated with pneumonia (HR, 2.123; 95% CI, 1.580–2.852; p < 0.001).
Conclusions
The incidence of pneumonia was higher in COPD patients on ICS/LABA compared with those on LAMA. It is recommended that ICS use be avoided in COPD patients with high pneumonia risk.
Mine tailings-based geopolymers: Durability, microstructure, thermal and leaching properties
Authors: Akeed Mahmoud 
Published: August 2022

Abstract
The mining industry produces a considerable amount of stone waste and tailings, posing an ecological danger. This industrial waste is often disposed of via landfill, which leads to soil degradation and water and air pollution while obtaining valuable land. It can be recycled via a variety of methods, including the promising geopolymerization approach, which converts waste into value. This research investigates recent advancements in the production of geopolymer composites derived from industrial waste and mine tailings as a potential sustainable construction material. This research also provides in-depth analyses of the features and behaviours of mine tailings mixtures utilized in geopolymer production, such as their durability, microstructure, thermal and leaching capabilities. This study also reveals an information gap that must be addressed to progress mine tailings composites for cementitious materials.
The effects of coriander seed supplementation on serum glycemic indices, lipid profile and parameters of oxidative stress in patients with type 2 diabetes mellitus: a randomized double-blind placebo-controlled clinical trial
Authors: Zamany Sanaz , Mahdavi Aida Malek , Pirouzpanah Saeed , Barzegar Ali 
Published: August 2022

Abstract
Background: This research aimed to study the effect of coriander seed supplementation on serum glycemic indices, lipid profile and oxidative stress parameters in patients with type 2 diabetes mellitus (T2DM).Methods: In this randomized double-blinded, placebo-controlled trial, eligible 40 T2DM patients aged 30-60 years were recruited from Sina Hospital (Tabriz, Iran) and randomly assigned into two groups to receive either coriander seed powder (1000 mg/day, n=20) or placebo (1000 mg/day, n=20) for 6 weeks. Anthropometric measurements, dietary intake, and biochemical parameters including fasting blood sugar (FBS), serum insulin, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), total cholesterol (TC), triglyceride (TG), high- and low-density lipoprotein cholesterols (HDL-C and LDL-C), malondialdehyde (MDA), and total antioxidant capacity (TAC) were assessed before and after supplementation.Results: Anthropometric measurements were not significantly different between intervention and placebo groups. Coriander seed supplementation led to significant within-group reductions in FBS (156.15±23.19 to 130.30±21.15), serum insulin (17.72±0.47 to 17.12±0.76), HOMA-IR (6.82±0.95 to 5.52±0.99), TC (183.85±55.68 to 145.20±31.36), TG (152.50±37.59 to 130.40 ±27.96), LDL-C (127.35±23.45 to 111.40±25.71), and MDA (1.65±0.15 to 1.49±0.15), whereas there were significant increases observed in serum TAC (1.93±0.12 to 1.97±0.09) (P<0.05). Post-dose comparisons showed significant between-group differences for FBS, serum insulin, HOMA-IR, TC, TG, LDL-C, MDA, and TAC levels after adjusting for baseline values (P<0.05).Conclusions: Coriander seed supplementation was able to improve glycemic indices, lipid profile and oxidative stress status in T2DM and it may be useful complementary treatment in management of these patients.Trial registration: The study protocol was registered on the Iranian Registry of Clinical Trials website (IRCT20190224042821N2) on 2019/Oct/11.
Application of Computational Simulation Integrating Inhibition Kinetics
for Detecting Tyrosinase Inhibitor: Salsalate Is a New Inhibitor
Authors: Xu Jie-Hao , Lee Jinhyuk , Wang Wei , Park Yong-Doo 
Published: August 2022

Background:
Tyrosinase inhibitor developments have been widely attended by
investigators for their various applications.

Objective:
A combination of virtual screening of docking simulations and biochemical inhibition
kinetics was performed to find a new inhibitor of tyrosinase for the clinical application of an antipigment
agent.

Methods:
We conducted docking simulations to detect tyrosinase key binding residues and used the
detected binding residues to screen the NCBI PubChem database for probing tyrosinase binding
compounds. The serial inhibition kinetics and spectrofluorimetry measurements were performed to
validate the inhibitory effect on tyrosinase.

Results:
We have detected 200 candidates and categorized them into four clusters. Among them, we
successfully confirmed salsalate as a new inhibitor of tyrosinase measured by serial enzyme
kinetics. Salsalate was detected as a reversible inhibitor of tyrosinase displaying a typical mixedtype
inhibition manner (IC50 = 22.19 ± 1.01 mM; Ki = 19.98 ± 2.11 mM). Spectrofluorimetry
measurement by integrating with 1-anilinonaphthalene-8-sulfonate showed that salsalate mainly
induced a slight regional conformation distortion of the tyrosinase active site accompanied by a
slight hydrophobic disruption.

Conclusion:
Our study suggests that salsalate is a potential anti-pigment drug via inhibition of
tyrosinase activity and it might be applicable for dermatologic clinical application. Also, our study
enlarges an insight into the salsalate drug application.
Mild Behavioral Impairment: An Early Sign and Predictor of Alzheimer's
Disease Dementia
Authors: Jiang Fei , Cheng Cheng , Huang Jinsong , Chen Qiaoling , Le Weidong 
Published: August 2022

Background:
Alzheimer's disease (AD) is the most common form of dementia in the elderly
population and places heavy burdens on medical care and nursing. Recently, the psychiatric and
behavioral symptoms of prodromal AD, especially mild behavioral impairment (MBI), have attracted
much attention. In 2012, Alzheimer's Association International Conference, MBI was proposed as a
syndrome with psychiatric and behavioral disturbance before the onset of typical clinical cognitive
symptoms in dementia. Increasing lines of evidence have indicated the link between MBI and early
AD pathologies including Aβ and tau.

Objective:
This narrative review aims to summarize the advantages of MBI over other concept of
psychiatric and behavioral symptoms associated with AD in the early prediction of AD dementia. We
also discuss the possible common genetic basis and pathological mechanisms underlying the interactions
between MBI and AD.

Methods:
Papers cited here were retrieved from PubMed up to February 2022. We selected a total of
95 articles for summary and discussion.

Results:
The occurrence of MBI is mainly due to the overlapped genetic and pathological risk factors
with AD and is related to the brain's response to environmental stressors. MBI may be a warning sign
for the early pathology of AD, and more attention should be paid on the number and duration of MBI
symptoms.

Conclusion:
MBI may be an early sign and predictor of Alzheimer's disease dementia. Early intervention
for MBI may have a positive effect on alleviating long-term cognitive decline.